We aim to apply artificial intelligence (AI) models in combination with experimental assays to unveil the roles of the newly discovered non-canonical proteome in the cellular physiology of G protein-coupled receptors (GPCRs). Genes have historically been thought to encode a single reference protein and its spliced isoforms, but recent technological advances (Ribo-Seq and proteogenomics) have highlighted thousands of non-canonical coding sequences (CDS)[1-2]. These non-canonical sequences are found in non-coding RNAs (ncRNAs), in the untranslated regions (UTRs) of mRNAs, or overlapping the canonical CDS in a different frame. Genomes can thereby generate many proteins aside from the currently annotated proteins. These additional proteins are termed alternative proteins or AltProts[1,3]. An ever-increasing number of studies highlight the biological roles of AltProts, notably their ability to bind to, and modulate, the functions of the canonical protein product of the gene[1,4-9]. This alternative proteome represents a large reservoir of uncharacterized proteins and hitherto unexplored avenues of fundamental and clinical research. However, there is no standardized annotation of AltProts and as they are relatively small, the risk of random CDS (false positive) is high. We need a data-driven and reliable approach to identify translated CDS and prioritize AltProts for functional characterization. Recent successes of deep learning models in sequence segmentation and classification bodes well for its applicability to the field of AltProts. Here, we suggest deep learning models can guide AltProt prioritization as well as structural and functional characterization to unveil their roles in the regulation of cell signalling. Our efforts will focus on GPCR signalling pathways as they control cellular physiology and are major targets for therapeutic drugs[10-11]. Identifying AltProts that are novel regulators of these pathways will transform our understanding of cell biology and generate actionable knowledge for the pharmacological industry. This interdisciplinary project links AI, bioinformatics, genetics, proteomics, structural biology, pharmacology and cell biology. It aims to use AI to identify and prioritize AltProts involved in regulation of GPCR signalling in human cells, and to experimentally validate predictions.

The growth of organisms, and organs such as the brain, fingers and toes, occur by cells dividing and changing from simple precursors into complex cells with specific functions through a series of carefully regulated processes. The cell cycle controls cell division by requiring the cell to pass multiple checkpoints to ensure only a healthy cell can divide. Another important ability for a cell is to be able to stop dividing. For example, when no more cells are required in the developing brain, cells exit the cycle resulting in no more cells being produced than are needed. Failure to exit the cell cycle can lead to excessive cell numbers, and so-called overgrowth disorders, whereby organs are too big and often do not have the correct structure. In the brain this results in the disorder megalencephaly. While brains generally stop growing once fully developed, the brains of people with overgrowth disorders continue to grow. This growth persists even after surgical intervention, resulting in further complications. Taken together, these observations tell us that precise management of the cell cycle is required for development of the brain as well as other cells and organs in the body. The aim of my research is to investigate a family of 3 proteins called D-type Cyclins (CyclinD), that act as a molecular switch for the cell cycle. This will help to understand the molecular processes that control the cell cycle and how these lead to disease when they don't work correctly. When CCND levels are high, cells continue to divide to create more cells, however when CyclinD is switched off the cells stop dividing. I am interested in disorders that occur which CyclinD's do not get switched off, meaning cells continue to divide even when they're not supposed to. In particular, I want to learn more about the molecules that control this switch, what happens in a cell when the switch cannot be turned off and to develop molecules that target CyclinD in order to stop the cells dividing. Using this information, I hope to learn how cells signal to stop cell division normally and therefore how they coordinate the development of complex structures such as the brain. Currently there are no cures or therapies available that can specifically target CCND accumulation. Through my research, we have gained a better understanding of how CyclinD is regulated. Using this new knowledge, I have developed CyclinD-inhibitors that can overcome the effects of CyclinD accumulation and have generated relevant cell-based disease models in which to test them in. This study will therefore test a panel of CyclinD-inhibitors I have developed on a range of relevant disease models in order to test their therapeutic potential for cancers and overgrowth disorders.

NERC: Kathryn Powell: NE/S007261/1 Insects underpin almost all ecosystems on the planet. They provide innumerable services to humans and other species through regulating the environment and providing resources. Abundance and biomass declines in a dominant group of species such as insects, are thought to be particularly damaging to ecosystem health due to the disproportionately large role they play in ecosystem functioning. Local studies have found evidence that insect populations are declining. However, due to data deficiencies and biases, there is yet to be a unified consensus on the extent of insect declines across the globe, and on the contribution of drivers, such as agricultural intensification, on long-term declines. Some of these data deficiencies exist because of fundamental issues with insect sampling and analysis protocols, such as using inappropriate temporal and/or spatial resolution to analyse long-term trends, and varying sampling effort. Given the scale of the challenge to assess a hyper-diverse taxonomic group such as insects, it is important to design cost-efficient yet statistically robust monitoring methods. This project will advance the solution Researchers at Université de Sherbrooke in Québec, Canada, aim to understand the impact of agricultural intensification on insect abundance and their predators (aerial insectivores such as tree swallows). The group has collected Diptera abundance and biomass data since 2006 from suction traps across gradients of agricultural intensity, from forest to intensively farmed arable fields. Due to extensive sampling effort, with traps checked every two days over the 15-year sampling period and over a wide spatial scale, I will be able to use the dataset to provide robust analysis of long-term trends in abundance of functionally important Diptera in Québec. I will also test how sampling scale and effort affect the outcome of analyses that monitor the impact of agricultural intensification on insects, in order to inform a future sampling protocol with optimal sampling effort for capturing long-term trends. This will help fill research gaps by re-purposing a dataset to uncover insect trends in an area where they constitute an important food source for other species like tree swallows, and laying foundations for the design of better insect monitoring and analysis protocols to understand drivers of decline. My project will both add to our knowledge of insect population trends and drivers of decline across the globe, and pave the way for future insect biodiversity research. The outcomes of our research will therefore meet research needs of both UK and Canadian biodiversity policies, addressing biodiversity loss through developing efficient ways to capture long-term insect trends and the impacts of environmental drivers on these trends. It will also provide a baseline abundance trend for flies in this region, which will be required for Canada's new sustainable agriculture plans, given that the sites in the dataset cover a significant area important for agriculture in Québec. The objectives I will achieve during my placement will bring exposure to skills and experiences outside of my PhD, such as taxonomic identification and interaction with public audiences, and will make me a more skilled, communicative and collaborative researcher. My project will give me exposure to a wider network of people across Canadian institutions so that I may foster long-term partnerships with experts in my field and further develop my future career in academia.

