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

Microbiological hazards associated with the use of water in the post-harvest handling and processing operations of fresh and frozen fruits, vegetables and herbs (ffFVHs). Part 1 (outbreak data analysis, literature review and stakeholder questionnaire)

The contamination of water used in post-harvest handling and processing operations of fresh and frozen fruit, vegetables and herbs (ffFVHs) is a global concern. The most relevant microbial hazards associated with this water are: Listeria monocytogenes, Salmonella spp., human pathogenic Escherichia coli and enteric viruses, which have been linked to multiple outbreaks associated with ffFVHs in the European Union (EU). Contamination (i.e. the accumulation of microbiological hazards) of the process water during post-harvest handling and processing operations is affected by several factors including: the type and contamination of the FVHs being processed, duration of the operation and transfer of microorganisms from the product to the water and vice versa, etc. For food business operators (FBOp), it is important to maintain the microbiological quality of the process water to assure the safety of ffFVHs. Good manufacturing practices (GMP) and good hygienic practices (GHP) related to a water management plan and the implementation of a water management system are critical to maintain the microbiological quality of the process water. Identified hygienic practices include technical maintenance of infrastructure, training of staff and cooling of post-harvest process water. Intervention strategies (e.g. use of water disinfection treatments and water replenishment) have been suggested to maintain the microbiological quality of process water. Chlorine-based disinfectants and peroxyacetic acid have been reported as common water disinfection treatments. However, given current practices in the EU, evidence of their efficacy under industrial conditions is only available for chlorine-based disinfectants. The use of water disinfection treatments must be undertaken following an appropriate water management strategy including validation, operational monitoring and verification. During operational monitoring, real-time information on process parameters related to the process and product, as well as the water and water disinfection treatment(s) are necessary. More specific guidance for FBOp on the validation, operational monitoring and verification is needed.

Quantitative risk assessment-epidemic curve prediction model for leafy green outbreak investigation

The objective of this study was to leverage quantitative risk assessment to investigate possible root cause(s) of foodborne illness outbreaks related to Shiga toxin-producing Escherichia coli O157:H7 (STEC O157) infections in leafy greens in the United States. To this end, we developed the FDA leafy green quantitative risk assessment epidemic curve prediction model (FDA-LG QRA-EC) that simulated the lettuce supply chain. The model was used to predict the number of reported illnesses and the epidemic curve associated with lettuce contaminated with STEC O157 for a wide range of scenarios representing various contamination conditions and facility processing/sanitation practices. Model predictions were generated for fresh-cut and whole lettuce, quantifying the differing impacts of facility processing and home preparation on predicted illnesses. Our model revealed that the timespan (i.e., number of days with at least one reported illness) and the peak (i.e., day with the most predicted number of reported illnesses) of the epidemic curve of a STEC O157-lettuce outbreak were not strongly influenced by facility processing/sanitation practices and were indications of contamination pattern among incoming lettuce batches received by the facility or distribution center. Through comparisons with observed number of illnesses from recent STEC O157-lettuce outbreaks, the model identified contamination conditions on incoming lettuce heads that could result in an outbreak of similar size, which can be used to narrow down potential root cause hypotheses.

Bio-based antimicrobial compositions and sensing technologies to improve food safety

Microbial contamination of food products is a significant challenge that impacts food safety and quality. This review focuses on bio-based technologies for enhancing the decontamination of raw foods during postharvest processing, preventing cross-contamination, and rapidly detecting microbial risks. The bio-based antimicrobial compositions include bio-based antimicrobial delivery systems and coatings. The antimicrobial delivery systems are developed using cell-based carriers, microbubbles, and lipid-based colloidal particles. The antimicrobial coatings are engineered by incorporating biopolymers with conventional antimicrobials or cell-based antimicrobial carriers. The bio-based sensing approaches focus on replacing antibodies with more stable and cost-effective bio-receptors, including antimicrobial peptides, bacteriophages, DNAzymes, and engineered liposomes. Together, these approaches can reduce microbial contamination risks and enhance the in-situ detection of microbes.

