Understanding the eco-evolutionary drivers of emerging antifungal resistance
Lead Research Organisation:
UK CENTRE FOR ECOLOGY & HYDROLOGY
Department Name: Pollution (Wallingford)
Abstract
Microbes in their environment are exposed to changing conditions, which select for the most fit variants. This continual process of adaptation leads to the genetic composition of populations shifting in space and time as the fittest mutations track change. Unfortunately, when selection is imposed by chemicals that are designed to kill microbes, then those that are genetically resistant rise in frequency; this results in the global problem of antimicrobial resistance evolving in the environment.
While emerging antimicrobial resistance is widely recognised in bacteria, the emergence of fungi that are resistant to antifungal chemicals is underappreciated yet is compromising our ability to grow blight-free crops and to treat serious human fungal diseases -therefore presenting a classic One Health dilemma. The core focus of our project is Aspergillus species, common environmental moulds to which all humans are exposed due to their ubiquitous presence in the air. Of note, A. fumigatus affects millions of susceptible individuals worldwide (including those with COVID-19) and is increasingly causing disease that is resistant to the frontline azole antifungal drugs that are used to treat it. Crucially, this is the same class of chemicals is used by farmers as fungicides, which is driving a surge in azole-resistant A. fumigatus as this mould comes under selection by these chemicals in its natural environment. However, we currently have very little understanding of the landscape-scale pathways that lead to fungicide chemical residues accumulating to the concentrations that select for, and amplify, resistance in moulds. We understand even less about the consequences combinations of different fungicides on the emergence of resistance, or how interactions with the wider microbial community that may hinder (or help) the emergence of resistance.
Our project will examine the nested anthropogenic drivers - agricultural practices and green-waste recycling - with the aim of understanding how they create hotspots of evolution for antifungal resistant pathogens. The moulds on which we will focus are embedded in complex microbial ecosystems and we will determine the impact of scale from country-wide distributions of the fungus, through the ecological succession seen in fungicide-rich mesocosm environments, and down to individual model microcosm models. To do this, we will couple field and laboratory studies with Bayesian-based statistical methods that take into account both evolutionary and ecological complexity within a spatially-explicit framework. In doing so, we will be able to identify, understand and link the key factors that lead to hotspots of fungicide-resistant moulds forming. The variables that we measure - landuse, fungicides, fungal genetics and microbial community ecology - will be integrated into a systems network analysis that links the usage of fungicides in the environment to ecological settings where resistance is selected for. These 'Bayesian probabilistic networks' are a powerful tool which will allow us predict hotspots for fungal drug-resistance, as well as allowing us to model methods to mitigate against this risk by reducing fungicide-inputs into specific 'pinch-points' that we identify.
Ultimately, by dissecting the extended (unintentional) consequence of fungicide use as these chemicals drive the evolution of fungal antimicrobial resistance, our project will address this problem within its greater 'One Health' context. Our approach is urgently needed to develop the knowledge-base that is needed to understand the current risk as well as to mitigate the selection-pressure driving future emergence of fungal antimicrobial resistance in the environment.
While emerging antimicrobial resistance is widely recognised in bacteria, the emergence of fungi that are resistant to antifungal chemicals is underappreciated yet is compromising our ability to grow blight-free crops and to treat serious human fungal diseases -therefore presenting a classic One Health dilemma. The core focus of our project is Aspergillus species, common environmental moulds to which all humans are exposed due to their ubiquitous presence in the air. Of note, A. fumigatus affects millions of susceptible individuals worldwide (including those with COVID-19) and is increasingly causing disease that is resistant to the frontline azole antifungal drugs that are used to treat it. Crucially, this is the same class of chemicals is used by farmers as fungicides, which is driving a surge in azole-resistant A. fumigatus as this mould comes under selection by these chemicals in its natural environment. However, we currently have very little understanding of the landscape-scale pathways that lead to fungicide chemical residues accumulating to the concentrations that select for, and amplify, resistance in moulds. We understand even less about the consequences combinations of different fungicides on the emergence of resistance, or how interactions with the wider microbial community that may hinder (or help) the emergence of resistance.
Our project will examine the nested anthropogenic drivers - agricultural practices and green-waste recycling - with the aim of understanding how they create hotspots of evolution for antifungal resistant pathogens. The moulds on which we will focus are embedded in complex microbial ecosystems and we will determine the impact of scale from country-wide distributions of the fungus, through the ecological succession seen in fungicide-rich mesocosm environments, and down to individual model microcosm models. To do this, we will couple field and laboratory studies with Bayesian-based statistical methods that take into account both evolutionary and ecological complexity within a spatially-explicit framework. In doing so, we will be able to identify, understand and link the key factors that lead to hotspots of fungicide-resistant moulds forming. The variables that we measure - landuse, fungicides, fungal genetics and microbial community ecology - will be integrated into a systems network analysis that links the usage of fungicides in the environment to ecological settings where resistance is selected for. These 'Bayesian probabilistic networks' are a powerful tool which will allow us predict hotspots for fungal drug-resistance, as well as allowing us to model methods to mitigate against this risk by reducing fungicide-inputs into specific 'pinch-points' that we identify.
Ultimately, by dissecting the extended (unintentional) consequence of fungicide use as these chemicals drive the evolution of fungal antimicrobial resistance, our project will address this problem within its greater 'One Health' context. Our approach is urgently needed to develop the knowledge-base that is needed to understand the current risk as well as to mitigate the selection-pressure driving future emergence of fungal antimicrobial resistance in the environment.
Publications

