Microbial variability in growth and heat resistance of a pathogen and a spoiler: All variabilities are equal but some are more equal than others

A secondary model for the effect of pH on the variability in growth fitness of Listeria innocua strains

Variability in microbial growth is a keystone of modern Quantitative Microbiological Risk Assessment (QMRA). However, there are still significant knowledge gaps on how to model variability, with the most common assumption being that variability is constant. This is implemented by an error term (with constant variance) added on top of the secondary growth model (for the square root of the growth rate). However, this may go against microbial ecology principles, where differences in growth fitness among bacterial strains would be more prominent in the vicinity of the growth limits than at optimal growth conditions. This study coins the term "secondary models for variability", evaluating whether they should be considered in QMRA instead of the constant strain variability hypothesis. For this, 21 strains of Listeria innocua were used as case study, estimating their growth rate by the two-fold dilution method at pH between 5 and 10. Estimates of between-strain variability and experimental uncertainty were obtained for each pH using mixed-effects models, showing the lowest variability at optimal growth conditions, increasing towards the growth limits. Nonetheless, the experimental uncertainty also increased towards the extremes, evidencing the need to analyze both sources of variance independently. A secondary model was thus proposed, relating strain variability and pH conditions. Although the modelling approach certainly has some limitations that would need further experimental validation, it is an important step towards improving the description of variability in QMRA, being the first model of this type in the field.

Modeling strain variability in Campylobacter jejuni thermal inactivation by quantifying the number of strains required

There is a limited understanding of the survival responses of Campylobacter jejuni during thermal processing, which must be investigated for appropriate risk assessment and processing. Therefore, we aimed to elucidate the survival response of C. jejuni and develop a predictive model considering strain variability and uncertainty, which are important for quantitative microbial risk assessment (QMRA) or risk-based processing control measures. We employed the most probable curve (MPC) method to consider the uncertainty in cell concentrations. Further, the multivariate normal (MVN) distribution served as a model for strain variability in bacterial survival behavior. The prediction curves from the MVN successfully captured the parameter variability of the most probable curves of each strain. More than ten reference strains effectively described the strain variability in parameters using the MVN distribution. The findings indicated that, with sufficient strain data, the MVN could estimate the strain variability, including unknown strains. The multi-level model for strain variability can potentially become a specialized tool for QMRA and risk-based processing controls. The combined approach of MPC and MVN provides valuable insights into strain variability, emphasizing the importance of accounting for variability and uncertainty in predictive models for QMRA and risk-based processing control measures.

Thermal inactivation kinetics of Listeria monocytogenes in milk under isothermal and dynamic conditions

Thermal processing is a widely used method to ensure the microbiological safety of milk. Predictive microbiology plays a crucial role in quantifying microbial growth and decline, providing valuable guidance on the design and optimization of food processing operations. This study aimed to investigate the thermal inactivation kinetics of Listeria monocytogenes in milk under both isothermal and dynamic conditions. The thermal inactivation of L. monocytogenes was conducted under isothermal and non-isothermal conditions in sterilized and pasteurized milk, with and without background microbiota, respectively. Furthermore, a secondary model was developed between the shoulder effect and temperature, which was then integrated into the dynamic model. The results showed that L. monocytogenes grown in Tryptic Soy Yeast Extract Broth (TSBYE) prior to thermal inactivation exhibited higher heat resistance compared to cells grown in sterilized milk at isothermal temperatures of 60.0, 62.5, and 65℃. Moreover, the presence of background microbiota in milk significantly enhanced the heat resistance of L. monocytogenes, as evidenced by the increased D-values from 1.13 min to 2.34 min, from 0.46 min to 0.53 min, and from 0.25 min to 0.34 min at 60.0, 62.5, and 65 °C, respectively, regardless of whether the background microbiota was inactivated after co-growth or co-inactivated with L. monocytogenes. For non-isothermal inactivation, the one-step dynamic model based on the log-linear with shoulder model effectively described the microbial inactivation curve and exhibited satisfactory model performance. The model developed contributes to improved risk assessment, enabling dairy processors to optimize thermal treatment and ensure microbiological safety.

