Professor Alison Mather from the Quadram Institute and University of East Anglia is leading an international consortium that will develop a practical method of detecting and monitoring the spread of genes responsible for antimicrobial resistance in bacteria.
The MEtaGenome-informed Antimicrobial resistance Surveillance, or MEGAISurv project is being supported by the Medical Research Council on behalf of the Biotechnology and Biological Sciences Research Council, the Engineering and Physical Sciences Research Council, and the Medical Research Council, under the framework of the JPIAMR – Joint Programming Initiative on Antimicrobial Resistance. The project involves researchers from University College Dublin (Professor Séamus Fanning, Dr Guerrino Macori), Utrecht University (Dr Aldert Zomer and Dr Tim Dallman) and Dawn Farm Foods (Dr Nick Andrews).
Antimicrobial resistance (AMR) is one of the most pressing challenges to global health. As more and more bacteria become resistant to the drugs used to control them, our collective ability to fight infections and maintain human health becomes weaker. AMR also threatens food security; our ability to grow sufficient crops and raise livestock relies on a sustainable, balanced relationship with the bacteria in the soil, on plants, in animals and across all environments.
Excessive or inappropriate use of antimicrobials in any of these settings can accelerate the evolution of AMR. Bacteria have remarkable abilities to share genetic elements, even across species, which has fuelled the spread of AMR. Understanding and tackling this demands a ‘One Health’ approach that links human, animal, and environmental health.
“Antimicrobial resistance is a threat to our health and well-being, and One Health surveillance is essential to understanding its sources, reservoirs and transmission” said Prof. Fanning.
This is the approach being taken by the MEGAISurv project. Their aim is to develop tools that can be used to assess the level of AMR in a particular sample, and the risk of its spread. Currently, levels of AMR are generally quantified by culturing an indicator organism, for example E. coli, and measuring its resistance. The MEGAISurv approach will use metagenomic sequencing. This attempts to sequence all the genes in a sample, without culturing, so providing a more complete picture of the level and type of AMR.
“Looking at only one indicator organism in all human, animal, food and environmental samples is like studying ocean life by looking at a single droplet of seawater with a microscope. Interesting differences can be found between droplets but is it really the entire picture?” said Dr Zomer.
The team will use long-read Nanopore sequencing, which has another advantage in that the data it produces can provide some information about how transmissible a particular AMR gene is. It can tell whether an AMR gene is within the bacterium’s chromosome, or whether it is on plasmids and transposons. These are more mobile genetic elements that make transmission to other bacterial species more likely. The team will also develop new analytical tools to investigate point mutations causing AMR in metagenomes and provide a novel computational framework to risk assess the spread of AMR.
“Our overall objective is to develop and validate the tools and analytical frameworks necessary to maximise the technological advancements in metagenome and long-read sequencing to generate high quality and actionable surveillance data across the One Health paradigm” said Prof. Mather.
“By applying these tools in real-world settings, we will learn how best to use them to target and evaluate interventions to reduce the spread of AMR” said Dr Andrews.