Oil from seeds forms a major source of nutrition for humans and livestock. It also has many important industrial uses, among them providing an increasingly relevant source of renewable energy (bio-diesel). The rate of oil accumulation in developing seeds is governed predominantly by biosynthesis. However, a number of studies have reported that a significant amount of oil is also turned over during seed development. Blocking this turnover could potentially elevate oil levels by between 5 and 25%, depending on the species and growth conditions. Controlling oil breakdown in seeds requires knowledge of the molecular mechanism, which until recently was completely lacking. This process also occurs after seed germination where it plays a fundamentally important role in providing energy for early seedling growth. I have gained a new insight into the mechanism of oil breakdown by isolating mutants in the model oilseed plant Arabidopsis that are impaired in post-germinative growth. I have discovered that one of these mutants, called sugar-dependent1, has a defect in the enzyme triacylglycerol hydrolase, which catalyses the first step in oil breakdown. The rate of oil breakdown is dramatically slowed in this mutant and as a consequence the developing seeds accumulate significantly more oil. The goals of this proposal are (i) To study how SDP1 is regulated and establish whether oil breakdown can be inhibited during seed development and not following germination. This would allow oil yield to be enhanced with the minimum impact on seedling vigour. (ii) To identify additional structural and regulatory proteins that function with SDP1 to govern the rate of oil breakdown. Disruption of these proteins will be used to block oil breakdown completely and thereby maximize oil accumulation. (iii) To investigate the role of SDP1 in the crop species oilseed rape and determine if oil yield can also be increased by impairing oil turnover. Addressing these objectives will contribute greatly to our fundamental knowledge of the mechanism and regulation of lipolysis, which is major metabolic process that is essential for the life cycle of many plants. The work could also lead to the development of crop plants with a higher oil yield.

Currently, the manufacture of pharmaceuticals, agrochemicals and other fine chemicals relies heavily on synthetic chemical methods, which use deleterious solvents, reagents and catalysts as well as non-renewable petrochemical precursors, which have serious detrimental environmental impact. Consequently, alternative biotechnology based processes are sought for the more economic and environmentally sustainable manufacture of those chemicals that are essential to maintain human health and quality of life. Central to the development of industrial biotechnologies is the availability of new enzymes, with tailored properties, that can be used to catalyse the transformation of renewable precursors into the required products under environmentally benign conditions. To date, industrial applications of enzymes have relied on a limited number of established enzymes, which catalyse a narrow range of transformations. However, recent genome sequencing has led to the discovery of a wider range of enzymes from natural sources. In addition new directed evolution technologies allow the properties of enzymes and even the reactions they catalyse to be altered and optimised for specific processes. Recently we solved the first structure and determined the detailed mechanism of a decarboxylase enzyme (AMDase) that catalyses the loss of carbon dioxide (decarboxylation) from malonic acid derivatives to generate chiral carboxylic acids. In this project, we aim to use these structural and mechanistic insights to develop more powerful decarboxylase enzymes that can provide access to a much wider range of structurally diverse carboxylic acids, which are particularly common intermediates in production of pharmaceuticals, agrochemicals and other products. The new decarboxylase enzymes are also attractive because the substrates can be generated from malonic acid, a natural precursor derived from renewable sources (fermentation). The availability of chiral carboxylic acids, which are single enantiomers (one of two possible stereoisomers that are non-superimposable mirror images) is of critical importance particularly for pharmaceutical production. Typically, enzymes only produce one of the two possible enantiomers, which is problematic if the opposite enantiomer is required. We will therefore use directed evolution technologies to develop enzymes that are enantiocomplementary. In this way, one enzyme can be used to produce one enantiomer (left-handed molecule), whilst another enzyme can produce the opposite enantiomer (right-handed molecule). Along with our industrial partners at BASF, who are the world's largest chemical manufacturers, we will tailor the new enantiocomplementary decarboxylases for production of key pharmaceutical intermediates. This includes chiral carboxylic acids used to manufacture non-steroidal anti-inflammatory drugs (from the ibuprofen family), the antiplatelet agent clopidogrel (the world's second-best selling drug) and captopril which is used to treat cardiac conditions. The family of enzymes to which the decarboxylases belong are known to be promiscuous, and can catalyse a wider range of reactions than decarboxylations, including racemisations and isomerisations. We aim to further explore the promiscuity of this enzyme family, with a view to developing alternative reactions that would also be of industrial importance.

