Every cell contains very large numbers of small molecules known as metabolites. These metabolites are the essential currency of the cell; they can be used to make larger molecules, generate energy and can be used as signalling compounds. There may be many hundreds, or even thousands, of metabolites within a single cell. Generally the composition of the metabolites reflects the status of the cells, for example if the cell is highly specialised it may make a large amount of one particular metabolite, or a range of other specific metabolites. Traditionally scientists have tended to examine small numbers of metabolites at a time, but we are now in a position to measure several hundred metabolites simultaneously. This information can be used as a fingerprint to give information about that cell, is it busy or resting for example. The information can also be used to see what happens if we alter the cell in some way, by, for example, adding a drug and seeing how the metabolites change. The metabolites in a cell are all interconnected by different pathways that are analogous to a map of the London underground in which the metabolites are represented by stations. By measuring all the metabolites simultaneously and seeing how they change over time we are better able to understand how individual metabolites (the stations) are interconnected. It also gives an excellent snapshot of the current status of the cell. This proposal is to buy equipment that will be used to measure a large number of metabolites simultaneously. This is a difficult process as many metabolites are structurally very similar even though they may have very different functions. The proposal is to use Gas Chromatography coupled with Mass Spectrometry. Essentially this separates molecules based upon their chemical properties and their size. It also gives information on how abundant different metabolites are. It is a specialised process that generates a very large amount of data. In order to handle such a large amount of data and to analyse a large number of samples much of the process is automated or handled by a computer. This same equipment can also be used to study any small molecules including pollutants, soil nutrients and complex volatile mixtures. We will use the equipment to address a range of problems in diverse areas of research including: 1. Study the relationship between metabolites in the single yeast cells and extrapolate from this relatively simple system to help understand how all cells work in complex multicellular organisms such as people or plants. 2. Stem cells offer the potential to cure many diseases that are currently untreatable, but in order to be able to generate enough of these cells much more needs to be known about how they behave and what regulates their unique properties. 3. Measuring metabolite changes in insulin-producing cells under different conditions will help us to understand the onset of diabetes and may help us to design better drugs to treat the condition. 4. Many new drugs are produced by growing cells in culture and in order to maximise production it is important to understand how producing these drugs affects the behaviour of the cultures. 5. Plant cell walls offer a huge resource that could potentially be harvested for use as a renewable source of energy and novel materials. To optimise production, more information is needed on how the compounds in the cell wall are made. 6. Nutrient availability and pollutants both limit plant productivity - by measuring these factors accurately it offers the potential to boost production. 7. The binding properties of olfactory receptors remain a mystery; we will be able to identify the natural ligands of single olfactory receptor neurons that express a single kind of olfactory receptor. This will have far-reaching implications for neurobiology and for the development of pest control strategies.

This project will unlock the potential of wheat grain heterogeneity. We will: 1) Develop a novel single seed phenotyping tool based on hyperspectral imaging technology (HSI) integrated with next generation machine learning 2) Explain the determinism of the variance of uniformity of single seed grain quality parameters and explore a broad range of both known, and novel and exotic wheat genotypes for previously undefinable unique single seed traits, this will allow breeders to target previously unavailable grain quality uniformity traits, as well as speed selection from segregating populations. 3) Deploy the single grain HSI technology as a novel molecular breeding tool by determining key genes controlling single grain quality uniformity traits and validating the candidate genes by developing lines with contrasting expressing of the novel genes which we will test in field experiments. 4) Demonstrate the application of the single seed phenotyping tool as a sorting technology at laboratory and pilot production scale for wheat. This will demonstrate the ultimate value of the approach by producing exemplar food products (bread, biscuit and malted wheat) with enhanced quality and health credentials and validating the findings through sensory and consumer insight testing. Ultimately this project offers the potential for breeders to significantly upgrade the UK wheat grain production, reduce the requirements to use imported wheat of millers, and enhance the nutritional quality and sensory quality traits of bread, biscuits and food products containing malted wheat for the consumer. The impact of this project will be very significant as sorting by hyperspectral classification for protein content would allow tighter segregation of the wheat supply chain into defined applications such as those that require lower protein (cakes, biscuits, pastry) from those that require higher protein with good protein quality and consistency and resulting good rheology (bread, pasta, high protein flour) and allow tighter adherence to supplier specifications in addition to reducing the need of imported wheat. At the highest capacities, a single sorting machine can process around 0.5 million tons per year, this indicates a very significant impact on the UK wheat industry with a relatively low-cost intervention, often in centralised milling sites. Furthermore, premium wheat with unique bread-making properties (e.g. elevated micronutrients, very high protein) and unique flavour potential through the malting process, will be sold with a price premium. If a further 20% of UK farmers growing bread-making wheat varieties were to achieve the grain protein market specification of 13% for the premium each year, it would be worth an extra £25 M per year to the UK agriculture sector.