MODELING THE ENVIRONMENTAL BIOLOGY OF FOODBORNE PATHOGENS TO SUPPORT THE SAFETY OF LOCAL FRESH FOOD IN THE UPPER GREAT PLAINS

• Sponsoring Institution: National Institute of Food and Agriculture
• Project Status: TERMINATED
• Funding Source: HATCH
• Reporting Frequency: Annual
• Accession No.: 1008073
• Project No.: ND02428
• Project Start Date: Oct 28, 2015
• Project End Date: Sep 30, 2019

Project Director
Bergholz, PE, WA.

Recipient Organization
NORTH DAKOTA STATE UNIV
(N/A)
FARGO,ND 58105

Performing Department
Microbiological Sciences

Non Technical Summary
This work will be used to support local food and community supported agriculture in North Dakota by providing growers with much needed information on how to manage their lands to ensure the safest food possible. Engaging in thinking about food safety in farm fields is important for growers in North Dakota, because fresh fruits and vegetables can reach large numbers of families, including communities like schools and nursing homes that are populated by people who are especially vulnerable to severe outcomes from foodborne illnesses. The most likely economic impacts of this research for North Dakota are through improvements to public health both through improved nutrition and reduced medical and business costs-associated with food safety practices and foodborne illnesses. A grower who can say that they have followed the Good Agricultural Practices and FDA recommendations is: a) less likely to grow food that ultimately causes illness, b) open to a larger customer base, including large grocery store chains that benefit from selling locally sourced food, and c) less vulnerable to civil suits associated with foodborne illness. Conversely, uncertainties about good food safety practices, regulations and audit requirements from retailers are among the biggest hurdles to entering the local food marketplace. This begs the question, "how does this research relate to GAPs and the proposed produce safety rule?" The proposed work directly tests the environmental behavior of foodborne pathogens in North Dakota, thus verifying the value of GAPs and Produce Safety Rule recommendations for growers in North Dakota. But a second, more direct benefit to growers, packers and retailers in North Dakota can be realized by translating our results directly into a GIS mapping algorithm. Such an algorithm can: a) make predictions about which parts of a grower's land, if any, are especially vulnerable to pathogen contamination, and b) be used to devise harvesting and planting strategies that will minimize chances for contamination. Work on this has already begun in my laboratory, with an initial version of a mapping algorithm that predicts the prevalence of Listeria monocytogenes in mixed-use agricultural landscapes in the Northeastern United States.

Animal Health Component

0%

Research Effort Categories

Basic

50%

Applied

20%

Developmental

30%

Classification

Knowledge Area (KA)	Subject of Investigation (SOI)	Field of Science (FOS)	Percent
712	0199	1060	100%

Knowledge Area
712 - Protect Food from Contamination by Pathogenic Microorganisms, Parasites, and Naturally Occurring Toxins;

Subject Of Investigation
0199 - Soil and land, general;

Field Of Science
1060 - Biology (whole systems);

Keywords

food safety

genomics

modeling

geographic information systems

environmental microbiology

listeria monocytogenes

foodborne pathogens

soil

climate

population

Goals / Objectives
Objective 1. Empirically measure and model the farm and landscape scale factors constraining abundance of foodborne pathogens.Hypothesis: The abundance of foodborne pathogens in croplands will vary spatially according to environmental factors among farms and within them. Some farms will have higher baseline levels of foodborne pathogens.Objective 2. Empirically measure and model the farm and landscape scale factors constraining the dispersal of foodborne pathogens.Hypothesis: Farm fields in landscapes with greater density of tree cover or closer proximity to water bodies will exhibit greater connectivity for foodborne pathogens to other locations on the landscape.Objective 3. Link adaptive variation in foodborne pathogens to their prevalence in farm environments.Hypothesis: The most prevalent foodborne pathogen strains in soils and sediments will have adaptive genetic polymorphisms in membrane stress response genes, stress response regulators and outer membrane proteins.