Microencapsulation and controlled release of Bacillus clausii through a novel non-digestible carbohydrate formulation as revolutionizing probiotic delivery

Probiotics have gained significant attention in recent years due to the growing awareness of physical health and well-being. However, maintaining high concentrations of probiotics throughout the product's shelf life and during the gastrointestinal tract is crucial for ensuring their health-promoting effects. After determining an optimal formulation through a fractional factorial model, this study optimizes probiotic Bacillus Clausii delivery through spray-drying microencapsulation using a novel maltodextrin-alginate-inulin (MDX-ALG-IN) formulation (optimized ratio: 7:2:1). Notably, this formulation exclusively comprises non-digestible carbohydrates, marking a novel approach in probiotic encapsulation. Achieving a high Product Yield (51.06 %) and Encapsulation Efficiency (80.53 %), the study employed SEM for morphological analysis, revealing an irregular form and extensive surface in dentations characteristic of maltodextrin involvement. With a low moisture content of 3.02 % (±0.23 %) and 90.52 % solubility, the powder displayed exceptional properties. Probiotic viability remained robust, surviving up to 60 % even after 180 days at 4 °C, 25 °C, and 37 °C. Thermal characterization unveiled microcapsule resilience, exhibiting a glass transition temperature (Tg) at 138.61 °C and a melting point of 177.28 °C. The study systematically addresses crucial aspects of microencapsulation, including formulation optimization, morphological characteristics, and powder properties. Notably, the MDX-ALG-IN microcapsules demonstrated stability in simulated gastrointestinal conditions, indicating potential application for supplements and complex food matrices. In summary, this research contributes to microencapsulation understanding, emphasizing the MDX-ALG-IN formulation's efficacy in preserving probiotic viability across production stages and simulated digestive processes.

Insight to the diversity of Photobacterium spp. isolated from European plaice (Pleuronectes platessa) based on phylogenetic analysis, phenotypic characterisation and spoilage potential

This study aimed to explore the diversity of fifty-four Photobacterium strains isolated from muscle tissue of European plaice (Pleuronectes platessa) caught at different fishing seasons and stored 14-days under various conditions. Single phylogenetic markers (16S rRNA, gapA, gyrB and recA) and multilocus sequence analysis (MLSA) were employed to classify isolates at species level. Furthermore, intra- and interspecies variability in the phenotypic traits, maximum specific growth rate (μmax) and spoilage potential of the Photobacterium isolates were investigated. The isolates were classified into the P. iliopiscarium (53.7 %), P. phosphoreum (40.7 %) and P. piscicola (5.6 %) clades using MLSA. Two housekeeping genes, gyrB and recA, exhibited a consistent phylogenetic relationship with MLSA, suggesting that they might be used as individual phylogenetic markers for the Photobacterium genus. Intra- and interspecies variability in the expression of phenotypic characteristics and the production of trimethylamine (TMA), inosine (HxR), and hypoxanthine (Hx) were observed. A growth optimum temperature for P. iliopiscarium was approximately 20 °C, while those for P. phosphoreum and P. piscicola were closer to 15 °C. All isolates exhibited the highest growth density at 1.5 % NaCl, followed by 0.5 %, 3 %, and 6 % NaCl. However, P. phosphoreum demonstrated a higher NaCl tolerance than the other two species. Although, the high CO2 atmosphere significantly inhibited the growth of all strains at 4 °C, P. phosphoreum and P. piscicola showed higher growth density at 15 °C than P. iliopiscarium. Notably, all strains demonstrated H2S production. The μmax varied considerably within each species, highlighting the significance of strain-level variability. This study demonstrates that P. iliopiscarium and P. piscicola, alongside P. phosphoreum, are efficient TMA-, HxR-, Hx-, and H2S-producers, suggesting their potential contribution to synergistic off-odour generation and spoilage. Moreover, the Photobacterium isolates seem to exhibit diverse adaptations to their environments, resulting in fluctuated growth and spoilage potential. Understanding intra- and interspecies variability will facilitate modelling seafood spoilage in microbial risk assessments and developing targeted hurdles to prolong products' shelf-life.

The importance of what we cannot observe: Experimental limitations as a source of bias for meta-regression models in predictive microbiology

Meta-regression models have gained in popularity during the last years as a way to create more generic models for Microbial Risk Assessments that also include variability. However, as with most meta-analyses and empirical models, systematic biases in the data can result in inaccurate models. In this article, we define experimental bias as a type of selection bias due to the practical limitations of microbial inactivation experiments. Conditions with extremely high D-values (i.e. slow inactivation) need very long experimental runs to cause significant reductions. On the other hand, when the D-value is extremely low, not enough data points can be gathered before the microbial population is below the detection limit. Consequently, experimental designs favour conditions within a practical experimental range, introducing a selection bias in the D-values. We demonstrate the impact of experimental bias in meta-regression models using numerical simulations. Models fitted to data with experimental bias overestimated the z-value and underestimated variability. We propose a rapid heuristic method to identify experimental bias in datasets, and we propose truncated regression to mitigate its impact in meta-regression models. Both methods were validated using simulated data. Thereafter the procedures were tested by building a meta-regression model for actual data for the inactivation of Bacillus cereus spores. We concluded that the dataset included experimental bias, and that it would cause an overestimation of the microbial resistance at high temperatures (>120 °C) for classical meta-regression models. This effect was mitigated when the model was built using truncated regression. In conclusion, we demonstrate that experimental bias could potentially result in inaccurate models for predictive microbiology. Therefore, checking for experimental bias should be a routine step in meta-regression modelling, and be included in guidelines on data analysis for meta-regression.

