A longitudinal study on the bacterial quality of baby spinach cultivated in Arizona and California.

In the U.S., baby spinach is mostly produced in Arizona (AZ) and California (CA). Characterizing the impact of growing region on the bacterial quality of baby spinach can inform quality management practices in industry. Between December 2021 and December 2022, baby spinach was sampled after harvest and packaging for microbiological testing, including shelf-life testing of packaged samples that were stored at 4°C. Samples were tested to (i) determine bacterial concentration, and (ii) obtain and identify bacterial isolates. Packaged samples from the Salinas, CA, area (n = 13), compared to those from the Yuma, AZ, area (n = 9), had a significantly higher bacterial concentration, on average, by 0.78 log10 CFU/g (P < 0.01, based on aerobic, mesophilic plate count data) or 0.67 log10 CFU/g (P < 0.01, based on psychrotolerant plate count data); the bacterial concentrations of harvest samples from the Yuma and Salinas areas were not significantly different. Our data also support that an increase in preharvest temperature is significantly associated with an increase in the bacterial concentration on harvested and packaged spinach. A Fisher's exact test and linear discriminant analysis (effect size), respectively, demonstrated that (i) the genera of 2,186 bacterial isolates were associated (P < 0.01) with growing region and (ii) Pseudomonas spp. and Exiguobacterium spp. were enriched in spinach from the Yuma and Salinas areas, respectively. Our findings provide preliminary evidence that growing region and preharvest temperature may impact the bacterial quality of spinach and thus could inform more targeted strategies to manage produce quality. IMPORTANCE: In the U.S., most spinach is produced in Arizona (AZ) and California (CA) seasonally; typically, spinach is cultivated in the Yuma, AZ, area during the winter and in the Salinas, CA, area during the summer. As the bacterial quality of baby spinach can influence consumer acceptance of the product, it is important to assess whether the bacterial quality of baby spinach can vary between spinach-growing regions. The findings of this study provide insights that could be used to support region-specific quality management strategies for baby spinach. Our results also highlight the value of further evaluating the impact of growing region and preharvest temperature on the bacterial quality of different produce commodities.

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.

Responsible antibiotic use labeling and consumers' willingness to buy and pay for fluid milk.

Concerns about antibiotic resistant infections in the United States have called for reduction of antibiotic use in livestock, including dairy cattle. Although effective in curbing antibiotic use, universal organic dairy farming would be impractical and unattainable due to its high land and premium demands. The US Department of Agriculture's organic certification, which completely eliminates antibiotic use in milk production, also raises animal welfare concerns, as it could discourage the use of antibiotics even to treat indicated diseases. Therefore, a proposed alternative for US consumers is a label indicating the responsible antibiotic use (RAU) - not complete elimination - that would minimize antibiotics more than conventional (unlabeled) milk and maximize animal welfare more than organic milk. Our goal was to determine consumers' (1) self-reported preference and (2) willingness to pay for this hypothetical RAU label of milk relative to existing substitutes in organic and unlabeled fluid milk. We conducted (1) a nationally representative survey of US adults and (2) a randomized non-hypothetical experimental Becker-Degroot-Marschak auction with real money and real milk. Although almost half of the survey participants (48.5%) responded that they would buy a RAU-labeled milk, consumers in the experimental auction refused to pay a significant premium for the milk compared with unlabeled milk (mean willingness to pay (95% confidence interval) per half-gallon: $1.92 ($1.65-$2.19) for RAU-labeled milk versus $1.86 ($1.58-$2.13) for unlabeled milk). These results suggest that consumers' survey-identified preferences for RAU-labeled milk could reflect either social desirability bias or a genuine preference for which, however, consumers simply will not pay a significant premium. The study provides preliminary data for future exploration of marketability of the proposed RAU label in the United States and demonstrates the benefits of using complementary survey and experimental auction approaches to understand the potential market for a new dairy product.

Population dynamics of Listeria spp., Salmonella spp., and Escherichia coli on fresh produce: A scoping review.

