Revealing new insights into MDR evolution, ecology and transmission across human, animal and environmental microbiomes

Antimicrobial resistance (AMR) a growing global crisis, posing a significant threat to human and animal health. Approximately one million deaths a year are directly attributed to drug-resistant bacterial infections with a further four million deaths associated with resistant infections every year. To address this challenge, we are excited to announce our ground breaking research project aimed at understanding and addressing the complex drivers of multi-drug resistance (MDR) across the One Health continuum. AMR is the process by which microorganisms such as bacteria and fungi adapt to survive and flourish in the presence of drugs used to treat infections. Bacteria can become resistant through random changes in their DNA (mutation) which enables their survival during antibiotic treatment. Of more concern is the fact that they can acquire foreign pieces of DNA (genes) through a process known as horizontal gene transfer, which allow bacteria to acquire resistance to multiple antibiotics in one step. AMR is not new, it has evolved in microbial populations in the environment over millions or billions of years to counteract antimicrobials naturally produced by fungi and bacteria, and these resistance mechanisms can move from harmless environmental bacteria to human pathogens. Globally, more antibiotics are used in intensive livestock farming than in clinical medicine and there is a strong association between antibiotic use in farming and resistance in animal gut microbiomes. This link between AMR in humans, animals and the environment has led to ideas around One Health, which acknowledges that to understand human health a broader consideration of animal and environmental systems is necessary. Although we know there is an association between AMR across One Health sectors, the relative importance of bacteria living in the environmental and livestock (ie. their microbiomes) and their role in emergence of resistance in human pathogens is poorly understood. Much like COVID-19 emerged from a wildlife reservoir, there are vast AMR reservoirs in animal and environmental microbiomes, and we need to understand the process that amplify these and lead to emergence in human pathogens. We will apply new state of the art computational analyses to DNA sequence data from human, animal and environmental microbiomes in the UK and China, to determine which resistance mechanisms are actively evolving in different settings. This will be combined with novel machine learning and computational approaches to predict MDR in pathogens and bacterial populations allowing drivers of resistance to be quantified. We will use experimental evolution models to determine causal relationships between antibiotic use and development of resistance, including hypothesis testing informed by our analyses and replicating antibiotic use in clinical medicine, livestock production and antibiotic residues introduced to the environment by pollution. This data will be used to develop a new risk assessment framework, that for the first time will include data on evolutionary dynamics of resistance genes across One Health microbiomes. Our novel approach will be tested in a proof of principle case study on human wastewater microbiomes in the UK and China allowing socio-economic, demographic, genetic, evolutionary and environmental drivers to be considered simultaneously. We will also develop low-cost diagnostic tools for detection of key MDR markers. Outputs will be communicated at national and supranational level through the unrivalled networks of team members in China, the UK and organisations such as the WHO and UN.