Predictive models for the growth of Salmonella spp., Listeria spp., and Escherichia coli in lettuce harvested on Taiwanese farms

This study aimed at developing predictive models for Salmonella, Listeria, and E. coli in lettuce iceberg (Lactuca sativa) locally grown in Taiwan. The models were developed under constant temperature levels (5, 10, 15, 20, and 25°C) and validated under dynamic temperature conditions (18°C for 4 h, 7°C for 48 h, 23°C for 4 h). The result showed that (1) all strains were unable to grow at 5°C except for standard strain of Listeria obtained from the BCRC and (2) the growth rate of locally isolated strains of Salmonella and Listeria was higher than the standard one at certain temperature levels and lower than the growth rates of E. coli. The findings in this study enhance our understanding about the growth variability between Salmonella, Listeria, and E. coli strains on vegetables locally grown in Taiwan and may be used to improve the management of proper storage temperature in the lettuce supply chain in this country. Considering the temperature recommendation for refrigerated food in Taiwan, the findings in this study therefore recommend that fresh vegetables (e.g., lettuce) should be stored at 5°C or lower to prevent the rapid growth of these microorganisms. Finally, the developed models can be used in the assessment of the microbiological risk of Salmonella, Listeria, and E. coli contamination in lettuce locally grown in Taiwan. PRACTICAL APPLICATION: This study developed predictive models describing the growth of Salmonella, Listeria, and E. coli in lettuce locally grown in Taiwan. The models developed in this study can be used in quantitative microbial risk assessment.

Strain Variability in Growth and Thermal Inactivation Characteristics of Listeria monocytogenes Strains after Acid Adaptation

ABSTRACT

Given the importance of strain variability to predictive microbiology and risk assessment, this study aimed to quantify the magnitude of strain variability in growth and thermal inactivation kinetics behaviors after acid adaptation. Thirty-three Listeria monocytogenes strains were exposed to acid-adapted tryptic soy broth supplemented with yeast extract (TSBYE; pH 5.5) and non-acid-adapted TSBYE (pH 7.0) for 20 h. Next, the growth parameters of these adapted and nonadapted strains that grew in nonbuffered TSBYE at 25°C were estimated. The tested strains were inactivated at 60°C in nonbuffered broth to obtain the heat resistance parameters. The results revealed that strain variability was present in the growth and thermal inactivation characteristics. The maximum specific growth rate ranged from 0.21 to 0.44 h-1 and from 0.20 to 0.45 h-1 after acid and nonacid adaptation, respectively. The lag times were from 0.69 to 2.56 h and from 0.24 to 3.36 h for acid-adapted and non-acid-adapted cells, respectively. The apparent D-values at 60°C of the pathogen ranged between 0.56 and 3.93 min and between 0.52 and 3.63 min for the presence and absence of acid adaptation condition, respectively. Acid adaptation significantly (P < 0.05) increased the magnitude of strain variability in the thermal inactivation characteristics of L. monocytogenes, with the coefficient of variation increasing to 0.17, whereas acid adaptation did not significantly (P ≥ 0.05) influence the variabilities in the growth parameters of the tested strains. Furthermore, the subsequent growth behaviors of all strains did not exhibit significant (P > 0.05) changes after exposure to acidic broth. However, the thermal resistance of most (25 of 33) of the tested strains increased (P < 0.05) after growing in acid-adapted broth. The relevant data generated in the present study can be used to describe the strain variability in predictive microbiology and to deeply understand the behavioral responses of different strains to acid adaptation.

HIGHLIGHTS

Competitive growth kinetics of Campylobacter jejuni, Escherichia coli O157:H7 and Listeria monocytogenes with enteric microflora in a small-intestine model

Aims

The biological events occurring during human digestion help to understand the mechanisms underlying the dose–response relationships of enteric bacterial pathogens. To better understand these events, we investigated the growth and reduction behaviour of bacterial pathogens in an in vitro model simulating the environment of the small intestine.