Project Methods
Objective 1. Empirically measure and model the farm and landscape scale factors constraining abundance of foodborne pathogens.To study this, we will conduct structured field assessments of foodborne pathogen abundance and examine these data for correlations with environmental characteristics present on-farm. Field studies will be conducted to quantify spatial variation in abundance due to environmental factors within farms and variation due to farm management between farms. Studies will be conducted on six cooperating produce growing farms in North Dakota. Population abundance is quantified as numbers of detected individual bacteria per unit mass of environmental sample. We will quantify the abundance and prevalence (presence/absence) of foodborne pathogens in environmental samples according to published methods.One useful analytical technique is random forests, in which samples can be recursively partitioned based on the abundance of foodborne pathogens then maps the most useful predictor variables are mapped onto those partitions.The analysis results in sets of partitioning rules which can then be coded into a GIS to predict the abundance of pathogens in new locations.Objective 2. Empirically measure and model the farm and landscape scale factors constraining the dispersal of foodborne pathogens.The dispersal of pathogens from source populations (e.g. concentrated livestock feeding operations) to sink populations (e.g. produce fields) is a function of interactions between foodborne pathogens, dispersal vehicles, and the humans. Since our analysis of dispersal relies on network analysis, twenty to forty locations must be sampled to provide sufficient measurements for testing hypotheses. Because bacteria are not visible to the naked eye, the best way to document their movement is by documenting the movement of their genes from one location to another. The gene sequences of pathogen isolates will be used to estimate movement rates. These results will then be compared to predictions from a geographic information systems (GIS) model. A quantitative value for dispersal (Di,j) can be predicted for each pair of sampled locations in a landscape given estimates of three factors: i) Load (Li) is how like an individual pathogen is to be carried away from its point of origin, i, by some dispersal vehicle, ii) Attraction (Aj) is how likely an individual pathogen is to be deposited in a new location, j, by a dispersal vehicle, and iii) Cost distance (Ci.j) is a measure of both the distance and the difficulty of reaching j from i.We will infer the environmental factors contributing to dispersal through the use of goodness-of-fit tests between the measured gene flow data and predictive models for connectivity in a GIS.Objective 3. Link adaptive variation in foodborne pathogens to their prevalence in farm environments.To develop a complete understanding of how pathogens persist in fruit and vegetable farms and contaminate food, the genomic traits of the pathogens must be conclusively linked to their ability to persist.A stratified environmental sampling design is ideal for obtaining isolates for this GWAS. As a result, the sampling for this isolate collection can be accomplished in tandem with sampling for Obj. 1 and 2 as standard documentation on all isolates will include environmental data associated with the sample. Genome sequencing of isolates from Obj. 1 and 2 will be used to generate collections of genome variants that might be associated with persistence in farm environments.Random forest algorithms will be applied to discern associations between genome variants and environmental characteristics of samples from which individual pathogens were isolated.

Progress 10/28/15 to 09/30/19

Outputs
Target Audience:This project reached diverse groups of stakeholders, including scientists working in food safety, produce growers, bean and grain crop growers, "wild" grassland and wetland restoration and managment specialists, livestock farmers, and nutritionists and dieticians working in rural communities. Changes/Problems: Nothing Reported What opportunities for training and professional development has the project provided?Undergraduate students, graduate students, a postdoctoral associate and a laboratory technician were each trained in at least a few of the following list of topics: environmental microbiology, environmental genomics, evolutionary genomics, geospatial modeling and analysis, spatial ecology, computational simulations/agent-based modeling, microbial physiology, on-farm surveillance for foodborne pathogens, soil biology, bioinformatics, and genome-wide association analysis. How have the results been disseminated to communities of interest?Results have been disseminated in two Extension presentations, research presentations at regional and major national and international conferences in the field including ASM Microbe and IAFP. Results have appeared in published journal articles, including one in Journal of Food Protection and another in Applied and Environmental Microbiology. Results also appear in two manuscripts in preparation. What do you plan to do during the next reporting period to accomplish the goals? Nothing Reported

Impacts
What was accomplished under these goals? We changed knowledge about how E. coli and other foodborne and 'fecal indicator' microbes are able to adapt to and persist in new environments, including many different types of soil and water. Highlights of our advances in knowledge include: Improved understanding of how forest cover, and the more stable environment it provides, influences the prevalence of E. coli in soil, as does proximity to water, and near-neutral soil pH. The discovery that, in some agricultural landscapes, E. coli disperses far and persists for long periods (i.e., years) in surface soils, such that very similar E. coli genotypes can be detected in patches of up to 20 km in diameter. We have identified hundreds of naturally occurring DNA mutations in E. coli that are associated with important survival traits (e.g. the ability to tolerate high amounts of salt or moderately low pH) and with occurrence in certain types of soil (e.g.soils with various pH values). We have further identified some sets of variants, occurring in genes shared by all E. coli, that appear to confer growth and survival advantages under several stressors.

