Predictive Population Dynamics of Escherichia coli O157:H7 and Salmonella enterica on Plants: a Mechanistic Mathematical Model Based on Weather Parameters and Bacterial State.

Weather affects key aspects of bacterial behavior on plants but has not been extensively investigated as a tool to assess risk of crop contamination with human foodborne pathogens. A novel mechanistic model informed by weather factors and bacterial state was developed to predict population dynamics on leafy vegetables and tested against published data tracking Escherichia coli O157:H7 (EcO157) and Salmonella enterica populations on lettuce and cilantro plants. The model utilizes temperature, radiation, and dew point depression to characterize pathogen growth and decay rates. Additionally, the model incorporates the population level effect of bacterial physiological state dynamics in the phyllosphere in terms of the duration and frequency of specific weather parameters. The model accurately predicted EcO157 and S. enterica population sizes on lettuce and cilantro leaves in the laboratory under various conditions of temperature, relative humidity, light intensity, and cycles of leaf wetness and dryness. Importantly, the model successfully predicted EcO157 population dynamics on 4-week-old romaine lettuce plants under variable weather conditions in nearly all field trials. Prediction of initial EcO157 population decay rates after inoculation of 6-week-old romaine plants in the same field study was better than that of long-term survival. This suggests that future augmentation of the model should consider plant age and species morphology by including additional physical parameters. Our results highlight the potential of a comprehensive weather-based model in predicting contamination risk in the field. Such a modeling approach would additionally be valuable for timing field sampling in quality control to ensure the microbial safety of produce. IMPORTANCE Fruits and vegetables are important sources of foodborne disease. Novel approaches to improve the microbial safety of produce are greatly lacking. Given that bacterial behavior on plant surfaces is highly dependent on weather factors, risk assessment informed by meteorological data may be an effective tool to integrate into strategies to prevent crop contamination. A mathematical model was developed to predict the population trends of pathogenic E. coli and S. enterica, two major causal agents of foodborne disease associated with produce, on leaves. Our model is based on weather parameters and rates of switching between the active (growing) and inactive (nongrowing) bacterial state resulting from prevailing environmental conditions on leaf surfaces. We demonstrate that the model has the ability to accurately predict dynamics of enteric pathogens on leaves and, notably, sizes of populations of pathogenic E. coli over time after inoculation onto the leaves of young lettuce plants in the field.

Survival and predictive modeling of Listeria monocytogenes under simulated human gastric conditions in the presence of bovine milk products.

Listeria monocytogenes is an opportunistic foodborne pathogen which has been implicated in many outbreaks of foodborne diseases. This study evaluated the effects of gastric acidity and gastric digestion time of adults, L. monocytogenes strain and food type on the survival of L. monocytogenes under simulated stomach conditions of adults in in vitro gastric models with dynamic pH changes occurring throughout the exposure. Individual strains as well as a cocktail of L. monocytogenes, inoculated at 8 log CFU/mL in filtered bovine milk products, 0 % milk, 2 % milk, 2 % chocolate milk and 3.25 % milk, were introduced to the gastric models for 2 h. The survival of L. monocytogenes depended on a combination of factors, including gastric acidity and gastric digestion time of adults, L. monocytogenes strain, food type and recovery method (P < 0.05). The survival rates of L. monocytogenes inoculated in 2 % milk after a 2-h exposure to simulated gastric fluids with pH values of 1.5, 2.0 and 3.0 were 0.003 to 0.040 %, 22.7 to 43.4 % and 16.6 to 27.2 %, respectively. Fluid milk containing a higher milk fat content (3.25 % vs 0 % milk) protected L. monocytogenes from being inactivated when they were exposed to the human stomach model with a gastric acidity of pH 2.0. Compared to 0 % and 3.25 % milk, L. monocytogenes survived the best in 2 % chocolate milk, which appears to be due to the presence of milk fat (2 %) and the additional nutrients that are present in chocolate milk. A predictive mathematical model was developed that captured the population of the strains of L. monocytogenes under the in vitro conditions. This study advances our understanding of the behaviour of L. monocytogenes under various human gastric conditions and provides key parameters that can affect the survival of L. monocytogenes in the stomachs of adults. The mathematical models developed in this study can be used as a supplementary tool to help predict the survival of L. monocytogenes under similar scenarios and for relevant risk-assessment studies.

