The aim of synthetic biology is to modify cells or biological systems in ways that produce societal and economic benefits in the areas of healthcare, energy production, food security and the environment. Eukaryotic cells hold huge potential in synthetic biology, however, due to their complexity, modifying them using conventional synthetic biology approaches, which involve constructing gene networks, is challenging. In contrast, directly regulating the function of proteins inside these cells may offer a simpler method to control their behaviour. A number of options, including antibodies, are currently available to do this, but the drawback of these approaches is that they cannot be easily switched off, so they affect the cell's behaviour continuously. In order to control cell behaviour more precisely, we need to develop a new system that can be turned on or off rapidly. The Ideal system would comprise a switch-like 'effector' protein inside the cell that can be engineered to bind and regulate other proteins, and a 'receptor' protein on the cell surface that can switch the effector protein on when a specific chemical is added to its environment. G protein-coupled receptor (GPCR) signalling pathways are natural systems that cells use to communicate; they are therefore ideal templates for the development of a new tool to control cell behaviour. GPCRs are cell-surface receptors that detect chemicals outside the cell, and activate effector proteins, called 'G proteins', inside the cell. The G proteins act as switches, which, when activated by GPCRs, bind and regulate their target protein, before switching themselves off in a time-dependent manner. Until now, it has not been possible to modify G proteins to bind and regulate different cellular proteins because of the high degree of complexity that has evolved within these pathways. However, I recently developed a simplified G protein that may, for the first time, make this possible. This proposal aims to modify the GPCR signalling pathway to create a novel cell-based tool that will allow us to control the activity of different proteins inside live eukaryotic cells. This will enable us to either study the protein's function in real time or directly control cellular processes and behaviours. The key component of this system will be the simplified G protein, which will be modified so that it can bind and regulate different cellular proteins. This G protein can be activated by either native GPCRs, in which case the tool could be controlled using naturally occurring chemicals (such as a hormone), or a modified GPCR, in which case it could be controlled by a specially designed chemical. This tool will have applications in several different areas. First, it will underpin basic research to understand the function of native cellular proteins that are central to the health and disease of animals and humans. Second, it will have applications in the development of a range of cell-based biosensors capable of detecting hundreds of physiologically-relevant chemicals in real time. Third, it will facilitate research in the field of regenerative medicine, by facilitating the precise control of human cell behaviour, for example, cell division. The first four years of the Fellowship will be used to develop and optimise the tool, and to foster partnerships with companies that are capable of translating it into viable healthcare products. The final three years will focus on both developing the biosensor applications, with the aim of producing miniaturised medical diagnostic devices, and exploring applications to control human cell division, with the aim of developing improved treatments for degenerative conditions such as osteoarthritis. The long-term implication of this research will be a novel cell-based tool that will benefit both academic and industrial researchers, by simplifying the implementation of synthetic biology in eukaryotic cells and expediting its promised societal and economic benefits.

The global human population is predicted to increase by a third over the next 25 years, with countries of the developing world hosting 97% of this expansion. The ability to 'feed 9Bn people sustainably by 2050' is an urgent priority Indian and UK governments with the 12th Indian Five Year Plan requiring growth of the agricultural sector at 4% per annum to achieve food security. Poultry farming is a highly efficient and cost-effective system for producing animal protein for human consumption, but circulating infectious diseases compromise gut health and impact dramatically on farm economics, animal welfare and occasionally human health through transmission of zoonoses. Poultry gastrointestinal infections of most concern in UK and India are caused by avian pathogenic Escherichia coli (APEC), Campylobacter jejuni, Clostridium perfringens, Eimeria and Salmonella. Susceptibility to gut colonisation and the outcomes of infection are directly influenced by many factors including host genotype, immune status, age at infection, strain of infecting microbe, composition of commensal enteric microbiota and presence of other acute or chronic infections. There are significant interactions between host and microbe biology, genetics, epigenetics, the environment and farm practices. Changes to diet, use of vaccines or antimicrobials, and flock-level interventions such as 'thinning', can have profound effects on intestinal health and the evolution and spread of disease-causing microbes and may be amplified by genetic variation in host and microbe populations. Whilst major advances in genomics and genotyping of commercial poultry lines is facilitating the identification of loci linked to susceptibility or resistance, the impact of host and pathogen diversity on disease and production outcomes remains largely unexplored. There is rich genetic diversity in India's native poultry breeds, and the hybrid exotic lines often used in Indian commercial production are distinct from the majority of poultry reared in the UK. The prevalence and dynamics of gastrointestinal infection at farm-level has a direct bearing on economic risk to individual farmers and contributes to overall global concerns of food security and food safety. Gaps in current knowledge prompt four fundamental questions around which this proposal is framed: 1. What is the epidemiology of specified gastrointestinal infections, and co-infections, across UK and Indian poultry production systems? 2. Does host genotype exert an influence on (a) the prevalence, evolution and transmission of specified microbes and (b) the composition of flock-level enteric microbiota? 3. What is the level of genetic variation within specific microbial populations in Indian and UK poultry production? 4. What on-farm factors affect the risk of enteric colonisation and carriage of specified microbes and how can changes in poultry husbandry and management practices mitigate this risk? The proposal brings together UK and India experts in poultry genetics, animal health, epidemiology, pathology and pathogen biology. A multidisciplinary approach combining metagenomic sequencing, high density SNP-based QTL mapping, bacteriology, parasitology, molecular epidemiology and mathematical modelling will be used to quantify and predict disease risks at farm and national levels and to inform the development of intervention and management strategies, including future breeding and husbandry planning.

