Antimicrobial resistance (AMR) is recognized by the World Health Organization (WHO) as a critical global health threat, particularly in low- and middle-income countries (LMICs). Agri-environments, including animal farms, agricultural soils, and crops, are emerging as significant origins of AMR. Given the cross-sectoral nature of the problem, spanning animals, humans, and the environment, addressing AMR requires a comprehensive One Health approach. This research focuses on LMICs in Asia and Africa, including China, Kenya, Iran, Sri Lanka, and Bangladesh, regions experiencing severe AMR challenges.
To understand the sources and risks associated with AMR in agri-environments, we conducted extensive sample collection from animal manure treatment systems and agricultural settings. Key methodologies include the detection of veterinary antibiotics using UPLC-MS/MS, profiling the antibiotic resistome with metagenomic sequencing, and quantifying clinically relevant antibiotic resistance genes (ARGs) such as optrA and tet(X4) through qPCR. Additionally, epicPCR (emulsion, paired-isolation, and concatenation PCR) was employed to identify environmental bacterial hosts of these ARGs, complemented by whole genome sequencing of ARG-carrying opportunistic pathogens.
The study’s objectives include assessing AMR risks in LMIC agri-environments, evaluating existing control technologies, and developing novel strategies based on the One Health paradigm. We aim to establish a comprehensive AMR data catalog covering China, Kenya, Iran, Sri Lanka, and Bangladesh, along with biological risk distribution reports and traceability studies. Furthermore, our work supports the development of international standards, policy guidance, and risk management strategies to curb AMR through reduced antibiotic use and improved manure treatment practices.
We invite collaboration to advance One Health solutions that address the global AMR crisis. By fostering sustainable practices in animal production, we can protect the health of animals, humans, and the environment in LMICs and beyond.