Fish oils have been historically associated with health-beneficial properties and over the last few years a large number of scientific studies have demonstrated the benefits of a diet rich in these oils. In particular, some of the fatty acids found in fish oils seem to play a role in preventing heart attacks and other circulatory problems. These fatty acids are the omega-3 long chain polyunsaturated fatty acids (abbreviated to omega-3 LC-PUFAs), and they are now widely viewed as vital constituents of human diet. As well as being able to play a role in preventing diseases, fish oil omega-3 LC-PUFAs are also very important in human growth and development. For example, breast milk contains these fatty acids, and it is for this reason formula (replacement) milks are now enriched in these fats. The primary source of omega-3 LC-PUFAs is fish oils, but unfortunately global fish stocks are now in severe decline (mainly due to decades of over-fishing). This not only represents an ecological crisis, but may also, in the future, severely hamper the availability of fish oils to maintain a healthy diet. Moreover, there are growing concerns about the contamination of current wild fish stocks with pollutants such as heavy metals, plasticizers and dioxins. Therefore, there is an urgent need to find a new sustainable source of these very important fatty acids. One approach that we are undertaking is to try and make fish oils in plants. This requires genetic engineering of a suitable plant (ideally an oilseed), because there are no known examples of higher plants which synthesise omega-3 LC-PUFAs. To carry out this work, the genes which direct the synthesis of omega-3 LC-PUFAs need to be introduced in a plant. These genes come from the tiny microbes (such as algae) which live in the ocean and synthesise omega-3 LC-PUFAs, so the project involves moving these genes into plants, to allow the synthesis of these important fatty acids in a clean and sustainable manner.

Current research in explosives detection focuses across key themes spanning the mode of signal transduction involved, including Optical, Electrical, Gravimetric and Calorimetric based solutions. Significant progress has been made in optical based detection systems and to date the most successful strategies are based upon solid state fluorescent materials and modulation of analyte interactions via electron transfer. With the exception of the conjugated polymers however, few materials have been incorporated or commercialised into device driven architectures. The future for fluorescence based sensors is in exploitable solid state technologies with enhanced sensitivity and selectivity. This proposal aims to combine the advantages of optical and electrical signal transduction to facilitate a synergistic optoelectronic sensor based upon bi-layer thin film photoconductor technology. Bi-layer heterojunctions play key roles in optoelectronic devices such as photovoltaics, organic light emitting diodes (OLEDS) and photoreceptors. The interface is responsible for creation and dissociation of photogenerated excitons into charge carriers that are transported to the electrodes via applied bias. Compared with chemiresistors and field effect transistors, separation of the processes of charge generation and charge transport into two different films in a heterojunction facilitates a more simplistic optimisation of the physical processes involved. Analyte detection via modulation of current output from lateral bi-layer photoconductors is possible using exciton generating layers whose photoluminescence efficiency is affected by local environment. Many potential organic fluorophores that could fulfil this role are however, poorly emissive in the solid-state from aggregation induced quenching effects and rational control of these unfavourable interactions is crucial for their future realisation in functional applications. Organic dyes and pigments are ubiquitous materials in photoconductive technologies such as xerography, upon which lateral bi-layer heterojunction sensors are based. They are effective in charge generation through careful manipulation of purity, crystallinity and morphology and as such make extremely attractive materials for the construction of bi-layer sensors. Furthermore, many dyes and pigments are amenable to organic functionalisation and crystal engineering, facilitating introduction of analyte specific recognition sites, tuneable absorption and controlled morphology to provide broadband sensor architecture. Thus, this proposal aims to develop a systematic understanding of the role of molecular design and crystal engineering on the solid state chemistry of photoluminescent dyes and pigments which can be exploited via the bi-layer approach. This aspect of the proposed research addresses several technical challenges in materials science and the fabrication of a device employing organic dyes and pigments, and metal oxides will require an in-depth understanding of their preparation, photochemistry and solid state properties. Devices based upon this structure offer significant advantages in explosives detection, providing an opportunity for high sensitivity, large dynamic range and selective target recognition with built in adaptability to changing threats. Additionally, this type of system would be non-invasive, portable and rugged, with few moving parts and the potential to offer a rapid analyte response mechanism that can be directly modulated into an electrical output.

Many important questions and challenges in process systems design, operation and control can be typically posed as nonlinear optimization problems. To date, most optimal decision making tools for such problems are mainly based on deterministic mathematical models, where all parameter values in the model are assumed to be known precisely. In practice, however, mathematical models are merely approximate descriptions of the real system, and parameters such as future demands, prices, equipment wearout and process conditions are subject to significant uncertainty. It has been frequently shown that disregarding such uncertainty can lead to severe performance losses, increased costs, and energy/environmental penalties. We propose to develop robust, local and global optimization methods for the efficient solution of such nonlinear optimization problems in the presence of uncertainties. Depending on their nature, uncertainties can be accounted for in a static/proactive or reactive way. Two important industrial applications will be investigated and the developed methods will be applied for the integrated design, optimization and control of process systems under uncertainty.