Collation of the current scope of literature related to population dynamics (i.e., growth, die-off, survival) of foodborne pathogens on fresh produce can aid in informing future research directions and help stakeholders identify relevant research literature. A scoping review was conducted to gather and synthesize literature that investigates population dynamics of pathogenic and non-pathogenic Listeria spp., Salmonella spp., and Escherichia coli on whole unprocessed fresh produce (defined as produce not having undergone chopping, cutting, homogenization, irradiation, or pasteurization). Literature sources were identified using an exhaustive search of research and industry reports published prior to September 23, 2021, followed by screening for relevance based on strict, a priori eligibility criteria. A total of 277 studies that met all eligibility criteria were subjected to an in-depth qualitative review of various factors (e.g., produce commodities, study settings, inoculation methodologies) that affect population dynamics. Included studies represent investigations of population dynamics on produce before (i.e., pre-harvest; n = 143) and after (i.e., post-harvest; n = 144) harvest. Several knowledge gaps were identified, including the limited representation of (i) pre-harvest studies that investigated population dynamics of Listeria spp. on produce (n = 13, 9% of pre-harvest studies), (ii) pre-harvest studies that were carried out on non-sprouts produce types grown using hydroponic cultivation practices (n = 7, 5% of pre-harvest studies), and (iii) post-harvest studies that reported the relative humidity conditions under which experiments were carried out (n = 56, 39% of post-harvest studies). These and other knowledge gaps summarized in this scoping review represent areas of research that can be investigated in future studies.

Comparison of different biomass methodologies to adjust sales data on veterinary antimicrobials in the USA.

OBJECTIVES: The United States (US) FDA, European Surveillance of Veterinary Antimicrobial Consumption (ESVAC), Public Health Agency of Canada (PHAC) and World Organisation for Animal Health (OIE) established methodologies that characterize antimicrobial sales for use in food animals by adjusting the sales by animal biomass. Our aim was to review and compare these methodologies on US-specific data. METHODS: Annual antimicrobial sales for cattle, swine, chickens and turkeys in the USA between 2016 and 2018 were adjusted by the FDA, ESVAC, PHAC and OIE methodologies. To better understand the advantages and disadvantages of the four methodologies, their biomass denominators were compared regarding the level of detail accounted for in the estimated US livestock biomass, their ability to observe temporal trends in animal biomass within a country and practicality in biomass estimation for comparing antimicrobial sales across countries. RESULTS: The four methodologies resulted in substantially different estimates of biomass-adjusted antimicrobial sales for use in US food animals. The 2018 estimates were the highest with the ESVAC methodology (314.7 mg of active antimicrobial ingredient/kg of animal biomass), followed by PHAC (191.5 mg/kg), FDA (127.6 mg/kg) and OIE (111.5 mg/kg). The animal weight parameters used in each methodology had the most impact on the biomass-adjusted sales estimates. CONCLUSIONS: In regard to the estimation of the animal biomass, no methodology was found to be perfect; however, the FDA methodology had the best resolution in characterizing the US livestock biomass while the OIE methodology was best for biomass estimation for global monitoring of antimicrobial sales for use in food animals.

A perspective on data sharing in digital food safety systems.

In this age of data, digital tools are widely promoted as having tremendous potential for enhancing food safety. However, the potential of these digital tools depends on the availability and quality of data, and a number of obstacles need to be overcome to achieve the goal of digitally enabled "smarter food safety" approaches. One key obstacle is that participants in the food system and in food safety often lack the willingness to share data, due to fears of data abuse, bad publicity, liability, and the need to keep certain data (e.g., human illness data) confidential. As these multifaceted concerns lead to tension between data utility and privacy, the solutions to these challenges need to be multifaceted. This review outlines the data needs in digital food safety systems, exemplified in different data categories and model types, and key concerns associated with sharing of food safety data, including confidentiality and privacy of shared data. To address the data privacy issue a combination of innovative strategies to protect privacy as well as legal protection against data abuse need to be pursued. Existing solutions for maximizing data utility, while not compromising data privacy, are discussed, most notably differential privacy and federated learning.

In Silico Models for Design and Optimization of Science-Based Listeria Environmental Monitoring Programs in Fresh-Cut Produce Facilities.