Methods and Results

The foodborne pathogens Campylobacter jejuni, Listeria monocytogenes and Escherichia coli O157:H7 were cultured with multiple competing enteric bacteria. Differences in the pathogen's growth kinetics due to the relative amount of competing enteric bacteria were investigated. These growth differences were described using a mathematical model based on Bayesian inference. When pathogenic and enteric bacteria were inoculated at 1 log CFU per ml and 9 log CFU per ml, respectively, L. monocytogenes was inactivated over time, while C. jejuni and E. coli O157:H7 survived without multiplying. However, as pathogen inocula were increased, its inhibition by enteric bacteria also decreased.

Conclusions

Although the growth of pathogenic species was inhibited by enteric bacteria, the pathogens still survived.

Significance and Impact of the Study

Competition experiments in a small‐intestine model have enhanced understanding of the infection risk in the intestine and provide insights for evaluating dose–response relationships.

Effect οf οxygen availability and pH οn adaptive acid tolerance response of immobilized Listeria monocytogenes in structured growth media

The aim of the present study was to evaluate the effect of oxygen availability (aerobic, hypoxic and anoxic conditions) and sub-optimal pH (6.2 and 5.5) in a structured medium (10% w/V gelatin) on the growth of two immobilized L. monocytogenes strains (C5, 6179) at 10 °C and their subsequent acid resistance (pH 2.0, e.g., gastric acidity). Anaerobic conditions resulted in lower bacterial population (P < 0.05) (7.8-8.2 log CFU/mL) at the end of storage than aerobic and hypoxic environment (8.5-9.0 log CFU/mL), a phenomenon that was intensified at lower pH (5.5), where no significant growth was observed for anaerobically grown cultures. Prolonged habituation of L. monocytogenes (15 days) at both pH increased its acid tolerance resulting in max. 10 times higher t_4D (appx. 60 min). The combined effect though of oxygen availability and suboptimal pH on L. monocytogenes acid resistance was found to vary with the strain. Anoxically grown cultures at pH 5.5 exhibited the lowest tolerance towards lethal acid stress, with countable survivors occurring only until 20 min of exposure at pH 2.0. Elucidating the role of oxygen limiting conditions, often encountered in structured foods, on acid resistance of L. monocytogenes, would assist in assessing the capacity of L. monocytogenes originated from different food-related niches to withstand gastric acidity and possibly initiate infection.

Quantification of Campylobacter jejuni gene expression after successive stresses mimicking poultry slaughtering steps

Broiler meat is considered as the most important source of the foodborne pathogen Campylobacter jejuni. Exposure to stress conditions encountered during the slaughtering process may induce bacterial adaptation mechanisms, and enhance or decrease pathogen resistance to subsequent stress. This adaptation may result from changes in bacterial gene expression. This study aims to accurately quantify the expression of selected C. jejuni genes after stresses inspired from the poultry slaughtering process. RT-qPCR was used to quantify gene expression of 44 genes in three strains after successive heat and cold stresses. Main results indicated that 26 genes out of 44 were differentially expressed following the successive thermal stresses. Three clusters of genes were differentially expressed according to the strain and the stress condition. Up-regulated genes mainly included genes involved in the heat shock response, whereas down-regulated genes belonged to metabolic pathways (such as lipid, amino-acid metabolisms). However, four genes were similarly overexpressed in the three strains; they might represent indicators of the thermal stress response at the species scale. Advances in the molecular understanding of the stress response of pathogenic bacteria, such as Campylobacter, in real-life processing conditions will make it possible to identify technological levers and better mitigate the microbial risk.

Assessing the survival and sublethal injury kinetics of Listeria monocytogenes under different food processing-related stresses

The foodborne pathogen L. monocytogenes can be present in food processing environments where it is exposed to various stressors. These antimicrobial factors, which aim to eliminate the pathogen, can induce sub-lethal injury to the bacterial cells. In the present study, we investigated the efficacy of different treatments (stresses) relevant to food processing and preservation as well as sanitation methods, in generating sub-lethal injury at 4 °C and 20 °C to two L. monocytogenes strains, ScottA and EGDe. Additionally, we evaluated the survival and extent of L. monocytogenes injury after exposure to commonly used disinfectants (peracetic acid and benzalkonium chloride), following habituation in nutrient-deprived, high-salinity medium. Each stress had a different impact on the survival and injury kinetics of L. monocytogenes. The highest injury levels were caused by peracetic acid which, at 4 °C, generated high populations of injured cells without loss of viability. Other injury-inducing stresses were lactic acid and heating. Long-term habituation in nutrient-limited and high salinity medium (4 °C) and subsequent exposure to disinfectants resulted in higher survival and injury in benzalkonium chloride and increased survival, yet with lower injury levels, in peracetic acid at 20 °C. Taken together, these results highlight the potential food safety risk emerging from the occurrence of injured cells by commonly used food processing methods. Consequently, in order to accurately assess the impact of an antimicrobial method, its potential of inducing sublethal injury needs to be considered along with lethality.