WHO and the G20 have identified the growing threats of Anti-Microbial resistance (AMR) as a major concern that will define the future of global health. Despite these urgent calls, the emergence of AMR in settings of war and distress migration has not been systematically explored. Case reports from Syria, Iraq, Libya, Yemen, and Afghanistan have shown the proliferation of AMR in combatants and civilians injured in these protracted conflicts. With regional conflicts spreading across state borders as well as one of the largest global refugee crises in decades, AMR in the context of conflict has come to pose a serious threat both regionally and internationally. So began penicillin in the Second World War: antibiotics arose in war. Today, in the context of long-running military conflicts we see harbingers of the end of antibiotics. The core question underpinning this proposal is how war, particularly weapons and the industrialised, urbanised context of contemporary conflicts, drives antibiotic resistance by contaminating the environment and the human and non-human organisms that live there. So far, there has been no systematic or holistic consideration of the environmental health impacts of contemporary conflicts conducted in cities. Our program draws together scholars working in the fields of medicine, anthropology, history of science, ethics, epidemiology, microbiology, molecular biology, and environmental sciences to examine the specific intersection of antibiotic resistance and war. Rather than focus on antibiotic resistance as a universal problem afflicting modern societies in general, we focus first on the impact of global conflict on antibiotic resistance more holistically, and second on the case of multi-drug resistant Acinetobacer baumanii (MDRAB), initially reported by American military surgeons under the moniker Iraqibacter, and that has been identified recently by the WHO as a "critical pathogen" for research and the development of new antibiotics. We will focus on a number of specific countries - Iraq, Syria, Palestine, Yemen, and Lebanon-places with history of protracted conflicts and with different, yet overlapping, ecologies of war. The potential global health significance of conflict-related heavy metal mediated antimicrobial resistance is enormous and warrants further study. It will contribute to the field of environmental pathways for antimicrobial resistance more broadly as well as informing the specific intersection of war and antibiotic resistance.

Insects are the little things that run the world (E.O. Wilson). With increasing recognition of the importance of insects as the dominant component of almost all ecosystems, there are growing concerns that insect biodiversity has declined globally, with serious consequences for the ecosystem services on which we all depend. Major gaps in knowledge limit progress in understanding the magnitude and direction of change, and hamper the design of solutions. Information about insects trends is highly fragmented, and time-series data is restricted and unrepresentative, both between different groups of insects (e.g. lepidoptera vs beetles vs flies) and between different regions. Critically, we lack primary data from the most biodiverse parts of the world. For example, insects help sustain tropical ecosystems that play a major role in regulating the global climate system and the hydrological cycle that delivers drinking water to millions of people. To date, progress in insect monitoring has been hampered by many technical challenges. Insects are estimated to comprise around 80% of all described species, making it impossible to sample their populations in a consistent way across regions and ecosystems. Automated sensors, deep learning and computer vision offer the best practical and cost-effective solution for more standardised monitoring of insects across the globe. Inter-disciplinary research teams are needed to meet this challenge. Our project is timely to help UK researchers to develop new international partnerships and networks to underpin the development of long-term and sustainable collaborations for this exciting, yet nascent, research field that spans engineering, computing and biology. There is a pressing need for new research networks and partnerships to maximize potential to revolutionise the scope and capacity for insect monitoring worldwide. We will open up this research field through four main activities: (a) interactive, online and face-to-face engagement between academic and practitioner stakeholders, including key policy-makers, via online webinars and at focused knowledge exchange and grant-writing workshops in Canada and Europe; (b) a knowledge exchange mission between the UK and North America, to share practical experience of building and deploying sensors, develop deep learning and computer vision for insects, and to build data analysis pipelines to support research applications; (c) a proof-of-concept field trial spanning the UK, Denmark, The Netherlands, Canada, USA and Panama. Testing automated sensors against traditional approaches in a range of situation; (d) dissemination of shared learning throughout this project and wider initiatives, building a new community of practice with a shared vision for automated insect monitoring technology to meet its worldwide transformational potential. Together, these activities will make a significant contribution to the broader, long-term goal of delivering the urgent need for a practical solution to monitor insects anywhere in the world, to ultimately support a more comprehensive assessment of the patterns and consequences of insect declines, and impact of interventions. By building international partnerships and research networks we will develop sustainable collaborations to address how to quantify the complexities of insect dynamics and trends in response to multiple drivers, and evaluate the ecological and human-linked causes and consequences of the changes. Crucially, this project is a vital stepping-stone to help identify solutions for addressing the global biodiversity crisis as well as research to understand the biological impacts of climate change and to design solutions for sustainable agriculture. Effective insect monitoring underpins the evaluation of future socio-economic, land-use and climate mitigation policies.