Weather stressors correlate with Escherichia coli and Salmonella enterica persister formation rates in the phyllosphere: a mathematical modeling study.

Enteric pathogens can enter a persister state in which they survive exposure to antibiotics and physicochemical stresses. Subpopulations of such phenotypic dormant variants have been detected in vivo and in planta in the laboratory, but their formation in the natural environment remains largely unexplored. We applied a mathematical model predicting the switch rate to persister cell in the phyllosphere to identify weather-related stressors associated with E. coli and S. enterica persister formation on plants based on their population dynamics in published field studies from the USA and Spain. Model outputs accurately depicted the bi-phasic decay of bacterial population sizes measured in the lettuce and spinach phyllosphere in these studies. Predicted E. coli persister switch rate on leaves was positively and negatively correlated with solar radiation intensity and wind velocity, respectively. Likewise, predicted S. enterica persister switch rate correlated positively with solar radiation intensity; however, a negative correlation was observed with air temperature, relative humidity, and dew point, factors involved in water deposition onto the phylloplane. These findings suggest that specific environmental factors may enrich for dormant bacterial cells on plants. Our model quantifiably links persister cell subpopulations in the plant habitat with broader physical conditions, spanning processes at different granular scales.

Chlorine inactivation of Escherichia coli O157:H7 in fresh produce wash process: Effectiveness and modeling.

Inactivation rate constant or inactivation coefficient (specific lethality) quantifies the rate at which a chemical sanitizer inactivates a microorganism. This study presents a modified disinfection kinetics model to evaluate the potential effect of organic content on the chlorine inactivation coefficient of Escherichia coli O157:H7 in fresh produce wash processes. Results show a significant decrease in the bactericidal efficacy of free chlorine (FC) in the presence of organic load compared to its absence. While the chlorine inactivation coefficient of Escherichia coli O157:H7 is 70.39 ± 3.19 L/mg/min in the absence of organic content, it drops by 73% for a chemical oxygen demand (COD) level of 600-800 mg/L. Results also indicate that the initial chlorine concentration and bacterial load have no effect on the chlorine inactivation coefficient. A second-order chemical reaction model for FC decay, which utilizes a proportion of COD as an indicator of organic content in fresh produce wash was employed, yielding an apparent reaction rate of (9.45 ± 0.22) × 10-4 /µM/min. This model was validated by predicting FC concentration in multi-run continuous wash cycles with periodic replenishment of chlorine.

An agent-based simulator for the gastrointestinal pathway of Listeria monocytogenes.

We developed an agent-based gastric simulator for a human host to illustrate the within host survival mechanisms of Listeria monocytogenes. The simulator incorporates the gastric physiology and digestion processes that are critical for pathogen survival in the stomach. Mathematical formulations for the pH dynamics, stomach emptying time, and survival probability in the presence of gastric acid are integrated in the simulator to evaluate the portion of ingested bacteria that survives in the stomach and reaches the small intestine. The parameters are estimated using in vitro data relevant to the human stomach and L. monocytogenes. The simulator predicts that 5%-29% of ingested bacteria can survive a human stomach and reach the small intestine. In the absence of extensive scientific experiments, which are not feasible on the grounds of ethical and safety concerns, this simulator may provide a supplementary tool to evaluate pathogen survival and subsequent infection, especially with regards to the ingestion of small doses.

Effect of Weather on the Die-Off of Escherichia coli and Attenuated Salmonella enterica Serovar Typhimurium on Preharvest Leafy Greens following Irrigation with Contaminated Water.

