Current projects

Primary investigator: Professor Véronique Gouverneur
Awarded: 2024/25

Since the 1940s, anthropogenic per- and polyfluoroalkyl substances (PFAS) are produced on large scale for use in most industry branches. In addition to well-known applications such as textile impregnation, fire-fighting foams, and electroplating, PFAS are components of consumers products as diverse as food packaging, cooking ware materials and soil remediation. Structurally, PFAS feature multiple C-F bonds that are at the origin of their surface properties, and are responsible for their resistance to biological or chemical degradation. Today, environmental persistence and bioaccumulation have resulted in global PFAS contamination in drinking water, livestock and agricultural products, with evidence of negative impact on human health upon chronic exposure.

With circular chemistry in mind, the design of a mild method that harvests the fluorine content of PFAS-contaminated waste stream for the production of critically- needed fluorochemicals would represent a paradigm shift in PFAS management. Such regenerative approach would contribute to diminish the root cause of impending global challenges such as food, water and energy shortages, depleted biodiversity and climate change. With this project, we propose a solution to this pressing challenge, based on the treatment of PFAS with a suitable inorganic salt under mechanochemical conditions; the process will generate a new solid “PFAS-mix” that will not be disposed in landfills or incinerated, but instead, will serve as a fluorinating reagent for the production of fluorochemicals.

Primary investigator: Professor Harvey Whitehouse
Awarded: 2023/24

This work builds on work by co-investigator Dr Julia Ebner that was a finalist for the ESRC Celebrating Impact Prizes and work by Dr Ebner, Professor Whitehouse, and colleagues that won the President’s Medal from the Market Research Society. This work is also co-funded by the Airey Neave Trust and a British Academy Talent Development Award.

Do heads of state who engage in extreme forms of violence against their own populations or foreign populations inadvertently give away their intentions in what they say? Prior to the visible changes in Russia’s military activities in 2021, most experts would have considered a Kremlin-led aggression war in Ukraine an unlikely scenario. Like with Vladimir Putin, the willingness of many leaders to translate hawkish words into action has proven hard to predict. How seriously should we take Kim Jong-un’s aggressive threats? How dangerous are countries led by ideologically extreme figures such as Iran under Ebrahim Raisi or Afghanistan under the Taliban? What about Erdogan or Min Aung Hlaing who both have a history of violence against their own populations? And most importantly, might there be an underestimated threat emerging in countries that are currently not on the radar of the diplomatic, defence and intelligence communities? 

The aim of our project is to establish an evidence-based psycholinguistic framework that can assess the risk that despotic leaders of autocratic states will resort to violent forms of repression domestically or hawkish foreign policies when the use of violence in these contexts carries high risk to self and group. The project will use a mixed methods approach, coupling qualitative text analysis with quantitative natural language processing (NLP) analysis to address the following questions: What makes some heads of states resort to violent means against their own population or other countries despite heavy costs that would deter most other political strategists? Could the risk of wars and seemingly irrational (e.g. high risk or costly) acts of aggression, resulting in genocides and other atrocities, be predicted based on the socio-psychological drivers that leaders unintentionally reveal via their speeches? 

Primary investigator: Professor Lars Østergaard
Awarded: 2023/24

Sustainable crop production is a central requirement for humanity to meet global challenges related to food security and climate change, as well as the related issues of climate-driven conflict and migration. Legumes (Fabaceae) comprise a globally important source of protein-rich and high-quality food. Their cultivation also reduces the environmental impact of agriculture, given its low emissions of greenhouse gasses and reduced requirement for nitrogen fertiliser. Here we will use the pea (Pisum sativum) as a model to understand the genetic and hormonal interactions underlying legume pod growth regulation.

Upon pollination, the pea pod grows to accommodate and nurture the developing seeds inside. Peas – along with other species in the Fabeae and Trifolieae (F/T) tribes of the Fabaceae – produce a chlorinated variant of the plant hormone auxin that is distinct from regular auxin (IAA). This chlorinated auxin (4-Cl-IAA) is enriched in fruits and seeds relative to vegetative tissues, and it crucially promotes pod growth. In F/T-species, endogenous 4-Cl-IAA may therefore serve as a seed-derived signal perceived by maternally-derived tissue – a signal provided by IAA in non-F/T and non-legume species. Intriguingly, 4-Cl-IAA is absent from the F/T sister taxon, Cicereae, and all other earlier diverging legume species. The significance of the evolution of this hormone ~25 million years ago in a common ancestor of the F/T tribes is unclear.

