Consumers' behavior in quantitative microbial risk assessment for pathogens in raw milk: Incorporation of the likelihood of consumption as a function of storage time and temperature

Foodborne disease as a result of raw milk consumption is an increasing concern in Western countries. Quantitative microbial risk assessment models have been used to estimate the risk of illness due to different pathogens in raw milk. In these models, the duration and temperature of storage before consumption have a critical influence in the final outcome of the simulations and are usually described and modeled as independent distributions in the consumer phase module. We hypothesize that this assumption can result in the computation, during simulations, of extreme scenarios that ultimately lead to an overestimation of the risk. In this study, a sensorial analysis was conducted to replicate consumers' behavior. The results of the analysis were used to establish, by means of a logistic model, the relationship between time\u2013temperature combinations and the probability that a serving of raw milk is actually consumed. To assess our hypothesis, 2 recently published quantitative microbial risk assessment models quantifying the risks of listeriosis and salmonellosis related to the consumption of raw milk were implemented. First, the default settings described in the publications were kept; second, the likelihood of consumption as a function of the length and temperature of storage was included. When results were compared, the density of computed extreme scenarios decreased significantly in the modified model; consequently, the probability of illness and the expected number of cases per year also decreased. Reductions of 11.6 and 12.7% in the proportion of computed scenarios in which a contaminated milk serving was consumed were observed for the first and the second study, respectively. Our results confirm that overlooking the time\u2013temperature dependency may yield to an important overestimation of the risk. Furthermore, we provide estimates of this dependency that could easily be implemented in future quantitative microbial risk assessment models of raw milk pathogens

Stochasticity in Colonial Growth Dynamics of Individual Bacterial Cells

Conventional bacterial growth studies rely on large bacterial populations without considering the individual cells. Individual cells, however, can exhibit marked behavioral heterogeneity. Here, we present experimental observations on the colonial growth of 220 individual cells of Salmonella enterica serotype Typhimurium using time-lapse microscopy videos. We found a highly heterogeneous behavior. Some cells did not grow, showing filamentation or lysis before division. Cells that were able to grow and form microcolonies showed highly diverse growth dynamics. The quality of the videos allowed for counting the cells over time and estimating the kinetic parameters lag time ( ) and maximum specific growth rate ( max) for each microcolony originating from a single cell. To interpret the observations, the variability of the kinetic parameters was characterized using appropriate probability distributions and introduced to a stochastic model that allows for taking into account heterogeneity using Monte Carlo simulation. The model provides stochastic growth curves demonstrating that growth of single cells or small microbial populations is a pool of events each one of which has its own probability to occur. Simulations of the model illustrated how the apparent variability in population growth gradually decreases with increasing initial population size (N0). For bacterial populations with N 0 of >100 cells, the variability is almost eliminated and the system seems to behave deterministically, even though the underlying law is stochastic. We also used the model to demonstrate the effect of the presence and extent of a nongrowing population fraction on the stochastic growth of bacterial populations

Strain effect on the heterogeneity of individual-cell growth kinetics of Salmonella Typhimurium

The present study showed that the variability of individual-cell growth kinetics may differ among strains of S. Typhimurium. The results provide useful quantitative information for incorporating strain variability and heterogeneity in individual-cell behavior in stochastic growth models and risk assessment studies

Modelling biofilm formation of Salmonella enterica ser. Newport as a function of pH and water activity

The effect of pH and water activity (aw) on the formation of biofilm by Salmonella enterica ser. Newport, previously identified as a strong biofilm producer, was assessed. Biofilm formation was evaluated in tryptone soy broth at 37 C and at different combinations of pH (3.3e7.8) and aw (0.894e0.997). In total, 540 biofilm formation tests in 108 pH and aw combinations were carried out in polystyrene microtiter plates using crystal violet staining and optical density (OD; 580 nm) measurements. Since the individual effects of pH and aw on biofilm formation had a similar pattern to that observed for microbial growth rate, cardinal parameter models (CPMs) were used to describe these effects. CPMs described successfully the effects of these two environmental parameters, with the estimated cardinal values of pHmin, pHopt, pHmax, awmin and awopt being 3.58, 6.02, 9.71, 0.894 and 0.994, respectively. The CPMs assumption of the multiplicative inhibitory effect of environmental factors was validated in the case of biofilm formation using additional independent data (i.e. 430 OD data at 86 different combinations of pH and aw). The validation results showed a good agreement (r2 ¼ 0.938) between observed and predicted OD with no systematic error. In the second part of this study, a probabilistic model predicting the pathogen's biofilm formation boundaries was developed, and the degree of agreement between predicted probabilities and observations was as high as 99.8%. Hence, the effect of environmental parameters on biofilm formation can be quantitatively expressed using mathematical models, with the latter models, in turn, providing useful information for biofilm control in food industry environments

Adaptation of Listeria monocytogenes in a simulated cheese medium: effects on virulence using the Galleria mellonella infection model