Food facilities need time- and cost-saving methods during the development and optimization of environmental monitoring for pathogens and their surrogates. Rapid virtual experimentation through in silico modeling can alleviate the need for extensive real-world, trial-and-error style program design. Two agent-based models of fresh-cut produce facilities were developed as a way to simulate the dynamics of Listeria in the built environment by modeling the different surfaces of equipment and employees in a facility as agents. Five sampling schemes at three time points were evaluated in silico on their ability to locate the presence of Listeria contamination in a facility with sample sites for each scheme (i.e., scenario, as modeled using scenario analysis) based on the following: the facilities' current environmental monitoring program (scenario 1), Food and Drug Administration recommendations (scenario 2), random selection (scenario 3), sites exclusively from zone 3 (i.e., sites in the production room but not directly adjacent to food contact surfaces) (scenario 4), or model prediction of elevated risk of contamination (scenario 5). Variation was observed between the scenarios on how well the Listeria prevalence of the virtually collected samples reflected the true prevalence of contaminated agents in the modeled operation. The zone 3 only (scenario 4) and model-based (scenario 5) sampling scenarios consistently overestimated true prevalence across time, suggesting that those scenarios could provide a more sensitive approach for determining if Listeria is present in the operation. The random sampling scenario (scenario 3) may be more useful for operations looking for a scheme that is most likely to reflect the true prevalence. Overall, the developed models allow for rapid virtual experimentation and evaluation of sampling schemes specific to unique fresh-cut produce facilities. IMPORTANCE Programs such as environmental monitoring are used to determine the state of a given food facility with regard to the presence of environmental pathogens, such as Listeria monocytogenes, that could potentially cross-contaminate food product. However, the design of environmental monitoring programs is complex, and there are infinite ways to conduct the sampling that is required for these programs. Experimentally evaluating sampling schemes in a food facility is time-consuming, costly, and nearly impossible. Therefore, the food industry needs science-based tools to aid in developing and refining sampling plans that reduce the risk of harboring contamination. Two agent-based models of two fresh-cut produce facilities reported here demonstrate a novel way to evaluate how different sampling schemes can be rapidly evaluated across multiple time points as a way to understand how sampling can be optimized in an effort to locate the presence of Listeria in a food facility.

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.

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.

Cul o 2 specific IgG3/5 antibodies predicted Culicoides hypersensitivity in a group imported Icelandic horses.

BACKGROUND: Culicoides hypersensitivity (CH) is induced in horses by salivary allergens of Culicoides midges. In Iceland, the causal Culicoides species for CH are not present. Previous epidemiological data indicated that Icelandic horses are more susceptible to CH when they are exported from Iceland and first exposed to Culicoides at adult age. Horses born in countries where Culicoides is endemic, develop the disease less frequently. Here, we established a longitudinal allergy model to identify predictive and diagnostic serological biomarkers of CH. RESULTS: Sixteen adult Icelandic horses from Iceland were imported to the Northeastern United States (US) during the winter and were kept in the same environment with natural Culicoides exposure for the next two years. None of the horses showed clinical allergy during the first summer of Culicoides exposure. In the second summer, 9/16 horses (56%) developed CH. Allergen specific IgE and IgG isotype responses in serum samples were analysed using nine potential Culicoides allergens in a fluorescent bead-based multiplex assay. During the first summer of Culicoides exposure, while all horses were still clinically healthy, Cul o 2 specific IgG3/5 antibodies were higher in horses that developed the allergic disease in the second summer compared to those that did not become allergic (p = 0.043). The difference in Cul o 2 specific IgG3/5 antibodies between the two groups continued to be detectable through fall (p = 0.035) and winter of the first year. During the second summer, clinical signs first appeared and Cul o 3 specific IgG3/5 isotypes were elevated in allergic horses (p = 0.041). Cul o 2 specific IgG5 (p = 0.035), and Cul o 3 specific IgG3/5 (p = 0.043) were increased in late fall of year two when clinical signs started to improve again. CONCLUSIONS: Our results identified IgG5 and IgG3/5 antibodies against Cul o 2 and Cul o 3, respectively, as markers for CH during and shortly after the allergy season in the Northeastern US. In addition, Cul o 2 specific IgG3/5 antibodies may be valuable as a predictive biomarker of CH in horses that have been exposed to Culicoides but did not yet develop clinical signs.

Design Elements of Listeria Environmental Monitoring Programs in Food Processing Facilities: A Scoping Review of Research and Guidance Materials.