Evaluation of Potential Impacts of Free Chlorine during Washing of Fresh-Cut Leafy Greens on Escherichia coli O157:H7 Cross-Contamination and Risk of Illness

Addition of chlorine-based antimicrobial substances to fresh-cut leafy green wash water is done to minimize microbial cross-contamination during processing. We developed the FDA Leafy Green Risk Assessment Model (FDA-LGRAM) to quantify the impact of free chlorine concentration in wash water during fresh-cut lettuce processing on the extent of water-mediated cross-contamination between shredded lettuce and the associated risk of illness due to exposure to Escherichia coli O157:H7. At different contamination prevalence and levels of E. coli O157:H7 on incoming lettuce heads, the model compared the predicted prevalence of contaminated fresh-cut lettuce packages and the risk of illness per serving between: (1) a scenario where fresh-cut lettuce was packaged without washing; and (2) scenarios involving washing fresh-cut lettuce with different levels of free chlorine (0 ppm, 5 ppm, 10 ppm, 15 ppm, and 20 ppm) prior to packaging. Our results indicate that the free chlorine level in wash water has a substantial impact on the predicted prevalence of contaminated fresh-cut lettuce packages and the risk of illness associated with E. coli O157:H7 in fresh-cut lettuce. Results showed that the required level of free chlorine that can minimize water-mediated cross-contamination and reduce the corresponding risk of illness depended on contamination prevalence and levels of E. coli O157:H7 on incoming lettuce heads. Our model also indicated that the pathogen inactivation rate in wash water via free chlorine was a key model parameter that had a significant impact on the extent of cross-contamination during washing and the predicted associated risk of illness.

Modeling bioaffinity-based targeted delivery of antimicrobials to Escherichia coli biofilms using yeast microparticles. Part I: Model development and numerical simulation

Biofilms are potential reservoirs for pathogenic microbes leading to a significant challenge for food safety, ecosystems, and human health. Various micro-and nanoparticles have been experimentally evaluated to improve biofilm inactivation by targeted delivery of antimicrobials. However, the role of transport processes and reaction kinetics of these delivery systems are not well understood. In this study, a mechanistic modeling approach was developed to understand the targeted delivery of chlorine to an Escherichia coli biofilm using a novel bioaffinity-based yeast microparticle. Biofilm inactivation by this delivery system was numerically simulated as a combination of reaction kinetics and transport phenomena. Simulation results demonstrate that the targeted delivery system achieved 7 log reduction within 16.2 min, while the equivalent level of conventional free chlorine achieved only 3.6 log reduction for the same treatment time. These numerical results matched the experimental observations in our previous study. This study illustrates the potential of a mechanistic modeling approach to improve fundamental understanding and guide the design of targeted inactivation of biofilms using biobased particles.

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.

Total amino acids concentration as a reliable predictor of free chlorine levels in dynamic fresh produce washing process

We establish the total amino acids (AA) concentration in wash water as an alternative indicator of free chlorine (FC) levels, and develop a model to predict FC concentration based on modeling the reaction kinetics of chlorine and amino acids. Using single wash of iceberg lettuce, green cabbage, and carrots, we report the first in situ apparent reaction rate β between FC and amino acids in the range of 15.3 - 16.6 M-1 s-1 and an amplification factor γ in the range of 11.52-11.94 for these produce. We also report strong linear correlations between AA levels and produce-to-water ratio (R2 = 0.87), and between chemical oxygen demand (COD) and AA concentrations (R2 = 0.87). The values of the parameters γ and β of the model were validated in continuous wash experiments of chopped iceberg lettuce, and predicted the FC (R2 = 0.96) and AA (R2 = 0.92) levels very well.

Microfluidic droplet application for bacterial surveillance in fresh-cut produce wash waters

Foodborne contamination and associated illness in the United States is responsible for an estimated 48 million cases per year. Increased food demand, global commerce of perishable foods, and the growing threat of antibiotic resistance are driving factors elevating concern for food safety. Foodborne illness is often associated with fresh-cut, ready-to-eat produce commodities due to the perishable nature of the product and relatively minimal processing from farm to the consumer. The research presented here optimizes and evaluates the utility of microfluidic droplets, also termed ultra-miniaturized bioreactors, for rapid detection of viable Salmonella enterica ser. Typhimurium in a shredded lettuce wash water acquired from a major Mid-Atlantic produce processing facility (denoted as Producer) in the U.S. Using a fluorescently-labeled anti-S. Typhimurium antibody and relative fluorescence intensities, paired with in-droplet incubation, S. Typhimurium was detected and identified with 100% specificity in less than 5 h. In initial optimization experiments using S. Typhimurium-spiked sterile water, the relative fluorescence intensity of S. Typhimurium was approximately two times that of the observed relative intensities of five non-S. Typhimurium negative controls at 4-h incubation in droplets containing Rappaport-Vasiliadis (RV) broth at 37°C: relative fluorescence intensity for S. Typhimurium = 2.36 (95% CI: 2.15-2.58), Enterobacter aerogens 1.12 (95% CI: 1.09-1.16), Escherichia coli 700609 = 1.13 (95% CI: 1.09-1.17), E. coli 13706 1.13 (95% CI: 1.07-1.19), E. coli 700891 1.05 (95% CI: 1.03-1.07) and Citrobacter freundii 1.04 (95% CI: 1.03-1.05). S. Typhimurium- and E. aerogens-spiked shredded lettuce wash waters acquired from the Producer were then incubated 4 h in-droplet at 37°C with RV broth. The observed relative fluorescence of S. Typhimurium was significantly higher than that of E. aerogens, 1.56 (95% CI: 1.42-1.71) and 1.10 (95% CI: 1.08-1.12), respectively. While further optimization focusing on compatible concentration methodologies for highly-dilute produce water samples is needed, this application of droplet microfluidics shows great promise in dramatically shortening the time necessary-from days to hours-to confirm viable bacterial contamination in ready-to-eat produce wash waters used throughout the domestic and international food industry.

