A major challenge in biology is to understand how cells recognize external signals and give appropriate responses. Now that the sequence of the human genome is complete, it is important to assign functions to each gene and to identify the corresponding proteins that control key cellular functions. White and colleagues pioneered the development of microscopy-based methods for the visualization and timelapse measurement of biological processes in single living cells. We have used natural light-emitting proteins from fireflies, jelly fish and fluorescent corals. Synthesis (expression) of these proteins causes mammalian cells to become luminescent (light emitting in the dark) or fluorescent (change the colour of light). By placing the gene that codes for a luminescent protein next to a promoter that controls a gene of interest, we can use luminescence from living cells as a way of measuring when the gene of interest is normally switched on and off. Fluorescent proteins have also been used to genetically label proteins of interest, so that the movement of the protein can be visualized in a living cell. White and colleagues previously used timelapse fluorescence and luminescence microscopy coupled to computer simulations to investigate cell decision making. We discovered that a set of important signalling proteins, called NF-kappaB, move repeatedly into and out of the nucleus of the cell, suggesting that cells may use proteins as timers to encode complex messages (like Morse Code). This was a surprise since the original NF-kappaB protein, p65, was discovered 20 years ago and was thought to act as a simple switch that moves into the nucleus once to activate genes. Only timelapse measurements in single living cells were able to see this. The NF-kappaB system is widely recognised as crucial to the control of important cellular processes including both cell division and cell death. It is implicated as being involved in a variety of diseases, such as cancer and inflammatory disease. We will now develop a substantial systems biology project to study all of the components of this complex system. While the previous work has provided major insights, we now need a far broader range of integrated experimental tools to study it. Also the use of mathematical models to make computer predictions will be critical to help us to visualize how this system works. We will make accurate measurements of the (much larger) set of proteins that are involved in NF-kappaB signalling and the genes that are controlled by these signals. The (very experienced) project team includes bioinformaticians, cell biologists, computer scientists, mathematicians, molecular biologists, microscopists and protein chemists. The project will be managed in a structured and organized way, so that the mathematical modelling can be used to predict and design the biological experiments. A central team of experimental officers will be responsible for coordinating the experiments, data and model storage and communication of information between team members. We will study the numbers of molecules of each of the NF-kappaB proteins in the cell, their stability, chemical states and interactions with each other and with other proteins. We will also study in detail which genes that they bind to and control. We will also aim to understand how single protein molecules acting at single genes can act to control decisions of cell life and death. This multidisciplinary approach is essential in order to understand this complex system. A further aim of the project is to provide training for post-docs and students. In this respect, we will benefit from sponsorship of training courses and symposia by the instrumentation companies Carl Zeiss, Hamamatsu Photonics, Coherent and Nano Imaging Devices. The project will also benefit from ongoing collaborations with Genetix and AstraZeneca

A major challenge in biology is to understand how cells recognize external signals and give appropriate responses. Now that the sequence of the human genome is complete, it is important to assign functions to each gene and to identify the corresponding proteins that control key cellular functions. White and colleagues pioneered the development of microscopy-based methods for the visualization and timelapse measurement of biological processes in single living cells. We have used natural light-emitting proteins from fireflies, jelly fish and fluorescent corals. Synthesis (expression) of these proteins causes mammalian cells to become luminescent (light emitting in the dark) or fluorescent (change the colour of light). By placing the gene that codes for a luminescent protein next to a promoter that controls a gene of interest, we can use luminescence from living cells as a way of measuring when the gene of interest is normally switched on and off. Fluorescent proteins have also been used to genetically label proteins of interest, so that the movement of the protein can be visualized in a living cell. White and colleagues previously used timelapse fluorescence and luminescence microscopy coupled to computer simulations to investigate cell decision making. We discovered that a set of important signalling proteins, called NF-kappaB, move repeatedly into and out of the nucleus of the cell, suggesting that cells may use proteins as timers to encode complex messages (like Morse Code). This was a surprise since the original NF-kappaB protein, p65, was discovered 20 years ago and was thought to act as a simple switch that moves into the nucleus once to activate genes. Only timelapse measurements in single living cells were able to see this. The NF-kappaB system is widely recognised as crucial to the control of important cellular processes including both cell division and cell death. It is implicated as being involved in a variety of diseases, such as cancer and inflammatory disease. We will now develop a substantial systems biology project to study all of the components of this complex system. While the previous work has provided major insights, we now need a far broader range of integrated experimental tools to study it. Also the use of mathematical models to make computer predictions will be critical to help us to visualize how this system works. We will make accurate measurements of the (much larger) set of proteins that are involved in NF-kappaB signalling and the genes that are controlled by these signals. The (very experienced) project team includes bioinformaticians, cell biologists, computer scientists, mathematicians, molecular biologists, microscopists and protein chemists. The project will be managed in a structured and organized way, so that the mathematical modelling can be used to predict and design the biological experiments. A central team of experimental officers will be responsible for coordinating the experiments, data and model storage and communication of information between team members. We will study the numbers of molecules of each of the NF-kappaB proteins in the cell, their stability, chemical states and interactions with each other and with other proteins. We will also study in detail which genes that they bind to and control. We will also aim to understand how single protein molecules acting at single genes can act to control decisions of cell life and death. This multidisciplinary approach is essential in order to understand this complex system. A further aim of the project is to provide training for post-docs and students. In this respect, we will benefit from sponsorship of training courses and symposia by the instrumentation companies Carl Zeiss, Hamamatsu Photonics, Coherent and Nano Imaging Devices. The project will also benefit from ongoing collaborations with Genetix and AstraZeneca