Occurrence of Listeria monocytogenes (Lm), the causative agent of listeriosis, in food processing facilities presents considerable challenges to food producers and food safety authorities. Design of an effective, risk-based environmental monitoring (EM) program is essential for finding and eliminating Lm from the processing environment to prevent product contamination. A scoping review was conducted to collate and synthesize available research and guidance materials on Listeria EM in food processing facilities. An exhaustive search was performed to identify all available research, industry and regulatory documents, and search results were screened for relevance based on eligibility criteria. After screening, 198 references were subjected to an in-depth review and categorized according to objectives for conducting Listeria sampling in food processing facilities and food sector. Mapping of the literature revealed research and guidance gaps by food sector, as fresh produce was the focus in only 10 references, compared to 72 on meat, 52 on fish and seafood, and 50 on dairy. Review of reported practices and guidance highlighted key design elements of EM, including the number, location, timing and frequency of sampling, as well as methods of detection and confirmation, and record-keeping. While utilization of molecular subtyping methods is a trend that will continue to advance understanding of Listeria contamination risks, improved study design and reporting standards by researchers will be essential to assist the food industry optimize their EM design and decision-making. The comprehensive collection of documents identified and synthesized in this review aids continued efforts to minimize the risk of Lm contaminated foods.

Multifactorial effects of ambient temperature, precipitation, farm management, and environmental factors determine the level of generic Escherichia coli contamination on preharvested spinach.

A repeated cross-sectional study was conducted to identify farm management, environment, weather, and landscape factors that predict the count of generic Escherichia coli on spinach at the preharvest level. E. coli was enumerated for 955 spinach samples collected on 12 farms in Texas and Colorado between 2010 and 2012. Farm management and environmental characteristics were surveyed using a questionnaire. Weather and landscape data were obtained from National Resources Information databases. A two-part mixed-effect negative binomial hurdle model, consisting of a logistic and zero-truncated negative binomial part with farm and date as random effects, was used to identify factors affecting E. coli counts on spinach. Results indicated that the odds of a contamination event (non-zero versus zero counts) vary by state (odds ratio [OR] = 108.1). Odds of contamination decreased with implementation of hygiene practices (OR = 0.06) and increased with an increasing average precipitation amount (mm) in the past 29 days (OR = 3.5) and the application of manure (OR = 52.2). On contaminated spinach, E. coli counts increased with the average precipitation amount over the past 29 days. The relationship between E. coli count and the average maximum daily temperature over the 9 days prior to sampling followed a quadratic function with the highest bacterial count at around 24°C. These findings indicate that the odds of a contamination event in spinach are determined by farm management, environment, and weather factors. However, once the contamination event has occurred, the count of E. coli on spinach is determined by weather only.

Exploratory spatial analysis of Lyme disease in Texas -what can we learn from the reported cases?

BACKGROUND: Lyme disease (LD) is a tick-borne zoonotic illness caused by the bacterium Borrelia burgdorferi. Texas is considered a non-endemic state for LD and the spatial distribution of the state's reported LD cases is unknown. METHODS: We analyzed human LD cases reported to the Texas Department of State Health Services (TX-DSHS) between 2000 and 2011 using exploratory spatial analysis with the objective to investigate the spatial patterns of LD in Texas. Case data were aggregated at the county level, and census data were used as the population at risk. Empirical Bayesian smoothing was performed to stabilize the variance. Global Moran's I was calculated to assess the presence and type of spatial autocorrelation. Local Indicator of Spatial Association (LISA) was used to determine the location of spatial clusters and outliers. RESULTS AND DISCUSSION: There was significant positive spatial autocorrelation of LD incidence in Texas with Moran's I of 0.41 (p = 0.001). LISA revealed significant variation in the spatial distribution of human LD in Texas. First, we identified a high-risk cluster in Central Texas, in a region that is thought to be beyond the geographical range of the main vector, Ixodes scapularis. Second, the eastern part of Texas, which is thought to provide the most suitable habitat for I. scapularis, did not appear to be a high-risk area. Third, LD cases were reported from several counties in western Texas, a region considered unsuitable for the survival of Ixodes ticks. CONCLUSIONS: These results emphasize the need for follow-up investigations to determine whether the identified spatial pattern is due to: clustering of misdiagnosed cases, clustering of patients with an out-of state travel history, or presence of a clustered unknown enzootic cycle of B. burgdorferi in Texas. This would enable an improved surveillance and reporting of LD in Texas.

Phylogenetic characterization of Escherichia coli O157 : H7 based on IS629 distribution and Shiga toxin genotype.