Modeling Invasion of Campylobacter jejuni into Human Small Intestinal Epithelial-Like Cells by Bayesian Inference

Current approaches used for dose-response modeling of low-dose exposures of pathogens rely on assumptions and extrapolations. These models are important for quantitative microbial risk assessment of food. A mechanistic framework has been advocated as an alternative approach for evaluating dose-response relationships. The objectives of this study were to investigate the invasion behavior of Campylobacter jejuni, which could arise as a foodborne illness even if there are low counts of pathogens, into Caco-2 cells as a model of intestinal cells and to develop a mathematical model for invading cell counts to reveal a part of the infection dose-response mechanism. Monolayer-cultured Caco-2 cells and various concentrations of C. jejuni in culture were cocultured for up to 12 h. The numbers of C. jejuni bacteria invading Caco-2 cells were determined after coculture for different time periods. There appeared to be a maximum limit to the invading bacterial counts, which showed an asymptotic exponential increase. The invading bacterial counts were higher with higher exposure concentrations (maximum, 5.0 log CFU/cm²) than with lower exposure concentrations (minimum, 0.6 log CFU/cm²). In contrast, the ratio of invading bacteria (number of invading bacteria divided by the total number of bacteria exposed) showed a similar trend regardless of the exposure concentration. Invasion of C. jejuni into intestinal cells was successfully demonstrated and described by the developed differential equation model with Bayesian inference. The model accuracy showed that the 99% prediction band covered more than 97% of the observed values. These findings provide important information on mechanistic pathogen dose-response relationships and an alternative approach for dose-response modeling.IMPORTANCE One of the infection processes of C. jejuni, the invasion behavior of the bacteria in intestinal epithelial cells, was revealed, and a mathematical model for prediction of the cell-invading pathogen counts was developed for the purpose of providing part of a dose-response model for C. jejuni based on the infection mechanism. The developed predictive model showed a high accuracy of more than 97% and successfully described the C. jejuni invading counts. The bacterial invasion predictive model of this study will be essential for the development of a dose-response model for C. jejuni based on the infection mechanism.

Incorporating strain variability in the design of heat treatments: A stochastic approach and a kinetic approach

For the design of thermal processes, the decimal reduction times (D-values) of target organisms can be used. However, many factors influence the D-value, like inherent organism's characteristics (strain variability), the effect of the history of the cells, as well as product factors and process factors. Strain variability is a very large contributor to the overall variation of the D-value. Hence, the overall reduction of microbial contaminants by a heat treatment is a combination of the occurrence of a strain with a certain heat resistance and its reduction given the prevailing conditions. This reduction can be determined using two approaches: a kinetic analysis based on integral equations or a stochastic approach based on Monte Carlo analysis. In this article, these two approaches are compared using as case studies the inactivation of two microorganisms: Listeria monocytogenes in a pasteurization process and the sporeformer Geobacillus stearothermophilus in a UHT process. Both approaches resulted in similar conclusions, highlighting that the strains with the highest heat resistance are determinant for the overall inactivation, even if the probability of cells having such extreme heat resistance is very low.

Variability in the heat resistance of Listeria monocytogenes under dynamic conditions can be more relevant than that evidenced by isothermal treatments

Heterogeneity in the response of microbial cells to environmental conditions is inherent to every biological system and can be very relevant for food safety, potentially being as important as intrinsic and extrinsic factors. However, previous studies analyzing variability in the microbial response to thermal treatments were limited to data obtained under isothermal conditions, whereas in the reality, environmental conditions are dynamic. In this article we analyse both empirically and through mathematical modelling the variability in the microbial response to thermal treatments under isothermal and dynamic conditions. Heat resistance was studied for four strains of Listeria monocytogenes (Scott A, CECT 4031, CECT 4032 and 12MOB052), in three different matrices (buffered peptone water, pH 7 Mcllvaine buffer and semi-skimmed milk). Under isothermal conditions, between-strain and between-media variability had no impact in the heat resistance, whereas it was very relevant for dynamic conditions. Therefore, the differences observed under dynamic conditions can be attributed to the variability in the ability for developing stress acclimation. The highest acclimation was observed in strain CECT 4031 (10-fold increase of the D-value), while the lowest acclimation was observed in strain CECT 4032 (50% increase of the D-value). Concerning the different media, acclimation was higher in buffered peptone water and semi-skimmed milk than in Mcllvaine buffer of pH 7.0. To the knowledge of the authors, this is the first research work that specifically analyses the variability of microbial adaptation processes that take place under dynamic conditions. It highlights that microbial heat resistance under dynamic conditions are sometimes determined by mechanisms that cannot be observed when cells are treated in isothermal conditions (e.g. acclimation) and can also be affected by variability. Consequently, empirical evidence on variability gathered under isothermal conditions should be extrapolated with care for dynamic conditions.