Two Generally Recognized as Safe Surfactants plus Acidulants Inactivate Salmonella, Escherichia coli O157:H7, and Listeria monocytogenes in Suspension or on Dip-Inoculated Grape Tomatoes

ABSTRACT

Contamination of fresh produce with the foodborne pathogens Salmonella enterica, Listeria monocytogenes, and Escherichia coli O157:H7 continues to be problematic, resulting in outbreaks of foodborne illness and costly corporate recalls. Various individual concentrations of citric or lactic acids (0.35 to 0.61%) or isopropyl citrate (0.16 to 0.54%) combined with two generally recognized as safe surfactants, 0.025% sodium-2-ethyl-hexyl sulfate and 0.025% sodium dodecylbenzene-sulfonate, were tested against these three pathogens in suspension and when inoculated and dried on the surface of grape tomatoes. The efficacy of sodium hypochlorite (NaClO; at 46 ppm) was also evaluated under dirty and clean conditions in suspension after addition of 0.3 or 0.03% bovine serum albumin, respectively, as an organic load. NaClO (46 ppm) inactivated the three pathogens in suspension by <0.76 log CFU/mL after 5 min in the presence of 0.3% bovine serum albumin, whereas 9 and 15 ppm of free chlorine inactivated the pathogens by 0.64 and 2.77 log CFU/mL, respectively, after 5 min under clean conditions. Isopropyl citrate (0.16% acidulant) plus 0.05% total concentration of the two surfactants inactivated the pathogens in suspension by up to 7.0 log CFU/mL within 2 min. When applied to grape tomatoes for 2 min, 0.54% isopropyl citrate plus 0.025% concentrations of each of the two surfactants reduced Salmonella, E. coli O157:H7, and L. monocytogenes by as much as ca. 5.47, 4.89, and 4.19 log CFU/g, respectively. These reductions were significantly greater than those achieved with 49 ppm of free chlorine. Citric acid and lactic acid plus surfactant washes achieved greater inactivation than water-only washes, reducing Salmonella, E. coli O157:H7, and L. monocytogenes on tomatoes by up to 4.90, 4.37, and 3.98 log CFU/g, respectively. These results suggest that these combinations of acidulants and surfactants may be an effective tool for preventing cross-contamination during the washing of grape tomatoes, for reducing pathogens on the fruit itself, and as an alternative to chlorine for washing fresh produce.

HIGHLIGHTS

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.

A Mathematical Model for Pathogen Cross-Contamination Dynamics during the Postharvest Processing of Leafy Greens

We developed a probabilistic mathematical model for the postharvest processing of leafy greens focusing on Escherichia coli O157:H7 contamination of fresh-cut romaine lettuce as the case study. Our model can (i) support the investigation of cross-contamination scenarios, and (ii) evaluate and compare different risk mitigation options. We used an agent-based modeling framework to predict the pathogen prevalence and levels in bags of fresh-cut lettuce and quantify spread of E. coli O157:H7 from contaminated lettuce to surface areas of processing equipment. Using an unbalanced factorial design, we were able to propagate combinations of random values assigned to model inputs through different processing steps and ranked statistically significant inputs with respect to their impacts on selected model outputs. Results indicated that whether contamination originated on incoming lettuce heads or on the surface areas of processing equipment, pathogen prevalence among bags of fresh-cut lettuce and batches was most significantly impacted by the level of free chlorine in the flume tank and frequency of replacing the wash water inside the tank. Pathogen levels in bags of fresh-cut lettuce were most significantly influenced by the initial levels of contamination on incoming lettuce heads or surface areas of processing equipment. The influence of surface contamination on pathogen prevalence or levels in fresh-cut bags depended on the location of that surface relative to the flume tank. This study demonstrates that developing a flexible yet mathematically rigorous modeling tool, a "virtual laboratory," can provide valuable insights into the effectiveness of individual and combined risk mitigation options.