Shiga toxin (stx)-producing Escherichia coli O157 : H7 is a prominent food-borne pathogen. Symptoms in human infections range from asymptomatic to haemorrhagic colitis and haemolytic uraemic syndrome, and there is a need for methods that yield information that can be used to better predict clinical and epidemiological outcomes. IS629 is an insertion sequence notable for its prevalence and variable distribution in the chromosome of E. coli O157 : H7, which has been exploited for subtyping and strain characterization. In particular, IS629 distribution is closely aligned with the major phylogenetic lineages that are known to be distinctive in their genome structure and virulence potential. In the present study, a comprehensive subtyping method in which IS629-typing was combined with stx genotyping was developed using a conventional PCR approach. This method consisted of a set of 32 markers based on the unique distribution of IS629 in the three major phylogenetic lineages of E. coli O157 : H7 and six additional markers to determine the stx genotype, a key virulence signature associated with each lineage. The analysis of IS629 loci variation with the 32 markers allowed us to determine the IS629 distribution profile (IDP), phylogenetic lineage and genetic relatedness of the 31 E. coli O157 : H7 strains examined. An association between IDP typing and stx genotype was observed. The use of both IDP and the stx genotype for strain characterization provided confirmative and complementary data in support of lineage placement of closely related strains. In addition, IS629/stx profiles were in agreement with strain segregation based on LSPA-6 (lineage-specific polymorphism assay) and PFGE subtyping, demonstrating its potential as a subtyping and strain tracking method.

Farm management, environment, and weather factors jointly affect the probability of spinach contamination by generic Escherichia coli at the preharvest stage.

The National Resources Information (NRI) databases provide underutilized information on the local farm conditions that may predict microbial contamination of leafy greens at preharvest. Our objective was to identify NRI weather and landscape factors affecting spinach contamination with generic Escherichia coli individually and jointly with farm management and environmental factors. For each of the 955 georeferenced spinach samples (including 63 positive samples) collected between 2010 and 2012 on 12 farms in Colorado and Texas, we extracted variables describing the local weather (ambient temperature, precipitation, and wind speed) and landscape (soil characteristics and proximity to roads and water bodies) from NRI databases. Variables describing farm management and environment were obtained from a survey of the enrolled farms. The variables were evaluated using a mixed-effect logistic regression model with random effects for farm and date. The model identified precipitation as a single NRI predictor of spinach contamination with generic E. coli, indicating that the contamination probability increases with an increasing mean amount of rain (mm) in the past 29 days (odds ratio [OR] = 3.5). The model also identified the farm's hygiene practices as a protective factor (OR = 0.06) and manure application (OR = 52.2) and state (OR = 108.1) as risk factors. In cross-validation, the model showed a solid predictive performance, with an area under the receiver operating characteristic (ROC) curve of 81%. Overall, the findings highlighted the utility of NRI precipitation data in predicting contamination and demonstrated that farm management, environment, and weather factors should be considered jointly in development of good agricultural practices and measures to reduce produce contamination.

A stochastic model for transmission, extinction and outbreak of Escherichia coli O157:H7 in cattle as affected by ambient temperature and cleaning practices.

Many infectious agents transmitting through a contaminated environment are able to persist in the environment depending on the temperature and sanitation determined rates of their replication and clearance, respectively. There is a need to elucidate the effect of these factors on the infection transmission dynamics in terms of infection outbreaks and extinction while accounting for the random nature of the process. Also, it is important to distinguish between the true and apparent extinction, where the former means pathogen extinction in both the host and the environment while the latter means extinction only in the host population. This study proposes a stochastic-differential equation model as an approximation to a Markov jump process model, using Escherichia coli O157:H7 in cattle as a model system. In the model, the host population infection dynamics are described using the standard susceptible-infected-susceptible framework, and the E. coli O157:H7 population in the environment is represented by an additional variable. The backward Kolmogorov equations that determine the probability distribution and the expectation of the first passage time are provided in a general setting. The outbreak and apparent extinction of infection are investigated by numerically solving the Kolmogorov equations for the probability density function of the associated process and the expectation of the associated stopping time. The results provide insight into E. coli O157:H7 transmission and apparent extinction, and suggest ways for controlling the spread of infection in a cattle herd. Specifically, this study highlights the importance of ambient temperature and sanitation, especially during summer.

Strain-specific Growth Parameters are Important to Accurately Model Bacterial Growth on Baby Spinach in Simulation Models.