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

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

Multilevel modelling as a tool to include variability and uncertainty in quantitative microbiology and risk assessment. Thermal inactivation of Listeria monocytogenes as proof of concept

Variability is inherent in biology and also substantial for microbial populations. In the context of food safety risk assessment, it refers to differences in the response of different bacterial strains (between-strain variability) and different cells (within-strain variability) to the same condition (e.g. inactivation treatment). However, its quantification based on empirical observations and its incorporation in predictive models is a challenge for both experimental design and (statistical) analysis. In this article we propose the use of multilevel models to quantify (different levels of) variability and uncertainty and include them in the predictions. As proof of concept, we analyse the microbial inactivation of Listeria monocytogenes to thermal treatments including different levels of variability (between-strain and within-strain) and uncertainty. The relationship between the microbial count and time was expressed using a (non-linear) Weibullian model. Moreover, we defined stochastic hypotheses to describe the different types of variation at the level of the kinetic parameters, as well as in the observations (microbial counts). The model parameters (kinetic parameters and variances) are estimated using Bayesian statistics. The multilevel approach was compared against an analogous, single-level model. The multilevel methodology shrinks extreme parameter estimates towards the mean according to uncertainty, thus mitigating overfitting. In addition, this approach enables to easily incorporate different levels of variation (between-strain and/or within-strain variability and/or uncertainty) in the predictions. On the other hand, multilevel (Bayesian) models are more complex to define, implement, analyse and communicate than single-level models. Nevertheless, their ability to incorporate different sources of variability in predictions make them very suitable for Quantitative Microbial Risk Assessment.

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.

Assessment of Spoilage Bacterial Communities in Food Wrap and Modified Atmospheres-Packed Minced Pork Meat Samples by 16S rDNA Metagenetic Analysis

Although several studies have focused on the dynamics of bacterial food community, little is known about the variability of batch production and microbial changes that occur during storage. The aim of the study was to characterize the microbial spoilage community of minced pork meat samples, among different food production and storage, using both 16S rRNA gene sequencing and classical microbiology. Three batches of samples were obtained from four local Belgian facilities (A–D) and stored until shelf life under food wrap (FW) and modified atmosphere packaging (MAP, CO₂ 30%/O₂ 70%), at constant and dynamic temperature. Analysis of 288 samples were performed by 16S rRNA gene sequencing in combination with counts of psychrotrophic and lactic acid bacteria at 22°C. At the first day of storage, different psychrotrophic counts were observed between the four food companies (Kruskal-Wallist test, p-value < 0.05). Results shown that lowest microbial counts were observed at the first day for industries D and A (4.2 ± 0.4 and 5.6 ± 0.1 log CFU/g, respectively), whereas industries B and C showed the highest results (7.5 ± 0.4 and 7.2 ± 0.4 log CFU/g). At the end of the shelf life, psychrotrophic counts for all food companies was over 7.0 log CFU/g. With metagenetics, 48 OTUs were assigned. At the first day, the genus Photobacterium (86.7 and 19.9% for food industries A and C, respectively) and Pseudomonas (38.7 and 25.7% for food companies B and D, respectively) were dominant. During the storage, a total of 12 dominant genera (>5% in relative abundance) were identified in MAP and 7 in FW. Pseudomonas was more present in FW and this genus was potentially replaced by Brochothrix in MAP (two-sided Welch’s t-test, p-value < 0.05). Also, a high Bray-Curtis dissimilarity in genus relative abundance was observed between food companies and batches. Although the bacteria consistently dominated the microbiota in our samples are known, results indicated that bacterial diversity needs to be addressed on the level of food companies, batches variation and food storage conditions. Present data illustrate that the combined approach provides complementary results on microbial dynamics in minced pork meat samples, considering batches and packaging variations.