Understanding the mechanism underlying 4-Cl-IAA-promoted pod growth will enable us to increase pod size and therefore the photosynthetically active area of the pod. This will have positive effects on legume seed production. The major aim of this project is to: 1) identify molecular components that allow pea to distinguish between 4-Cl-IAA and IAA, and 2) unravel the evolutionary trajectory of 4-Cl-IAA signalling response. Ultimately, our goal is to uncover key regulators involved in the 4-Cl-IAA-mediated promotion of pea pod growth, with the vision of translating this new-found knowledge to legume crops beyond the pea.

Primary investigator: Dr Maheshi Ramasamy
Awarded: 2023/24

The history of medicine reveals significant strides taken in public health in the last century; the development of evidence-based interventions alongside the partnership of international organisations has led to rigorous and effective responses to infectious disease. Yet the history of medicine also shows that the cooperation of the public is vital to the success of any public health intervention. During the Covid-19 pandemic, a significant challenge was a lack of trust in scientific expertise exhibited in some communities. While much attention has been focused on vaccine hesitancy and the proliferation of conspiracy theories, an overlooked phenomenon is the existence of rival forms of forecasting, fringe practices of ‘divination’ used by some communities to predict the course of the pandemic and guide behaviour.  

Lack of public trust in medical expertise is not just a modern phenomenon, nor is the existence of competing practices of forecasting. The origins of epidemiological forecasting are said to be traceable to 1662, when the merchant John Graunt experimented with population data derived from the London Bills of Mortality. Yet when Graunt undertook his studies, there was a lively forecasting marketplace in which numerous practices of prediction attempted to monitor and predict the health of the public. One of these was astrology, which, in stark contrast to its fringe position in modern society, was counted as an academic subject into the late seventeenth century. Astrologers used quantitative tools not only to count the spread of disease in society, but to correlate this with external factors, using the patterns they found to predict epidemics.  

During successive outbreaks of plague in the early modern period, many turned to astrology for answers to epidemiological questions. It is striking, then, that during the Covid-19 pandemic, we saw a similar phenomenon: for many, astrology was again a compelling rival to epidemiological forecasting. This project therefore seeks to investigate how the public has navigated the existence of rival forms of disease forecasting. In addition, the project aims to demonstrate that forecasting epidemics has a history longer and more complicated than current narratives about the origins of epidemiology suggest. Finally, the project also aims to show how, regardless of the evidence-base of any form of forecasting, the authority of forecasters in the eyes of the public, and the perceived legitimacy of the knowledge they produce, is historically and culturally contingent.

Primary investigator: Dr Jennifer Castle
Awarded: 2022/23

Human-induced climate change is the biggest threat to humanity, leading to an escalation of extreme weather events, loss of land from rising sea levels and loss of biodiversity, resulting in increased loss of life and livelihoods, along with rising inequality, migration, and social unrest. The threat is stark, documented by the IPCC, and our project addresses this through rigorous statistical analysis to model outcomes, produce forecasts and propose policy interventions to achieve the stated goal of net zero greenhouse gas emissions by 2050.

How can decision makers be confident that actions they undertake to tackle climate change will benefit the climate and put economies on a path to net zero? The answer is in evidence-based policy, so it is crucial the evidence base is meticulous, accurate and statistically sound. Our project will develop climate applications based on powerful and innovative empirical modelling techniques. It will also deliver policy analysis to show how to get to net zero in a fair and equitable way.

Climate science has established a vast body of knowledge about the processes and causal links in the Earth’s climate system. The climate of planet Earth depends on the energy balance between incoming radiation from the Sun and re-radiation from the planet. But greenhouse gas emissions are mainly due to economic activity, so the econometric methods used to model human behaviour naturally play a role in modelling climate change outcomes and implications.

The key outcomes anticipated from this project are: a) more robust climate models based on cutting-edge econometric methods with a focus on policy relevant topics; b) linking empirical feedbacks between greenhouse gas emissions and socio-economic processes; c) knowledge exchange between climate scientists and social scientists, bridging the gap by showing the commonalities and differences between the physical and statistical approaches; d) new research showing how net zero can be achieved in a fair and equitable way, proposing policies to focus on stranded workers and their families, addressing issues of poverty as well as stranded assets; and e) direct evidence based analysis of the progress Magdalen College is making towards its stated goal of net zero by 2050.

Primary investigator: Dr Rachel Wheatley
Awarded: 2022/23

Antibiotics are crucial for treating bacterial infections. The rising resistance of bacterial pathogens to antibiotics poses a global health threat and is increasing treatment failure, mortality, and healthcare costs associated with infections. Over one million deaths in 2019 alone were attributable to the antibiotic resistance of bacteria, and this number is only predicted to rise. While it is well established that antibiotic treatment selects for resistance, the dynamics of this process during the complex biological environment of infection remain less well understood. 

