Flows of antimicrobial resistance and pathogens through environment to food chain
Project Lead
Challenges
Farm animals are a major source of key zoonotic pathogens of humans, including enteric disease-causing Campylobacter spp., Salmonella spp., enterotoxigenic Escherichia coli and Clostridioides difficile. There are around 2.4 million cases of foodborne pathogen infections annually in Scotland, with a financial burden of £9 billion. Importantly, many gut bacteria carry antimicrobial resistance genes (ARG), some of which are located on mobile genetic elements with the potential to transfer to other bacteria (commensal or pathogenic). It is predicted that by 2050, deaths caused by antimicrobial resistance (AMR) will exceed those caused by cancer and diabetes. Reducing the carriage of zoonotic pathogens within the gastrointestinal tract of farm animals has clear potential to reduce the incidence of human foodborne disease and the spread of AMR - both of which are real health crises.
Despite a significant body of research globally on AMR in the environment, there are still many unknowns about transmission from the environment to humans. We need to improve our understanding of the routes of transmission of resistance including the impact of the environment and food. There is a lack of understanding of how differences in farming practices can drive AMR and pathogen transmission combined with a paucity of data quantifying antimicrobial gene load onto food crops. There are also challenges around identifying increased risk to farmers due to their proximity to antimicrobials and animals. There is also a limited understanding of how farmers perceive the link between antimicrobial use and AMR, and how this may influence behaviours. Lastly, there is a lack of a unifying model to predict future scenarios of hazards to food.
Questions
- What are the sources and epidemiology of foodborne disease in Scotland and what interventions can be introduced to reduce foodborne disease?
- What new methods can be developed to assist with identifying and tackling emerging microbiological, chemical, and nutrient risks in food for Scottish consumers and businesses?
- What are the flows of bacterial antimicrobial resistance (AMR) genes through soils, animals, and humans?
Solutions
The aim of this project is to quantify the flow of ARG and pathogens from the environment to the food chain and directly to humans in the farm environment. We are integrating social science work to understand the perceptions farmers have of the link between antimicrobial use and antimicrobial resistance. Both quantitative and qualitative data is being used to develop a risk assessment model based on the source-pathway-receptor principle.
Understanding the flow of bacterial antimicrobial resistance genes and pathogenic E. coli through soils, animals, and humans
We are attempting to obtain a better understanding of the flow of bacterial ARG and pathogenic E. coli through soils, animals, and humans. To quantify antibiotics in soils, we are developing new methods to track the transmission of ARG from sources through the environment to the food chain under different farming practices. Soils and manures are known sources of ARG, with water sources acting as conduits between environments, but little is known about how farming practices may influence the transmission of ARG from these sources to the food chain.
Next, we are quantifying the difference in ARG load onto food crops grown under traditional vs integrated crop management, and ARG carriage in farm workers compared to the animals they handle. We are determining farmer perceptions of the link between antimicrobial use and AMR. Social sciences work has focused on attitudes and behaviours related to antimicrobial use on-farm, but little is known about how farm workers conceptualise and deal with the link between antimicrobial use and AMR regarding their health, animal health and environmental AMR. Lastly, we are addressing the flow of pathogenic and non-pathogenic E. coli from source to receptor. Similarly, this activity is identifying the drivers of pathogen flows from the environment to the food chain.
This project links to the work done in the Emerging Water Futures project on antibiotic and ARG quantification methods in soils, manures and crops and some shared aspects of Bayesian Belief Network modelling.
Developing models to support quantitative risk assessments on hazards that affect the Scottish food chain
We are developing models to support quantitative risk assessments on hazards that affect the Scottish food chain. To do this, we are building a risk assessment model to assess the impact of different farm management approaches on ARG and pathogen flows and inform where management interventions can be implemented in the food chain system to reduce foodborne risks.
Understanding how current farming practices contribute to AMR and pathogen dissemination allows for better-targeted interventions. Therefore, this work is helping inform policy and industry governance on farming practices (including antimicrobial use) to reduce the transmission of antimicrobials, AMR, and pathogens to the food chain. Ultimately, this is impacting and benefiting public health through the reduction of human exposure to food hazards and reducing pressure on public health services.
Project Partners
Progress
A literature review to inform sampling strategy, so as to capture the flow of AMR on farms, identified several AMR sources as sampling points (e.g., water, faeces, soil and feed) as well as possible methods of transfer (e.g., equipment, run-off and water troughs). The review also identified ARG that should be monitored as well as current knowledge gaps. Environmental samples have been taken from four farms covering a range of farm practices (organic, conventional and integrated), including two experimental farms of the James Hutton Institute (JHI). Additionally, 43 arable farm samples were obtained from the SoilBio archive. Sample processing and analysis is underway.
A method has been developed to measure antibiotics in soils. Twelve antibiotics were chosen for the method development (extraction then analysis by LC-MS/MS): sulfadiazine, sulfamethoxazole, trimethoprim, ofloxacin, ciprofloxacin, norfloxacin, doxycycline, chlortetracycline, oxytetracycline, erythromycin, clarithromycin and azithromycin. Instrumental parameters of the combined liquid-chromatography with tandem mass spectrometry (LC-MS/MS) method (e.g., ion transition, entrance voltage, collision cell lens and collision energy) were optimised for these target compounds, in addition to the extraction conditions (e.g., solvents and solid-phase extraction cartridge). Output such as recoveries, linearity and limit of detection (LOD) were determined.
Ethical approval for participant observation on dairy farms was obtained from the JHI Research Ethics Committee. Participant observation is proving to be a valuable method for gathering in depth understanding into farmers' antibiotic and waste management practices. Initial results are indicating participants are concerned about the risk of AMR, but at a societal level rather than in relation to themselves, their farm and their animals. The biggest risk around antibiotic use is seen as potential contamination of the milk supply which could lead to financial losses and reputational damage to their milk buyer. Farmers do not receive much information about the risk to themselves nor the spread of resistance genes through waste on the farm. All study paperwork was prepared, and ethical approval obtained from the Rowett Ethics Committee, for faecal sample collection from farmers on the above dairy farms. Recruitment of dairy farmers to provide samples of which to analyse the microbial profile and carriage of ARG has commenced and the first samples received.
A preliminary conceptual model structure, informed through a stakeholder/expert workshop, to model the risk of AMR transmission and exposure via the food chain has been developed. The model structure is based on the source-pathway-receptor principle and developed around the example of lettuce production, a commonly used model crop in quantitative microbial risk assessments. The model focuses on the AMR risks during lettuce production within the environment (i.e., AMR transmission during growth to harvest), however there are also separate modules to model the post-harvest stages of processing, post-processing and home preparation. The model has been implemented in GeNie, a software for Bayesian Belief Network modelling, that is described in a short summary report.
The envisioned impact of this project includes using the empirical data accumulated as a baseline of AMG levels on farms using different management practices; in future this could be used to determine whether changes in practice lowers AMR risk. The method we developed to measure antibiotics in soil could be provided as a service for other researchers, regulators and industries to gain a better understanding of the extent of antibiotic pollution. The section of the project concerned with observing the activities of farmers and asking them about their understanding of antimicrobial usage and impacts will contribute to policy on managing waste containing antimicrobial residues to prevent the spread of resistance into the environment and to gain a better understanding of the health and safety needs of farmers and farm workers in relation to AMR. The section evaluating the levels of ARG in the guts of farmers and farm workers will aid in understanding the role of direct contact vs. food chain transfer of resistance genes. Finally, AMR risk model aims to identify AMR control points to inform policy and practice in order to identify where in the food chain system management interventions could be implemented to reduce foodborne AMR risks.
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