Publications

• Type: Conference Papers and Presentations Status: Published Year Published: 2019 Citation: Hawkins RGS, Arroyo A, Schmidt KN, Bergholz PW. (2019). Applying a new method for the quantification of predation by Dictyostelium discoideum on soil-isolated Escherichia coli. 2019 Meeting of the North Dakota Academy of Sciences. Grand Forks, ND.
• Type: Conference Papers and Presentations Status: Accepted Year Published: 2019 Citation: Biodiversity of Escherichia coli associated with passage through soil: a landscape genomics approach. 2019 Meeting of the Society for Molecular Biology and Evolution. Manchester, UK.
• Type: Conference Papers and Presentations Status: Published Year Published: 2018 Citation: Schwartz, MA, Arroyo A, Schmidt KN, Bergholz PW. (2018). Genome variants associated with low-temperature growth phenotypes in E. coli isolates from soil. 78th Annual Meeting of the North Central Branch of the American Society for Microbiology. Mankato, MN

Progress 10/01/17 to 09/30/18

Outputs
Target Audience:This year, the primary target audience was food safety and microbiology researchers. Changes/Problems: Nothing Reported What opportunities for training and professional development has the project provided?Graduate and undergraduate students received training in environmental microbiology, microbiology, microbial physiology, environmental modeling, bioinformatics and genome-wide association studies. How have the results been disseminated to communities of interest?Results were reported in a manuscript and thesis published, another manuscript (in preparation), a talk at ASM Microbe 2018 and a poster at ISME17. What do you plan to do during the next reporting period to accomplish the goals? Conduct a landscape genomic analysis of how E. coli adapt to other soil conditions. Analyze how other traits are or are not selected during passage of E. coli through soil and link that information to the generalized and specialized genomic variants affecting those traits in soil isolates. Present the results in publications.

Impacts
What was accomplished under these goals? We found that soil isolates of E. coli form denser biofilms than a comparable set of related isolates from the feces of wildlife. We performed a genome-wide association study to delve into the molecular basis of biofilm enhancement and found that associated variants included: a) genes for the synthesis and export of extracellular matrix, b) novel variants of adhesins and flagella, c) chemotaxis and virulence regulators (including ethanolamine metabolism), d) metal homeostasis genes, e) osmolyte biosynthesis and transport genes, and e) virulence factors - including factors for resistance against killing by neutrophils (ecotin). These findings were the subject of a student thesis and a publication under preparation. They are important because they show that passage through soil can result in selection at discrete genomic loci for traits that serve a dual purpose in extrahost survival and pathogenicity. We found evidence linking biofilm density traits and the concentration of calcium in soils of origin in the genomes of our soil isolates of E. coli. Indeed, genomic variants in genes for aerobic respiration, nitrate respiration (partial denitrification) and sugar fermentation were associated both with enhanced biofilm formation and elevated soil [Ca2+]. Similarly, variants in attachment and adhesion factors and flagella biosynthesis (motility) were associated with both biofilm density and soil [Ca2+]. This is important in food safety, because it suggests common conditions in agricultural soils may also contribute to selection for virulence and survival traits in E. coli that transiently inhabit the soil. It remains to be explored how frequently the variants for these traits may then be transferred to pathogenic E. coli strains. In the same study, we also used a machine learning algorithm to decipher that about 10% of genomic variation in our E. coli isolates correlates with one or more soil environmental variables, and that the Buffalo River may have impeded the spread of E. coli variants in our study, indicating that rivers may act as barriers for the dispersal of soil-associated E. coli in mixed-use landscapes; although they can still act as point-to-point dispersal pathways when used for irrigation. These findings were presented in an invited talk at the 2018 meeting of the American Society for Microbiology (ASM-Microbe 2018, Atlanta, GA). We worked with the American Society for Microbiology (ASM) and the local ASM Ambassador to host a seminar from Dr. Chrystal Berry Landgraf, a genomicist and outbreak investigator with the National Medical Laboratories of Canada Enterics Group in Winnipeg, Manitoba. The seminar was well-attended and hosted in the main Century Theater at North Dakota State University. We collected data on 16 traits of 277 soil isolates of E. coli that share a common ancestor approx. 250,000 ya, including, growth rates and growth yields at soil temperature, three elevated osmolarities, and two non-optimal pH levels; biofilm density at two temperatures, resistance against predation by soil amoebae, and natural variation in stress tolerance gene expression. We identified genomic variants that appear to be of generalized value, affecting multiple traits and these included variants in amino acid biosynthesis, cell wall biosynthesis, adenylate cyclase, and aromatic compound oxidation. Such a finding is important because it suggests that selection at a small subset of genomic loci can confer advantages across many stress phenotypes. Most of these results were reported on a poster presented by the PI at the 17th International Symposium on Microbial Ecology in Leipzig, Germany.