Digital tools to predict produce shelf life have the potential to reduce food waste and improve consumer satisfaction. To address this need, we (i) performed an observational study on the microbial quality of baby spinach, (ii) completed growth experiments of bacteria that are representative of the baby spinach microbiota, and (iii) developed an initial simulation model of bacterial growth on baby spinach. Our observational data showed that the predominant genera found on baby spinach were Pseudomonas, Pantoea and Exiguobacterium. Rifampicin-resistant mutants (rifR mutants) of representative bacterial subtypes were subsequently generated to obtain strain-specific growth parameters on baby spinach. These experiments showed that: (i) it is difficult to select rifR mutants that do not have fitness costs affecting growth (9 of 15 rifR mutants showed substantial differences in growth, compared to their corresponding wild-type strain) and (ii) based on estimates from primary growth models, the mean (geometric) maximum population of rifR mutants on baby spinach (7.6 log10 CFU/g, at 6°C) appears lower than that of the spinach microbiota (9.6 log10 CFU/g, at 6°C), even if rifR mutants did not have substantial growth-related fitness costs. Thus, a simulation model, parameterized with the data obtained here as well as literature data on home refrigeration temperatures, underestimated bacterial growth on baby spinach. The root mean square error of the simulation's output, compared against data from the observational study, was 1.11 log10 CFU/g. Sensitivity analysis was used to identify key parameters (e.g., strain maximum population) that impact the simulation model's output, allowing for prioritization of future data collection to improve the simulation model. Overall, this study provides a roadmap for the development of models to predict bacterial growth on leafy vegetables with strain-specific parameters and suggests that additional data are required to improve these models.

Knowledge, Health, and Social Drivers of Frozen Vegetable Consumption Practices Relevant to Listeriosis in Women of Childbearing Age.

In recent years, there have been numerous recalls of frozen vegetable products due to Listeria monocytogenes contamination, which causes listeriosis. In pregnant women, listeriosis can cause miscarriage, stillbirth, and other serious complications. Manufacturing guidelines are created with the intention that frozen vegetables will be cooked prior to consumption. However, consumers may prepare and eat frozen vegetables without prior cooking. Therefore, it is necessary to assess behaviors that could be risky for L. monocytogenes exposure. A 10-question online survey was distributed to women between the ages of 18-54 to investigate frozen vegetable consumption behaviors. The prevalence of uncooked frozen vegetable consumption, reading preparation instructions, and listeriosis knowledge was assessed. Data were analyzed using logistic and ordered logit regression. Of 1,001 complete responses, 531 (53%) indicated that they consumed frozen vegetables in the past week, and of those 35.6% (n = 189) indicated that they consumed frozen vegetables without prior heating. Women who had not heard of listeriosis and had not read preparation instructions had significantly higher odds of uncooked frozen vegetable consumption (Odds Ratio (OR): 2.30, 95% Confidence Interval (CI): 1.48, 3.55; OR: 1.85, 95% CI: 1.13, 3.01, respectively). These results will guide future research on safe food handling practices for frozen vegetable products. The findings support the need for updating public health guidelines to include frozen vegetables as foods that are risky for listeriosis in pregnancy. Additionally, these findings have implications for future research to inform food policy governing labeling regulation on frozen vegetable products to reflect current consumer behavior.

Generic Escherichia coli contamination of spinach at the preharvest stage: effects of farm management and environmental factors.

The objective of this study was to determine the effects of farm management and environmental factors on preharvest spinach contamination with generic Escherichia coli as an indicator of fecal contamination. A repeated cross-sectional study was conducted by visiting spinach farms up to four times per growing season over a period of 2 years (2010 to 2011). Spinach samples (n = 955) were collected from 12 spinach farms in Colorado and Texas as representative states of the Western and Southwestern United States, respectively. During each farm visit, farmers were surveyed about farm-related management and environmental factors using a questionnaire. Associations between the prevalence of generic E. coli in spinach and farm-related factors were assessed by using a multivariable logistic regression model including random effects for farm and farm visit. Overall, 6.6% of spinach samples were positive for generic E. coli. Significant risk factors for spinach contamination with generic E. coli were the proximity (within 10 miles) of a poultry farm, the use of pond water for irrigation, a >66-day period since the planting of spinach, farming on fields previously used for grazing, the production of hay before spinach planting, and the farm location in the Southwestern United States. Contamination with generic E. coli was significantly reduced with an irrigation lapse time of >5 days as well as by several factors related to field workers, including the use of portable toilets, training to use portable toilets, and the use of hand-washing stations. To our knowledge, this is the first report of an association between field workers' personal hygiene and produce contamination with generic E. coli at the preharvest level. Collectively, our findings support that practice of good personal hygiene and other good farm management practices may reduce produce contamination with generic E. coli at the preharvest level.