Tools for the Epidemiology of AMR Plasmids, One-Health Transmission and Surveillance

Antimicrobial resistance (AMR) is spreading rapidly across the globe, and much of this is driven by autonomous 'elements' of DNA called plasmids, which can common carry AMR genes. The ability of AMR plasmids to transfer independently between bacteria, even of different species, presents a serious challenge for epidemiologists attempting to monitor the prevalence and spread of AMR, because the patterns of transmission of AMR plasmids, and AMR genes, might be distinct from those of the bacteria themselves. There is thus a requirement at the core of One-Health AMR management strategies to tease apart the transmission of strains, plasmids (and even individual AMR genes), to implement effective monitoring and risk assessments. Currently, however, our capacity for to track plasmids is limited due to how quickly they evolve and diversify. This network brings together experts who have made critical contributions to this problem through the development of bioinformatics tools, clinical and non-clinical AMR surveillance, and plasmid biology. The network includes partners from low and middle-income countries and will place an emphasis on training and stakeholder engagement.

Antimicrobial resistance (AMR) is spreading rapidly across the globe, and much of this is driven by plasmids harbouring AMR genes. The ability of AMR plasmids to transfer independently presents a serious challenge for epidemiologists attempting to monitor the prevalence and spread of AMR using genomics approaches, because the patterns of transmission of AMR plasmids, and AMR genes, might be distinct from those of the host bacteria. There is thus a requirement at the core of One-Health AMR management strategies to tease apart the transmission of strains, plasmids (and even AMR genes carried in transposons), to implement effective monitoring and risk assessments. Currently, however, our capacity for effective plasmid molecular surveillance in both clinical and non-clinical settings is limited due to the diversity and speed of evolutionary change of plasmids. This poses both bioinformatic and conceptual problems, and current plasmid typing schemes lack the resolution to infer transmission links. This network brings together experts who have made critical contributions to this problem through the development of bioinformatics tools, clinical and non-clinical AMR surveillance, and plasmid biology. The network has two key aims:i) design and implement a novel platform (plasmid.watch) that incorporates WGS data from plasmids and their host strains (allowing easy cross-referencing between the two), and ii) identify the optimum rapid plasmid typing methods for surveillance. The network includes partners from LMICs and will place an emphasis on ECR training and stakeholder engagement.