Glover RE
(2023)
The antibiotic subscription model: fostering innovation or repackaging old drugs?
in The Lancet. Microbe

Glover RE
(2023)
Why is the UK subscription model for antibiotics considered successful?
in The Lancet. Microbe

Shelton JMG
(2023)
Citizen science reveals landscape-scale exposures to multiazole-resistant Aspergillus fumigatus bioaerosols.
in Science advances

Srathongneam T
(2024)
High throughput qPCR unveils shared antibiotic resistance genes in tropical wastewater and river water.
in The Science of the total environment
Description | Animal and Environment AMR Delivery Group for Wales |
Geographic Reach | National |
Policy Influence Type | Participation in a guidance/advisory committee |
Description | Consultant for the U.S. Department of State on Environmental AMR |
Geographic Reach | North America |
Policy Influence Type | Participation in a guidance/advisory committee |
Description | PATH-SAFE Science Advisory Group |
Geographic Reach | National |
Policy Influence Type | Participation in a guidance/advisory committee |
Description | AMR National Action Plan in the UK and the Role of WBS of AMR into the future |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Postgraduate students |
Results and Impact | To provide a seminar at Virginia Tech University suited to a focused group of academics interested in the use of wastewater surveillance and its applications to AMR. |
Year(s) Of Engagement Activity | 2024 |
Description | Antimicrobial Resistance in the Environment |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Policymakers/politicians |
Results and Impact | Aim was to provide US policymakers with an understanding of the environmental dimension of AMR. |
Year(s) Of Engagement Activity | 2023 |
Description | The Environmental Dimension of Antimicrobial Resistance |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Postgraduate students |
Results and Impact | Provided an overview of the environnmental dimension of AMR with insights into how surveillance for AMR might benefit from advances seen in wastewater-based surveillance. |
Year(s) Of Engagement Activity | 2024 |
URL | https://www.lshtm.ac.uk/newsevents/events/environmental-dimension-antimicrobial-resistance |
Description | Wastewater-based Epidemiology: A paradigm shift in democratising health surveillance |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Postgraduate students |
Results and Impact | A mixture of academics were focused on a range of cutting edge research that includes examining the environment for signals of human behaviour and health. The outcome of the meeting was to help focus research new areas where gaps remain and policy benefit can be seen. |
Year(s) Of Engagement Activity | 2023 |