The aim of this study was to evaluate the effect of the acid and salt adaptation in a cheese-based medium on the virulence potential of Listeria monocytogenes strains isolated from cheese and dairy processing environment using the Galleria mellonella model. Four L.monocytogenes strains were exposed to a cheese-based medium in conditions of induction of an acid tolerance response and osmotolerance response (pH 5 center dot 5 and 3 center dot 5% w/v NaCl) and injected in G.mellonella insects. The survival of insects and the L.monocytogenes growth kinetics in insects were evaluated. The gene expression of hly, actA and inlA genes was determined by real-time PCR. The adapted cells of two dairy strains showed reduced insect mortality (P<0 center dot 05) in comparison with nonadapted cells. Listeria monocytogenes Scott A was the least virulent, whereas the cheese isolate C882 caused the highest insect mortality, and no differences (0 center dot 05) was found between adapted and nonadapted cells. The gene expression results evidenced an overexpression of virulence genes in cheese-based medium, but not in simulated insect-induced conditions. Our results suggest that adaptation to low pH and salt in a cheese-based medium can affect the virulence of L.monocytogenes, but this effect is strain dependent. Significance and Impact of the Study In this study, the impact of adaptation to low pH and salt in a cheese-based medium on L.monocytogenes virulence was tested using the Wax Moth G.mellonella model. This model allowed the differentiation of the virulence potential between the L.monocytogenes strains. The effect of adaptation on virulence is strain dependent. The G.mellonella model revealed to be a prompt method to test food-related factors on L.monocytogenes virulence.Fundacao para a Ciencia e Tecnologia (FCT); IBB/CBME, LA, FEDER/The authors are grateful for the support of Fundação para a Ciência e Tecnologia (FCT) and IBB/CBME, LA, FEDER

The public health risk posed by Listeria monocytogenes in frozen fruit and vegetables including herbs, blanched during processing

A multi-country outbreak ofListeria monocytogenesST6 linked to blanched frozen vegetables (bfV)took place in the EU (2015–2018). Evidence of food-borne outbreaks shows thatL. monocytogenesisthe most relevant pathogen associated with bfV. The probability of illness per serving of uncooked bfV,for the elderly (65–74 years old) population, is up to 3,600 times greater than cooked bfV and verylikely lower than any of the evaluated ready-to-eat food categories. The main factors affectingcontamination and growth ofL. monocytogenesin bfV during processing are the hygiene of the rawmaterials and process water; the hygienic conditions of the food processing environment (FPE); andthe time/Temperature (t/T) combinations used for storage and processing (e.g. blanching, cooling).Relevant factors after processing are the intrinsic characteristics of the bfV, the t/T combinations usedfor thawing and storage and subsequent cooking conditions, unless eaten uncooked. Analysis of thepossible control options suggests that application of a complete HACCP plan is either not possible orwould not further enhance food safety. Instead, specific prerequisite programmes (PRP) andoperational PRP activities should be applied such as cleaning and disinfection of the FPE, water control,t/T control and product information and consumer awareness. The occurrence of low levels ofL. monocytogenesat the end of the production process (e.g.<10 CFU/g) would be compatible with thelimit of 100 CFU/g at the moment of consumption if any labelling recommendations are strictly followed(i.e. 24 h at 5°C). Under reasonably foreseeable conditions of use (i.e. 48 h at 12°C),L. monocytogeneslevels need to be considerably lower (not detected in 25 g). Routine monitoring programmes forL. monocytogenesshould be designed following a risk-based approach and regularly revised based ontrend analysis, being FPE monitoring a key activity in the frozen vegetable industry

Spatial temperature profiling by semi-passive RFID loggers for perishable food transportation

Perishable food products are at risk of suffering various damages along the cold chain. The parties involved should control and monitor the conditions of goods in order to ensure their quality for consumers and to comply with all legal requirements. Among environmental parameters during transport, temperature is the most important in prolonging the shelf life of the products. Radio Frequency IDentification (RFID) is an emergent technology that has proven its suitability for tracking and tracing in logistics. This paper shows how miniaturized RFID temperature loggers can be adapted to analyze the amount of local deviations, detect temperature gradients, and estimate the minimum number of sensors that are necessary for reliable monitoring inside a truck or container. These devices are useful tools for improving the control during the transport chain and detecting weaknesses by identifying specific problem areas where corrective actions are necessitated. In a first step, the RFID tags were tested by studying the temperature distribution in a pallet. Then, 15 shipments from a wholesale company in Germany in compartmented trucks were monitored, covering different temperature range conditions. During transport, several temperature differences were found in the same compartment. Using a factorial Analysis of Variance (ANOVA) the influence of different factors has been studied, such as: the location of the logger, type of truck, and external temperature. The shelf life, or keeping quality model, was applied to the recorded temperature profiles. Suggestions for future research areas are also discussed

Predictive models for bacterial growth in sea bass (Dicentrarchus labrax) 1 stored on ice

The final publication is available at Springer."The purpose of this paper was to estimate microbial growth through predictive modelling as a key element in determining the quantitative microbiological contamination of sea bass stored on ice and cultivated in different seasons of the year. In the present study, two different statistical models were used to analyse changes in microbial growth in whole, ungutted sea bass (Dicentrarchus labrax) stored on ice. The total counts of aerobic mesophilic and psychrotrophic bacteria, Pseudomonas sp., Aeromonas sp., Shewanella putrefaciens, Enterobacteriaceae, sulphide-reducing Clostridium and Photobacterium phosphoreum were determined in muscle, skin and gills over an 18-day period using traditional methods and evaluating the seasonal effect. The results showed that specific spoilage bacteria (SSB) were dominant in all tissues analysed but were mainly found in the gills. Predictive modelling showed a seasonal effect among the fish analysed. The application of these models can contribute to the improvement of food safety control by improving knowledge of the microorganisms responsible for the spoilage and deterioration of sea bass.