The Food Safety Modernization Act (FSMA) includes a time-to-harvest interval following the application of noncompliant water to preharvest produce to allow for microbial die-off. However, additional scientific evidence is needed to support this rule. This study aimed to determine the impact of weather on the die-off rate of Escherichia coli and Salmonella on spinach and lettuce under field conditions. Standardized, replicated field trials were conducted in California, New York, and Spain over 2 years. Baby spinach and lettuce were grown and inoculated with an ∼104-CFU/ml cocktail of E. coli and attenuated Salmonella Leaf samples were collected at 7 time points (0 to 96 h) following inoculation; E. coli and Salmonella were enumerated. The associations of die-off with study design factors (location, produce type, and bacteria) and weather were assessed using log-linear and biphasic segmented log-linear regression. A segmented log-linear model best fit die-off on inoculated leaves in most cases, with a greater variation in the segment 1 die-off rate across trials (-0.46 [95% confidence interval {95% CI}, -0.52, -0.41] to -6.99 [95% CI, -7.38, -6.59] log10 die-off/day) than in the segment 2 die-off rate (0.28 [95% CI, -0.20, 0.77] to -1.00 [95% CI, -1.16, -0.85] log10 die-off/day). A lower relative humidity was associated with a faster segment 1 die-off and an earlier breakpoint (the time when segment 1 die-off rate switches to the segment 2 rate). Relative humidity was also found to be associated with whether die-off would comply with FSMA's specified die-off rate of -0.5 log10 die-off/day.IMPORTANCE The log-linear die-off rate proposed by FSMA is not always appropriate, as the die-off rates of foodborne bacterial pathogens and specified agricultural water quality indicator organisms appear to commonly follow a biphasic pattern with an initial rapid decline followed by a period of tailing. While we observed substantial variation in the net culturable population levels of Salmonella and E. coli at each time point, die-off rate and FSMA compliance (i.e., at least a 2 log10 die-off over 4 days) appear to be impacted by produce type, bacteria, and weather; die-off on lettuce tended to be faster than that on spinach, die-off of E. coli tended to be faster than that of attenuated Salmonella, and die-off tended to become faster as relative humidity decreased. Thus, the use of a single die-off rate for estimating time-to-harvest intervals across different weather conditions, produce types, and bacteria should be revised.

Formation of Escherichia coli O157:H7 Persister Cells in the Lettuce Phyllosphere and Application of Differential Equation Models To Predict Their Prevalence on Lettuce Plants in the Field.

Escherichia coli O157:H7 (EcO157) infections have been recurrently associated with produce. The physiological state of EcO157 cells surviving the many stresses encountered on plants is poorly understood. EcO157 populations on plants in the field generally follow a biphasic decay in which small subpopulations survive over longer periods of time. We hypothesized that these subpopulations include persister cells, known as cells in a transient dormant state that arise through phenotypic variation in a clonal population. Using three experimental regimes (with growing, stationary at carrying capacity, and decaying populations), we measured the persister cell fractions in culturable EcO157 populations after inoculation onto lettuce plants in the laboratory. The greatest average persister cell fractions on the leaves within each regime were 0.015, 0.095, and 0.221%, respectively. The declining EcO157 populations on plants incubated under dry conditions showed the largest increase in the persister fraction (46.9-fold). Differential equation models were built to describe the average temporal dynamics of EcO157 normal and persister cell populations after inoculation onto plants maintained under low relative humidity, resulting in switch rates from a normal cell to a persister cell of 7.7 × 10-6 to 2.8 × 10-5 h-1 Applying our model equations from the decay regime, we estimated model parameters for four published field trials of EcO157 survival on lettuce and obtained switch rates similar to those obtained in our study. Hence, our model has relevance to the survival of this human pathogen on lettuce plants in the field. Given the low metabolic state of persister cells, which may protect them from sanitization treatments, these cells are important to consider in the microbial decontamination of produce.IMPORTANCE Despite causing outbreaks of foodborne illness linked to lettuce consumption, E. coli O157:H7 (EcO157) declines rapidly when applied onto plants in the field, and few cells survive over prolonged periods of time. We hypothesized that these cells are persisters, which are in a dormant state and which arise naturally in bacterial populations. When lettuce plants were inoculated with EcO157 in the laboratory, the greatest persister fraction in the population was observed during population decline on dry leaf surfaces. Using mathematical modeling, we calculated the switch rate from an EcO157 normal to persister cell on dry lettuce plants based on our laboratory data. The model was applied to published studies in which lettuce was inoculated with EcO157 in the field, and switch rates similar to those obtained in our study were obtained. Our results contribute important new knowledge about the physiology of this virulent pathogen on plants to be considered to enhance produce safety.

Modeling of Free Chlorine Consumption and Escherichia coli O157:H7 Cross-Contamination During Fresh-Cut Produce Wash Cycles.

