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TEXAS: Towards next-generation AMR surveillance: Assessment of novel technologies with high-throughput and multiplexing potential

Lead Research Organisation: Durham University
Department Name: Biosciences

Abstract

There is growing recognition that reducing global AMR requires integrated surveillance of clinically relevant markers (e.g., genes associated with specific resistant pathogens, "drug-bug" combinations). However, there is no consensus regarding which markers to target and what exposures are safe, or what technologies are most suitable for monitoring the selected markers. The proposed TEXAS project will define a suite of genetic
markers that best describe AMR status of a targeted location, and integrate them into multiplexed platforms using new technologies that do not require cultivation of bacteria. A digital droplet PCR (ddPCR) platform (suitable for high income regions) will quantify clinically relevant markers in a diverse range of environments, generating large and synchronized datasets that can be exploited for comparative AMR status, facilitating
understanding of AMR across different One Health sectors. In tandem, an electrochemical biosensor will provide a means for high-throughput on-site monitoring of selected AMR markers. The biosensor does not require special equipment or trained operators, and thus can be applied in low income regions that lack sophisticated infrastructure. The multidisciplinary TEXAS consortium includes experts in electrical and water engineering, genomic epidemiology, molecular microbial ecology, public health, and policy guidance. Consequently, we are confident that the project will generate implementable technological solutions that can be adopted by stakeholders for integrated surveillance that will be fundamental to reducing global AMR.

Technical Summary

Various genetic approaches are used for AMR surveillance, but there are few harmonized, high-throughput platforms that target clinically relevant markers that indicate AMR mobility and multidrug resistance (MDR). Here we will develop and validate two promising technological platforms that can be readily incorporated into national and international integrated surveillance programs. Our digital droplet PCR platform will provide a highly sensitive unbiased method of resistance gene (ARG), mobile genetic element, and taxonomic gene co-occurrence in complex environments. This approach allows genetic source tracking of clinically relevant MDR pathogens in regions with suitable analytical facilities. In tandem, our multiplexed DNA-based electrochemical biosensor platform will facilitate on-site multiplexed quantification of MDR markers, which
reduces the need for expensive analytical equipment and highly trained staff. This will be invaluable for AMR surveillance in low-resource regions. Both technological platforms will integrate taxonomic, ARG and mobility markers inferred from microbiological, epidemiological, and environmental data generated by the consortium. The diverse and multidisciplinary TEXAS team includes experts on technology development as well as policy guidance to international organizations on central to global integrated surveillance planning. This will promote adoption of selected targets, and implementation of the two platforms (validated against gold standard methods) for samples collected from low- and high-resource settings and differing sectoral contexts.

Publications

10 25 50
 
Description Integration lead in the new UN Quadripartite Technical Group on Antimicrobial Resistance and Use Integrated Surveillance (QTG-AIS)
Geographic Reach Multiple continents/international 
Policy Influence Type Participation in a guidance/advisory committee
Impact The Guide connected environmental AMR surveillance with human, animal and plant health surveillance in a manner that can be used in low, medium and high economic settings. It aims to unify methods and data management.
 
Description Chinese National Academy of Science - Ningbo Institute of Urban Environment 
Organisation Chinese Academy of Agricultural Sciences
Country China 
Sector Academic/University 
PI Contribution We are working with CAS (w/ Prof Yong-Guan Zhu) on the use of artificial intelligence and machine learning in understanding AMR research around the world to develop the most relevant and representative targets for diagnostic tools developed in TEXAS This is an extension of on-going joint work.
Collaborator Contribution We are sharing resistome samples for comparisons between samples within this new project, our previous collabarotion on ARC AMR, and their samples from Antartica and Tibet. The goal of this additional work is to determine how background AMR gene levels compare in "remote" locations around the world.
Impact Two manuscripts have resulted thus far, but more are under development.
Start Year 2021
 
Description Keynote Address at the 2024 World One Health Congress in Cape Town 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact Provided a keynote presentation entitled "Improving cross-sectoral integration in AMR prevention and surveillance", which centred on the integrated use of artificial intelligence and machine learning methods, and the physical environmental monitoring in developing priority targets for AMR mitigation across One Health settings.
Year(s) Of Engagement Activity 2024
URL https://globalohc.org/8WOHC