Agriculture underpins European industry with an annual turnover of more than ¤1 trillion and is essential for our survival. As resources dwindle and world populations grow, our demands on agriculture will also increase. As climate changes in the coming decades, current trends suggest that global temperatures will rise. Not only is mean temperature set to change but weather systems are also becoming less predictable: an unprecedented frost this year resulted in a failure of the Californian citrus crop, costing the industry $450 million. The combination of increased demand on agriculture and the changes in global climate and weather extremes represent a major challenge for science in the 21st century. To meet this challenge, we need to know how plants both respond to and protect against temperature changes. The same issues apply to other environmental factors across all biological systems, therefore, understanding this is a major goal for experimental and theoretical scientists. In recent years reductionist science, where biological pathways are studied in isolation, has not identified plant temperature sensors. It also cannot address how temperature effects that cross the many, interacting pathways, which we now know are involved. We take a multi-disciplinary approach and focus our studies on one of the best characterised signalling networks in plants. We will combine expertise from biologists that specialise in molecular and cell biology, plant physiology and climate change; and theoreticians that specialise in statistical, mathematical and computer science approaches to analyse and model biological systems. To provide vital independent expertise and avenues for collaboration we have invited a panel of experts from industry and academia, to meet with us on a yearly basis. We will analyse how temperature influences the interlinked pathways of light, 24-hour clock and cold signalling. We conduct our studies in the model plant Arabidopsis as it offers several advantages: 1. we have already developed the most advanced mathematical model in plant signalling, for a section of our network; 2. our network pathways are already well defined, with many useful tools and resources in Arabidopsis; and 3. the pathways in plants of economic and ecological importance appear to be closely related, so our results can readily be translated to other species. To capture a meaningful view of how temperature-regulated molecular events translate to important physiological traits we will conduct our analysis at molecular, cellular and whole plant levels. Our first task will be to expand our model with the pre-existing knowledge for the rest of our network. We will measure the response of all our network components over a range of temperatures and integrate these data into our preliminary model. This, approach will locate the temperature-sensitive and -tolerant parts of the network in an unbiased fashion: the important point is that the temperature responses that matter will not be caused by single components, but by many acting together. We cannot understand this complexity without computer models. Our models will help inform our experiments, to home in on the molecular mechanisms that control the network's properties. Finally, we will test the role of important network components in controlling agriculturally and ecologically relevant traits in whole plants. In summary, this project will develop the most advanced signalling network model in plants, define network features that permit responsiveness and tolerance, and identify plant temperature sensors. Our work will address fundamental questions in biology and create the knowledge base required to meet the challenge to develop crops better able to withstand a range of climatic conditions. Our multidisciplinary collaboration will also provide training and extension of 'Systems Biology' approaches to universities with no current expertise and to our industrial collaborators.

Soft image sensors are expected to take vital roles in our future daily life. They can monitor the physiological information of our body to provide real-time, noninvasive medical diagnostics, as well as capture and share photos, videos via wireless communications. However, current image sensing electronics cannot be integrated easily into humans, because they are made of rigid semiconductor photodetectors and integrated with optical filters for colour discrimination. In addition, the use of filter creates additional requirements on the optical path difference, which confines the foldability and limits the resolution of the detector array. To overcome these technological limitations, filterless foldable photodetectors which only detect light within a specific wavelength have emerged as critical elements for building soft image sensors. Colloidal quantum dots, metal halide perovskite and organic photodetectors have shown excellent flexibility and detectivity. However, their broad light absorption means filters need to be added to make them specific to a certain colour of light. So far, the most successful filterless model is based on charge collection narrowing (CCN) photodiodes, which are semiconductor devices that convert the specific colour of light into an electrical current. However, since the narrowband response is delivered by controlling photogenerated charge collection efficiency, micrometres thickness junction is often required, which results in an array with a greater likelihood of interpixel cross-talk and frequency bandwidth limitations. It has been demonstrated that the junction thickness can be reduced by using high reflectivity cavities, but a number of challenges still remain. In this research, we aim to tackle these challenges to help find suitable semiconductors that use non-toxic elements and are able to efficiently detect light within a specific wavelength of interest at thicknesses as little as few hundred nanometres. If successful, we would be moving a step closer to an eco-friendly soft image sensor with the potential for many applications. Among all incarnations of solution-processed semiconductors, the recently discovered two-dimensionally (2D) Colloidal Quantum Wells (CQWs) are highly promising for soft image sensor applications, not only do they offer high colour purity with ultranarrow full-width at half-maximum (FWHM) but they also exhibit excellent compatibility with flexible electronics, such as unique stretching enhanced optical polarisation. Unlike colloidal quantum dots, CQW ensembles have no inhomogeneous broadening due to an atomically-precise definition of the short axis and is the reason why CQWs exhibit the narrowest ensemble absorption and emission spectrum of any solution-processed material reported to date. However, looming over much of this success is the fact that all the reported CQWs include toxic heavy metals (e.g., cadmium and lead), and little progress has been made on the fabrication of non-toxic CQWs or CQW narrowband photodetectors. This proposal is therefore designed to substantially address this challenge by using non-toxic mechanically stretchable 2D solution-processed CQWs for the fabrication of soft image sensors. This proposal starts from the growth and surface functionalisation of non-toxic CQWs followed by predictions of the new cavity and charge transport layers for fast CCN. The proposed work will consider the key factors limiting frequency bandwidth, and will demonstrate the inkjet printing of multi-coloured CCN-based photodiodes in a soft image sensor scenario. The high impact objective of this project is the demonstration of a CQWs image sensor which is stretchable and mechanically conformable. This proposal will be underpinned from the established compound semiconductor research expertise at Cardiff University, in close collaboration with Oxford, Cambridge and Bristol University, TCL Corporate Research, Huawei UK, Glaia, 99P Recycling and Hamamatsu UK.