The presence of ochratoxin A does not influence Saccharomyces cerevisiae growth kinetics but leads to the formation of modified ochratoxins

Yeasts are able to reduce the levels of ochratoxin A in fermentative processes; and, through their enzymatic complex, these micro-organisms are also capable of forming modified mycotoxins. These mycotoxins are often underreported, and may increase health risks after ingestion of contaminated food. In this sense, this study aims to evaluate whether the presence of ochratoxin A influences yeast growth kinetic parameters and to elucidate the formation of modified ochratoxin by Saccharomyces cerevisiae strains during fermentation. Three S. cerevisiae strains (12 M, 01 PP, 41 PP) were exposed to OTA at the concentrations of 10, 20 and 30 μg/L. The Baranyi model was fitted to the growth data (Log CFU/mL), and the identification of modified ochratoxins was performed through High Resolution Mass Spectrometry. The presence of ochratoxin A did not influence the growth of S. cerevisiae strains. Four pathways were proposed for the metabolization of OTA: dechlorination, hydrolysis, hydroxylation, and conjugation. Among the elected targets, the following were identified: ochratoxin α, ochratoxin β, ochratoxin α methyl ester, ochratoxin B methyl ester, ethylamide ochratoxin A, ochratoxin C, hydroxy-ochratoxin A, hydroxy-ochratoxin A methyl ester, and ochratoxin A cellobiose ester. These derivatives formed from yeast metabolism may contribute to the occurrence of underreporting levels of total mycotoxin in fermented products.

The resistance of Bacillus, Bifidobacterium, and Lactobacillus strains with claimed probiotic properties in different food matrices exposed to simulated gastrointestinal tract conditions

The resistance of Bifidobacterium, Lactobacillus, and Bacillus strains with claimed probiotic properties in different food matrices was evaluated. Lactobacillus paracasei PXN 37, Lactobacillus acidophilus La-5, Bifidobacterium animalis subsp. lactis Bb-12, Bifidobacterium breve PXN 25, Bacillus subtilis PXN 21, Bacillus coagulans GBI30 6086 and Bacillus coagulans MTCC 5856 strains were inoculated in "requeijão cremoso" cheese, pasteurized orange juice, and bread. Further, the counts of the strains with claimed probiotic properties were determined throughout the products' shelf-life. Additionally, the survival (%), at the beginning and at the end of their shelf-life, of each strain with claimed probiotic properties inoculated in the three foods was estimated by using a static in vitro system simulating the gastric (pH 2), enteric I (pH 5) and enteric II (pH 7) phases of gastrointestinal tract (GIT). Overall, it has been found that the Bacillus strains with claimed probiotic properties showed greater viability than probiotic Bifidobacterium and Lactobacillus strains no matter the food studied. The percentage of survival of the Bacillus strains with claimed probiotic properties were always above 83%. The Bacillus strains with claimed probiotic properties were able to survive well in all the food matrices tested. Therefore, this study shows that these strains of Bacillus may comprise a feasible strategy for expanding the range of "probiotic food" choices given their high resistance to the composition of foods, manufacturing steps, and resistance to simulated GIT conditions.

Underscoring interstrain variability and the impact of growth conditions on associated antimicrobial susceptibilities in preclinical testing of novel antimicrobial drugs

In the era of multidrug resistant (MDR) organisms, reliable efficacy testing of novel antimicrobials during developmental stages is of paramount concern prior to introduction in clinical trials. Unfortunately, interstrain variability is often underappreciated when appraising the efficacy of innovative antimicrobials as preclinical testing of a limited number of standardized strains in unvarying conditions does not account for the vastness and potential for hyperdiversity among and within microbial populations. In this review, the importance of accounting for interstrain variability's potential to impact breadth of novel drug efficacy evaluation in the early stages of drug development will be discussed. Additionally, testing under varying microenvironmental conditions that may influence drug efficacy will be discussed. Biofilm growth, the influence of polymicrobial growth, mechanisms of antimicrobial resistance, pH, anaerobic conditions, and other virulence factors are some of critical issues that require more attention and standardization during preclinical drug efficacy evaluation. Furthermore, potential solutions for addressing this issue in pre-clinical antimicrobial development are proposed via centralization of microbial characterization and drug target databases, testing of a large number of clinical strains, inclusion of mutator strains in testing and the use of growth parameter mathematical models for testing.