Controlling the free chlorine (FC) availability in wash water during sanitization of fresh produce enhances our ability to reduce microbial levels and prevent cross-contamination. However, maintaining an ideal concentration of FC that could prevent the risk of contamination within the wash system is still a technical challenge in the industry, indicating the need to better understand wash water chemistry dynamics. Using bench-scale experiments and modeling approaches, we developed a comprehensive mathematical model to predict the FC concentration during fresh-cut produce wash processes for different lettuce types (romaine, iceberg, green leaf, and red leaf), carrots, and green cabbage as well as Escherichia coli O157:H7 cross-contamination during fresh-cut iceberg lettuce washing. Fresh-cut produce exudates, as measured by chemical oxygen demand (COD) levels, appear to be the primary source of consumption of FC in wash water, with an apparent reaction rate ranging from 4.74 × 10 - 4 to 7.42 × 10 - 4 L/mg·min for all produce types tested, at stable pH levels (6.5 to 7.0) in the wash water. COD levels increased over time as more produce was washed and the lettuce type impacted the rate of increase in organic load. The model parameters from our experimental data were compared to those obtained from a pilot-plant scale study for lettuce, and similar reaction rate constant (5.38 × 10-4 L/mg·min) was noted, supporting our hypothesis that rise in COD is the main cause of consumption of FC levels in the wash water. We also identified that the bacterial transfer mechanism described by our model is robust relative to experimental scale and pathogen levels in the wash water. Finally, we proposed functions that quantify an upper bound on pathogen levels in the water and on cross-contaminated lettuce, indicating the maximum potential of water-mediated cross-contamination. Our model results could help indicate the limits of FC control to prevent cross-contamination during lettuce washing.

Advancing risk assessment: mechanistic dose-response modelling of Listeria monocytogenes infection in human populations.

The utility of characterizing the effects of strain variation and individual/subgroup susceptibility on dose-response outcomes has motivated the search for new approaches beyond the popular use of the exponential dose-response model for listeriosis. While descriptive models can account for such variation, they have limited power to extrapolate beyond the details of particular outbreaks. By contrast, this study exhibits dose-response relationships from a mechanistic basis, quantifying key biological factors involved in pathogen-host dynamics. An efficient computational algorithm and geometric interpretation of the infection pathway are developed to connect dose-response relationships with the underlying bistable dynamics of the model. Relying on in vitro experiments as well as outbreak data, we estimate plausible parameters for the human context. Despite the presence of uncertainty in such parameters, sensitivity analysis reveals that the host response is most influenced by the pathogen-immune system interaction. In particular, we show how variation in this interaction across a subgroup of the population dictates the shape of dose-response curves. Finally, in terms of future experimentation, our model results provide guidelines and highlight vital aspects of the interplay between immune cells and particular strains of Listeria monocytogenes that should be examined.

With-in host dynamics of L. monocytogenes and thresholds for distinct infection scenarios.

The case fatality and illness rates associated with L. monocytogenes continue to pose a serious public health burden despite the significant efforts and control protocol administered by private and public sectors. Due to the advance in surveillance and improvement in detection methodology, the knowledge of sources, transmission routes, growth potential in food process units and storage, effect of pH and temperature are well understood. However, the with-in host growth and transmission mechanisms of L. monocytogenes, particularly within the human host, remain unclear, largely due to the limited access to scientific experimentation on the human population. In order to provide insight towards the human immune response to the infection caused by L. monocytogenes, we develop a with-in host mathematical model. The model explains, in terms of biological parameters, the states of asymptomatic infection, mild infection and systemic infection leading to listeriosis. The activation and proliferation of T-cells are found to be critical for the susceptibility of the infection. Utilizing stability analysis and numerical simulation, the ranges of the critical parameters relative to infection states are established. Bifurcation analysis shows the impact of the differences of these parameters on the dynamics of the model. Finally, we present model applications in regards to predicting the risk potential of listeriosis relative to the susceptible human population.

Individual based modeling and analysis of pathogen levels in poultry chilling process.