Tackling the rise of antibiotic-resistant pathogens requires a combined ecological and evolutionary approach. We need an improved understanding of how resistance emerges and spreads in individual species, which are often embedded in dynamic microbial communities such as the gut or respiratory microbiome. Microbes existing in the same space will sense and respond to each others presence, exchange metabolites, genetic material, compete for resources and space, and all of this will change how a single entity responds to environmental stressors such as antibiotics. The goal of this research project is to investigate how the presence of a microbial community shapes antibiotic resistance evolution of a bacterial pathogen. The outcomes of this research could highlight microbiome manipulation approaches for reducing the emergence of antibiotic resistance. Furthermore, this project addresses a fundamental question in evolutionary biology – how does ecology inform on evolution?

Primary investigator: Professor Tim Barraclough
Awarded: 2022/23

The Threat to Humanity that we address is the decline in food supply and resilient ecosystems due to failure to control pests and diseases of crop plants sustainably. Pests and disease account for losses of 30% of plant crops worldwide (around 5% in the UK). Losses would be greater still without existing control methods, which focus on resistant varieties and chemical pesticides. Current approaches are unsustainable, however, for two main reasons. First, pests evolve to overcome any new control within 5 years or so, leading to a continual ‘arms race’ with agriscience needing to develop new varieties and chemicals. Second, pesticides have off-target effects on other species, which leads to environmental deterioration and a reduction in the resilience and productivity of crop systems themselves (for example, through declines in pollinators and natural enemies that eat pests).

Policy makers recognise the need to reduce chemical inputs and limit the land area devoted to intensive agriculture (for example, in The European Commission’s Green Deal, 2019- 2024), but we currently lack ways to do that without losing more crops to plant disease. We need to develop more specific control measures with fewer off-target effects and that are more robust and agile for counter-acting the evolution of resistance. Better methods are vital to feed the growing population while simultaneously reducing harm to the environment.

Current work shows that RNA interference (RNAi) sprays work in several major fungal disease of crops, with the ability to knock down metabolic genes, including targets of current fungicides. But history shows us that resistance to any new control measure will evolve in short order, and as yet we lack a strong set of design principles for choosing which genes to target to maximise effectiveness (now that all of them are accessible in theory thanks to these new tools). There are great opportunities for developing a toolkit for designing optimal RNAi strategies.

Our new approach is to identify design principles for choosing genetic targets based on enhanced knowledge of the evolutionary dynamics of crop pathogens. Specifically, we are sequencing whole genomes of a suite of fungal pathogens from a frozen collection of living samples that spans the last 70 years or so that saw the rise of chemical agriculture. We use these genomes to identify genes and traits that have evolved quickly in response to pressures from past control measures (such as resistance pathways and effectors of plant infection). This part of the work is already underway through John Fell funding, a NERC-funded PhD student, and a grant submitted to BBSRC is currently under review.

The next step is to use this information, coupled with evolutionary theory of how gene networks should evolve in response to new pressures, to design targets for RNAi control. For example, desirable properties for gene targets might include taxonomic specificity; a lack of off-target effects both in the focal pathogen and in other species; a role in symptoms or infection rather than growth in the environment (which would limit the arena for resistance evolution); evidence of strong purifying selection (i.e. conserved regions); genes found in genome compartments with low mutability; genes in highly linked networks (where resistance mutations would have knock on effects that bring costs to resistance); and/or genes that control the evolutionary rate of pathogens to slowdown the evolution of resistance.

Primary investigator: Dr Laura Fortunato
Awarded: 2017/18

What factors sustain cooperation in humans? The answer to this question is of both theoretical and practical interest, as society faces challenges that can only be addressed through cooperative behaviour. Recent events, most notably in the political world and in the public health domain, highlight the importance of understanding social interactions within and between human groups.

This research project aims to investigate the effect of network structure and dynamics on social behaviour in humans, focusing on factors related to cooperation and competition, including the role of social norms. It brings together researchers with expertise in cultural evolution, the evolution of cooperation, and the social-psychological study of inter-group conflict. A key element of the project is data collection in the Italian city of Siena. The city centre has been historically divided into 17 contrade, roughly equivalent to districts. Members of the contrade feel strong allegiance towards the district they are affiliated with, forming close-knit communities that engage in related activities and rituals throughout the year. The key event in the Sienese calendar is the world-famous palio, a bareback horse race featuring the contrade, which is held in the central city square twice over the summer months. As such, the contemporary contrade provide an ideal setting to study patterns of social interaction within and between naturally occurring human groups.