A quantitative study on growth variability and production of ochratoxin A and its derivatives by A. carbonarius and A. niger in grape-based medium

Aspergillus carbonarius and Aspergillus niger are the main responsible fungi for the accumulation of ochratoxin A (OTA) in wine grapes. Some strains are able to convert the parent mycotoxin into other compounds by means of hydrolysis and/or conjugation reactions through their defense mechanisms and enzymatic activity, leading to the formation of a modified mycotoxin. Thus, the variability of growth and metabolite production are inherent to the strain, occurring distinctively even when submitted to similar conditions. In this sense, this contribution aimed at determining the variability in multiplication and production of OTA by strains of A. carbonarius and A. niger isolated from grapes, as well as investigating the formation of modified mycotoxins. Strains were incubated in grape-based medium, and the diameter of the colonies measured daily. The determination of OTA was performed by high-performance liquid chromatography and the identification of modified mycotoxins was carried out using high-resolution mass spectrometry. Variabilities in terms of growth and OTA production were assessed across five different strains. Peak production of OTA was detected on day 15, and a decline on day 21 was observed, indicating that the observed reduction may be associated with the degradation or modification of the OTA over time by the fungus. Ethylamide ochratoxin A, a modified mycotoxin identified in this study, provides evidence that there may be underreporting of total mycotoxin levels in food, increasing uncertainty concerning health risks to the population.

Quantifying the Responses of Three Bacillus cereus Strains in Isothermal Conditions and During Spray Drying of Different Carrier Agents

Spray drying is a widely used method for producing milk powder. This process is not aimed to cause microbial inactivation, thus sporeforming bacteria may be abundant in the microbiota of milk powder. The first aim of this study was to determine the inactivation kinetics parameters in capillary tubes of three Bacillus cereus strains (436, B63, 540) in three menstrua (whole milk, phosphate buffer, and talc suspension) at 90, 100, and 110°C. D-values for B. cereus in the three menstrua were not significantly different at the highest tested temperature (p > 0.05). Thus, talc was chosen as a carrier agent to allow the recovery of B. cereus from spray dried materials given its low interference on inactivation kinetics. B. cereus spores were also inoculated in whole milk and skim milk following spray drying at 95, 105, and 110°C (outlet temperature). After the spray drying runs, B. cereus spores were counted and the number of decimal reductions (γ) calculated. A correlation between the small diameter of the particles with the survival of spores of three B. cereus strains was found, and B. cereus 436 presented consistently the lowest γ no matter temperature and a carrier agent. The highest γ was found when talc powder was used, which suggest that this carrier agent does not protect B. cereus spores during spray drying. Spray drying of milk can lead to up to 4 γ (strain 540) of B. cereus spores but depending on the strain less than one γ (strain 436) could be observed. This study contributes to the knowledge on the microbiology of low water activity foods by providing novel findings regarding the fate of three B. cereus strains to different spray drying conditions. Acknowledging the variability of inactivation of B. cereus during spray drying is key in the current context of food safety in which the quantification of effects of unit operations must be known for the validation of processes and development of more robust formulations.

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.

From Culture-Medium-Based Models to Applications to Food: Predicting the Growth of B. cereus in Reconstituted Infant Formulae

Predictive models of the growth of foodborne organisms are commonly based on data generated in laboratory medium. It is a crucial question how to apply the predictions to realistic food scenarios. A simple approach is to assume that the bias factor, i.e., the ratio between the maximum specific growth rate in culture medium and the food in question is constant in the region of interest of the studied environmental variables. In this study, we investigate the validity of this assumption using two well-known link functions, the square-root and the natural logarithm, both having advantageous properties when modeling the variation of the maximum specific growth rate with temperature. The main difference between the two approaches appears in terms of the respective residuals as the temperature decreases to its minimum. The model organism was Bacillus cereus. Three strains (B594, B596, and F4810/72) were grown in Reconstituted Infant Formulae, while one of them (F4810/72) was grown also in culture medium to calculate the bias factor. Their growth parameters were estimated using viable count measurements at temperatures ranging from 12 to 25°C. We utilized the fact that, if the bias factor is independent of the temperature, then the minimum growth temperature parameter of the square-root model of Ratkowsky et al. (1982) is the same for culture medium and food. We concluded, supported also by mathematical analysis, that the Ratkowsky model works well but its rearrangement for the natural logarithm of the specific growth rate is more appropriate for practical regression. On the other hand, when analyzing mixed culture data, available in the ComBase database, we observed a trend different from the one generated by pure cultures. This suggests that the identity of the strains dominating the growth of mixed cultures depends on the temperature. Such analysis can increase the accuracy of predictive models, based on culture medium, to food scenarios, bringing significant saving for the food industry.