Software is integral to the fabric of our lives, controlling transport, the economy and infrastructure, and providing the main tools of work and leisure. The cost of software failures is therefore high, to productivity, stability, safety, and privacy. As an indication of the economic impact, it is estimated that software errors cost the US economy tens of billions of dollars last decade. Software errors can also impact human safety as software is used to control transport, infrastructure, and medical equipment. The research agenda of program verification aims to mitigate these risks by putting software engineering on a rigorous foundation through techniques to guarantee program correctness. As software becomes more complex and pervasive, program verification is ever more important. This work aims to advance the state-of-the-art in verification at the point of program development through advancements in programming language theory and practice. Programming languages are the core tool in which software is constructed; they are the means of communicating our intentions to computer hardware. There are various design trade-offs when creating a programming language, which has led to the variety of programming languages in use today. Some languages support verification by including a "type system" which categorises data and operations, ensuring that operations are only applied to data of the correct type. This provides some guarantees about the correctness of the program by ruling out various kinds of error before the program is ever executed. A subfield of programming language research aims to make type systems more expressive so that they can describe and enforce more properties of programs and thus raise the level of verification possible within the language. The current proposal aims to do just this, focussing on the notion of data as a "resource" subject to constraints which should be enforced by a language's type system. This project develops a particular technique for building such type systems in a way that can capture various kinds of property in one system. The manipulation of data is central to the task of programming. Current programming languages essentially view data as an infinitely-replicable resource that can be stored, manipulated, and communicated without restriction. However, this perspective is naive. Some data is private and thus should not be arbitrarily copied, stored, or communicated. Some data is large and thus should not be replicated too frequently. Some data acts as a way of interfacing with other parts of a system, e.g., files or communication channels, which are then subject to restrictions on how they can be used, such as agreed protocols of interaction. Most programming languages are agnostic to these constraints however, treating data as totally unconstrained. This can lead to various software errors, including privacy breaches, performance problems, and crashes due to incorrect interactions between parts of a system. The goal of this research is to embed the constraints associated with data into the type system of a language so that these additional constraints can be automatically enforced. The key technology for doing this is a novel notion of types called "graded modal types" which can capture and track different kinds of information about the structure of programs and the flow of data through them. This work will develop the theory and practice of graded modal types, producing a prototype language that demonstrates their use for verifying program properties. Three case studies will be carried out to demonstrate their power: (1) ensuring privacy and confidentiality, (2) capturing and reasoning about performance e.g., how fast a program will execute relative to the size of its inputs and how much memory it will consume (3) enforcing fine-grained protocols of interaction. This work is a step towards a new generation of trustworthy software.

Passive non-neuronal brain cells called astrocytes have emerged as a critical yet grossly understudied part of brain machinery. Atrocytes take up released neurotransmitters, maintain ionic homeostasis of the extracellular space, and generate a variety of molecular signlas that regulate neural circuit activity. However, the emerging difference between animal and human astroglia in their morphology and physiology threatens the harm-benefit ratio of animal preparations in this important field of neuroscience and neurology. In this respect, realistic computational models of astroglia and astroglia-neuronal networks could provide hypothesis testing, mechanistic physiological insights, and an inter-species knowledge transfer that are unattainable in animal experiments. Exploring such models ought to minimise animal experimentation with no loss of knowledge, yet the methodology to create the corresponding modelling environment is only beginning to emerge. Thus, the present project aims to combine an experimental methodological approach, on the one hand, and open-access computer-simulation platforms, on the other, that would shift the weight of knowledge-based glial research from animals to human tissue preparations and realistic computational models. This will be achieved through the three objectives: (i) to establish working experimental protocols for up-to-date studies of human astroglia in organised brain tissue, making them a commonly accessible, viable alternative to animal brain tissue research strategies, (ii) to create an open-access computational platform that enables exploratory investigation of realistic biophysical models of astroglia, thus reducing similarly aimed experimental trials in animals, and (iii) to generate an experimental data library adaptable for the functional comparison of animal and human astroglia, thus providing a guidance on potentially implausible extrapolation of animal data to human brain astroglia.