Publications

• Type: Theses/Dissertations Status: Published Year Published: 2018 Citation: Petersen, M. (2018) Biofilm formation of Escherichia coli from surface soils is influenced by variation in cell envelope, iron metabolism and attachment factor genes. (MS Thesis). North Dakota State University.
• Type: Conference Papers and Presentations Status: Published Year Published: 2018 Citation: Bergholz, PW (2018). Deposition in soil selects for enhanced biofilm formation in E. coli. ASM Microbe 2018, Atlanta, GA
• Type: Conference Papers and Presentations Status: Published Year Published: 2018 Citation: Petersen, M., Schmidt, K., Hewitt, A., Arroyo, A., and Bergholz, P. (2018). Genomic biodiversity associated with 12 traits of environmental, biotechnological, and public health relevance in Escherichia coli. 17th International Symposium on Microbial Ecology, Leipzig, Germany.

Progress 10/01/16 to 09/30/17

Outputs
Target Audience:This year, the project efforts were targetted at food safety researchers, food industry executives and professionals, and fruit and vegetable growers. Changes/Problems: Nothing Reported What opportunities for training and professional development has the project provided?Graduate and undergraduate students receieved training in environmental microbiology, microbiology, microbial physiology, bioinformatics, environmental modeling, and genome-wide association studies. How have the results been disseminated to communities of interest?Results were reported in a manuscript (under review), a video, and at a symposium at IAFP 2017. What do you plan to do during the next reporting period to accomplish the goals? Conduct a landscape genomic analysis of how genes spread through populations of Escherichia coli in agricultural landscapes. Identify adaptive variants in E. coli genomes that may be under natural selection in agricultural land uses. Present results in an invited talk at the Microbe 2018 (ASM) conference in Atlanta, GA.

Impacts
What was accomplished under these goals? We presented results on survival of Listeria monocytogenes and Escherichia coli as affected by rainfall and flooding at the 2017 meeting of the International Association for Food Protection. This talkincluded data indicating that simulated rainfall increases the abundance of culturableListeria monocytogenesin soil microcosms. In other words,L. monocytogenesgrew in soil microcosms following simulated rainfall events, and died more slowly after while soil retained its moisture from the rainfall event. It also included data on the prevalence ofE. coliin soil and on farm surfaces following a catastrophic flooding event. The detection ofE. coliin surface soils declined over time following the flood, with the biggest declines occurring over-winter.E. coliwere more prevalent near surface water on farms throughout the study, but their prevalence in areas farther removed from surface water declined until a spatial decline with increasing distance from water was observed.E. coliin surface soil became less genetically diverse over increasing time post-flood, indicating that surface soils were selecting for particular genotypes and that populations ofE. coliin soil were declining. We produced a video supporting extension efforts for home gardeners and produce growers in a region experiencing frequent flooding. The video contained data from our talk at IAFP 2017, reformatted for growers, and it included reiteration of the FDA's advice for growers for handling of crops after flood events. We compiled and analyzed data about the landscape scale factors affecting the prevalence of Escherichia coli in surface soils in agricultural landscapes. In this study, we found thatE. coliwere most abundant in forest soil samples and least abundant in croplands (corn-soybean-wheat rotation). When those prevalences were accounted for,E. coliwere most abundant in croplands and other areas that occurred in close proximity to forested areas (within 38 m). Soil pH and/or calcium exerted a selective effect onE. coli -with certain subtypes preferring exhibiting greater prevalence in mildly acidic soils. Recent rainfall may have also selected for certain subtypes ofE. coli, but this evidence was statistically marginal. We analyzed the physiological and genomic diversity of Escherichia coli isolated from surface soils. To date, we have determined that there is approximately 100% variation in growth rates of soil isolates at non-optimal pH, that there is approximately 200% variation in biofilm formation capacity in soil isolates, and that isolates of E. colifrom soilform denser biofilms than E. coliisolated from wildlife fecal deposits. We are currently analyzing genomic variants (mutations) that are associated with the phenotypic differences amongE. coli?isolates.