Pathogen control during poultry processing critically depends on more enhanced insight into contamination dynamics. In this study we build an individual based model (IBM) of the chilling process. Quantifying the relationships between typical Canadian processing specifications, water chemistry dynamics and pathogen levels both in the chiller water and on individual carcasses, the IBM is shown to provide a useful tool for risk management as it can inform risk assessment models. We apply the IBM to Campylobacter spp. contamination on broiler carcasses, illustrating how free chlorine (FC) sanitization, organic load in the water, and pre-chill carcass pathogen levels affect pathogen levels of post-chill broilers. In particular, given a uniform distribution of Campylobacter levels on incoming poultry we quantify the efficacy of FC control in not only reducing pathogen levels on average, but also the variation of pathogen levels on poultry exiting the chill tank. Furthermore, we demonstrate that the absence/presence of FC input dramatically influences when, during a continuous chilling operation, cross-contamination will be more likely.

Unraveling the dose-response puzzle of L. monocytogenes: A mechanistic approach.

Food-borne disease outbreaks caused by Listeria monocytogenes continue to impose heavy burdens on public health in North America and globally. To explore the threat L. monocytogenes presents to the elderly, pregnant woman and immuno-compromised individuals, many studies have focused on in-host infection mechanisms and risk evaluation in terms of dose-response outcomes. However, the connection of these two foci has received little attention, leaving risk prediction with an insufficient mechanistic basis. Consequently, there is a critical need to quantifiably link in-host infection pathways with the dose-response paradigm. To better understand these relationships, we propose a new mathematical model to describe the gastro-intestinal pathway of L. monocytogenes within the host. The model dynamics are shown to be sensitive to inoculation doses and exhibit bi-stability phenomena. Applying the model to guinea pigs, we show how it provides useful tools to identify key parameters and to inform critical values of these parameters that are pivotal in risk evaluation. Our preliminary analysis shows that the effect of gastro-environmental stress, the role of commensal microbiota and immune cells are critical for successful infection of L. monocytogenes and for dictating the shape of the dose-response curves.

A mathematical model for pathogen cross-contamination dynamics during produce wash.

One of the main challenges for the fresh-food produce industry is to ensure that the produce is free from harmful pathogens. A potential area of risk is due to cross-contamination in a sanitizing chlorine wash-cycle, where the same water is used to wash contaminated as well as non-contaminated produce. However, this is also an area where effective intervention strategies are possible, provided we have a good understanding of the mechanism of cross-contamination. Based on recent experimental work by Luo, Y. et al. A pilot plant scale evaluation of a new process aid for enhancing chlorine efficacy against pathogen survival and cross-contamination during produce wash, International Journal of Food Microbiology, 158 (2012), 133-139, we have built mathematical models that allow us to quantify the amount of cross-contamination of Escherichia coli O157:H7 from spinach to lettuce, and assessed the efficacy of the associated wash-cycle protocols.

Enhanced surveillance on food-borne disease outbreaks: dynamics of cross-contamination in biocidal wash procedure.

Understanding the geographic and temporal spread of food-borne diseases associated with fresh produce is crucial for informing adequate surveillance and control. As a first step towards this goal, we develop and analyze a novel three stage model at the processing/sanitization juncture in the fresh produce supply chain. The key feature of our model is its ability to describe the dynamics of cross-contamination during commercial wash procedures. In general, we quantify the degree of cross-contamination in terms of model parameters. Applying these results in the case of Escherichia coli O157:H7 contamination of fresh-cut romaine lettuce, we identify the mean wash time and free chlorine concentration as critical parameters. In addition to showing how these parameters affect contamination levels, we recommend that in order to prevent potential source misidentification, at least 2.2 mg/L of free chlorine should be used during a wash lasting at least 30s.

Evolutionary convergence to ideal free dispersal strategies and coexistence.

We study a two species competition model in which the species have the same population dynamics but different dispersal strategies and show how these dispersal strategies evolve. We introduce a general dispersal strategy which can result in the ideal free distributions of both competing species at equilibrium and generalize the result of Averill et al. (2011). We further investigate the convergent stability of this ideal free dispersal strategy by varying random dispersal rates, advection rates, or both of these two parameters simultaneously. For monotone resource functions, our analysis reveals that among two similar dispersal strategies, selection generally prefers the strategy which is closer to the ideal free dispersal strategy. For nonmonotone resource functions, our findings suggest that there may exist some dispersal strategies which are not ideal free, but could be locally evolutionarily stable and/or convergent stable, and allow for the coexistence of more than one species.