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The One Health resistome: Integrating environmental, microbial, and human antimicrobial resistance surveillance and
Arnab Majumdar1, Dhritidipa Bagchi2, Ioly Kotta-Loizou1
1Department of Life Sciences, Imperial College London, London SW7 2AZ, United Kingdom.
Abstract:
Antimicrobial resistance (AMR) and antibiotic resistance (ABR) represent one of the most pressing global health threats, driven by the complex interplay between human, animal, and environmental factors. The One Health resistome framework recognises that resistance genes circulate continuously across clinical, agricultural, and environmental compartments through horizontal gene transfer, co-selection mechanisms, and anthropogenic contamination. This comprehensive review synthesises current evidence on integrated AMR surveillance, examining how digital technologies are transforming our capacity to monitor, predict, and respond to resistance emergence. Key advances include whole-genome sequencing enabling high-resolution pathogen tracking, metagenomics revealing environmental resistome diversity, machine learning algorithms predicting resistance phenotypes with > 85% accuracy, and point-of-care diagnostics extending sophisticated testing to resource-limited settings. Geographic information systems facilitate spatial hotspot identification, while wastewater-based surveillance provides early warning capabilities, detecting resistance genes before clinical manifestation. Despite technological progress, substantial challenges persist: fragmented data streams across sectors, lack of standardised environmental monitoring methods, limited laboratory capacity in low- and middle-income countries, and chronic underfunding. Emerging technologies, portable nanopore sequencing, CRISPR-based diagnostics, artificial intelligence, and blockchain-enabled data governance promise to address these gaps. Realising comprehensive One Health resistome surveillance requires sustained investment in interoperable digital infrastructure, international standardisation, capacity building, and political commitment to cross-sectoral coordination, prioritising equitable global implementation.
Insights
Antimicrobial resistance (AMR) is a major global health threat. Digital technologies like genomics and AI are improving surveillance, but challenges in data sharing and funding remain for effective One Health strategies.
Area of Science:
- One Health
- Microbiology
- Public Health
Background:
- Antimicrobial resistance (AMR) and antibiotic resistance (ABR) pose significant global health risks.
- The One Health framework highlights the interconnectedness of human, animal, and environmental factors in AMR.
- Resistance genes spread across different compartments via horizontal gene transfer and contamination.
Purpose of the Study:
- To review integrated AMR surveillance strategies.
- To examine the role of digital technologies in monitoring and predicting AMR.
- To identify challenges and future directions for One Health resistome surveillance.
Main Methods:
- Review of current evidence on integrated AMR surveillance.
- Analysis of digital technologies including whole-genome sequencing, metagenomics, machine learning, and GIS.
- Examination of wastewater-based surveillance and point-of-care diagnostics.
Main Results:
- Digital technologies significantly enhance AMR monitoring, prediction, and response capabilities.
- Whole-genome sequencing offers high-resolution pathogen tracking; metagenomics reveals environmental resistome diversity.
- Machine learning predicts resistance with >85% accuracy; wastewater surveillance provides early warnings.
Conclusions:
- Despite technological advances, challenges like data fragmentation, lack of standardization, and underfunding persist.
- Emerging technologies offer potential solutions for comprehensive One Health resistome surveillance.
- Sustained investment, standardization, capacity building, and cross-sectoral coordination are crucial for global AMR control.
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