Publications

• Type: Journal Articles Status: Under Review Year Published: 2017 Citation: Dusek, N., A.J. Hewitt, K. N. Schmidt, and P. W. Bergholz. (Under Review). Landscape scale factors affecting the prevalence of Escherichia coli in surface soil include land cover type, edge interactions, and soil pH. Appl. Environ. Microbiol. (Under Review).
• Type: Conference Papers and Presentations Status: Published Year Published: 2017 Citation: Bergholz, P.W. (2017). Spatiotemporal analysis of microbiological contamination in New York State produce fields following extensive flooding from Hurricane Irene, August 2011. 2017 Meeting of the International Association for Food Protection. Tampa, FL.

Progress 10/28/15 to 09/30/16

Outputs
Target Audience:The primary target audiences for this work includes the scientific community and growers of fresh fruit and vegetables in the Upper Plains. Food safety professionals in the produce industry are also a target audeince for the models planned in this project. Changes/Problems: Nothing Reported What opportunities for training and professional development has the project provided? The project contributed to the training of three undergraduates, four graduate students, and one technician in environmental microbiology, environmental genomics, population genomics, and individual-based modeling using the Java Eclipse platform Repast-Simphony. How have the results been disseminated to communities of interest? Results were reported at the 16th International Symposium on Microbial Ecology. What do you plan to do during the next reporting period to accomplish the goals? Continue to analyze our large E. coli collection. Publish a paper on Listeria monocytogenes survival as affected by environmental interactions, including interactions with native microbes in soil. Continue to develop our agent-based model of foodborne pathogen dispersal. Share our results so far at the 2017 meeting of the International Association for Food Protection.

Impacts
What was accomplished under these goals? We measured the survival of Listeria monocytogenes in agriculturally impacted and protected wetlands as a function of geochemistry, microbial community composition and land management. We analyzed the prevalence of both commensal and pathogenic in soils under varying land management and soil chemistry regimes using a large collection of approx. 3,300 E. coli isolates from a single field sampling study. We search genomes of 322 of the above isolates for virulence factors. We developed an individual-based model of microbial survival and dispersal in soil. Development is still in early stages, but the model currently exhibits the characteristic behaviors of microbes competing for resources. The microbes can mutate and adapt to new habitats after a random dispersal process. We are currently exploring adding animal-driven dispersal of microbes to the model.

Publications

• Type: Journal Articles Status: Published Year Published: 2016 Citation: Bergholz, P.W. and M. Wiedmann. (2016). Toward agent-based models for pre-harvest food safety IBM JOURNAL OF RESEARCH AND DEVELOPMENT. 60(5/6). Paper 8. ppg 1-13.
• Type: Journal Articles Status: Published Year Published: 2016 Citation: Mwima, R., A. Gidudu, A. Mazimwe, A. Ligmann-Zielinska, S. Majalija, M. Khaitsa, J.D. Kabasa, and P. Bergholz. (2016). Spatially explicit uncertainty modeling of zoonotic pathogen distribution: a case of Listeria monocytogenes in New York State, USA. Applied Geomatics DOI:10.1007/s12518-016-0177-4
• Type: Journal Articles Status: Published Year Published: 2016 Citation: Bergholz, P.W., L.K. Strawn, G.T. Ryan, S.K. Warchocki, M. Wiedmann (2016). Spatiotemporal analysis of microbiological contamination in New York State produce fields following extensive flooding from Hurricane Irene, 2011. J. Food Prot. 79:384-391
• Type: Journal Articles Status: Published Year Published: 2016 Citation: Weller, D., S. Shiwakoti, P. Bergholz, Y.T. Grohn, M. Wiedmann, and L.K. Strawn. (2016) Validation of previously developed geospatial model that predicts Listeria monocytogenes prevalence for New York State produce fields. Appl. Environ. Microbiol. 82:797-807