A clinical trial run by an established UK company has identified two natural plant molecules that inhibit skin inflammation. Unfortunately, the amount of these molecules from the source plant is very low and therefore extraction from the source plant is not feasible on an industrial scale. A potential solution to this problem is to use cultured plant cells, which can been grown on a large scale in multi-tonne bioreactors and optimised for the production of these target plant natural products. Significantly, by employing non-GM genetic approaches, the yield of these target molecules will be significantly increased in these cultured plant cells. This approach will also enable new insights into the biochemical regulation of these molecules within the source plant, potentially leading to further improvements in yield. The target natural products isolated from the generated plant cell lines will also be tested and compared to the same molecules extracted from the source plant in a large number of biomedical-based assays. It is anticipated this work will show the molecules produced from the generated plant cell lines are functionally equivalent to those extracted from the source plant. Once confirmed, and beyond the scale of this particular research project, the company will scale-up the growth of the generated plant cells and isolate the target molecules for their introduction into commercial products.

The recent advances in high through-put data generation for DNA/RNA, proteins and metabolites has resulted in a paradigm shift in how we seek to answer some of the fundamental questions of biology. Over the past decade, significant amounts of these large data sets encompassing resident microbial communities (microbiome), specific host responses and environmental conditions have been generated. To date the integration and exploitation of these complex datasets in a structured way has been highly problematic. However recent advancements in in-silico methodologies can for the first time help to unlock the full potential of these data, facilitating improved understanding of and discovery of novel interventions for host-microbiome interactions. With the advent of these technologies it has become apparent that interactions between environmental, host and microbial factors give rise to the various changes in skin homeostasis that result in cosmetic conditions such as dry skin and dandruff. Dandruff and dry skin are widespread conditions impacting over 50% of the world's population affecting quality of life including self/body confidence and their treatment is the basis of a sector worth over 10bn Euros annually. In this study, in collaboration with our industrial partners, Unilever, we will investigate the physiological changes of normal, dry skin and dandruff through unique integration of computational biology and modelling with microbiology. We will develop a computational and experimental platform for skin host-microbiome interactions to reveal the microbial mechanisms involved in different skin states. Using this approach, we will identify and evaluate new therapeutic targets as well as reveal the underlying physiological events in skin homeostasis. Using a combination of skin samples collected by tape strips from normal, dry skin and dandruff, as well as data generated from reconstituted skin models and keratinocyte monolayers, we will generate data that accurately describes skin-microbe interactions. we will also identify the key species and strains of Malassezia, Staphylococcus and Cutibacterium associated with different skin states. In parallel by using the available multi-omics data from Unilever and the public domain, we will generate computational models for microbes and host skin tissue and cells. Having both in-silico and in-vitro set ups, we will investigate the impact of key metabolites and anti-metabolites on the relationship between the skin and key microbes and microbial communities. Finally, we will explore the impact of key host factors, such as cytokines (e.g. IL-36, IL-1, IL-17, IL-20 family) and antimicrobial peptides (e.g. beta-defensins, S100, LL-37) on the resident microbial communities. We will then categorize these therapies based on their mode of action on skin-microbiomes interactions. The new therapeutic targets generated and validated through this combination of both computational and experimental techniques can then be tested for host toxicity and efficacy. This cutting-edge integrative platform could be easily extended to identify new targets or drugs for different microbial constituents in human body, their association with a range of hosts and pathologies. As such it will delineate an entirely novel approach to investigating host-microbiome interactions that will have broad applicability across a wide range of sectors, including medical, veterinary, cosmetic and agricultural.

A wide range of household products as diverse as foodstuffs, cleaning materials and personal care products, rely on the ability to modify starting materials on an industrial scale to generate products with the desired properties. One key requirement in many cases is the introduction of charged groups, to bestow the desired characteristics such as the ability to gel, to bind other materials or to behave as detergents. This can often be achieved by the addition of charged groups and one key way to do this is to add a sulfate group. The problem is that this is done currently using toxic and environmentally damaging chemicals. The global market for such household products is huge and growing, for example, for personal care products is $ 7.35 Bn with annual growth of 7%. Our industrial collaborator, Unilever, with whom we have a long and well-established working relationship, is a major global player, with around 50% of the market share. Consumer sensitivity to environmental concerns, particularly with existing petroleum-based products and the use of harsh chemicals, arising from their resistance to biological degradation, the generation of greenhouse gases and other environmental issues during their production or disposal, has culminated in commercial pressure to develop sustainable alternatives. The current method of achieving sulfation industrially, involving aggressive chemicals which show poor selectivity and are environmentally damaging, needs to be replaced with a one employing renewable resources without damaging the environment. Together with Unilever, we aim to develop methods by which sulfation can be achieved using enzymes, thereby avoiding these problems. The route we propose - engineering enzymes to carry out this modification - offers both better control of the process and, crucially, enables environmentally responsible production of biodegradable products and waste. Until now, the application of enzymes to these areas has been hindered by the problems of readily detecting the modifications that have been made and, owing to the cost of some of the materials involved, also of developing a commercially feasible method of adding sulfate groups. Now, however, as a result the combination of preliminary work carried out by ourselves and Unilever, as well as other technological advances, both of these problems can be solved. This project will exploit these improved technologies, together with our established expertise in enzyme production to achieve two principal aims: (i) to assemble the technology (termed the high throughput enzyme-engineering platform) with which to produce and optimise enzymes that will be suitable for application to a wide range of enzyme-driven processes of industrial relevance and, (ii) to illustrate the use of this platform to select and optimise suitable enzymes, using a class of enzymes that can add sulfate groups to naturally-occurring and renewable starting materials such as complex sugars (polysaccharides) and lipids (glycolipids) from plants. The potential for industrial application of these sulfated products will then be assessed by Unilever, a major global company with a developed sustainability agenda that, in the future, will enable delivery of clean, renewable products.

Handling flexible materials is common in industrial, domestic and retail applications, e.g., evaluating new fabric products in the fashion industry, sorting clothes at home and replenishing shelves in a clothing store. Such tasks have been highly dependent on human labour and are still challenging for autonomous systems due to the complex dynamics of flexible materials. This proposal aims to develop a new visuo-tactile integration mechanism for estimating the dynamic states and properties of flexible materials while they are being manipulated by robot hands. This technique offers the potential to revolutionise the autonomous systems for handling flexible materials, allowing inclusion of their automated handling in larger automated production processes and process management systems. While the initial system to be developed in this work is for handling the textiles, the same technology would have the potential to be applied in handling other flexible materials including fragile products in the food industry, flexible objects in manufacturing and hazardous materials in healthcare.

Bio-based processes will make a major contribution to solving the challenges faced by a global society in the 21st century, including those associated with environmental sustainability. The employment of biocatalysts in industrial processes is expected to boost the sustainable production of chemicals, materials and fuels from renewable resources. We are collaborating with Unilever, Ingenza and Diageo to ensure the translation of academic research into a novel biological platform for the sustainable production of scientifically improved enzymes, bio-based chemicals and other biomaterials by exploiting new technologies. This disruptive innovation will lead to the development of unique and sustainable new products, derived from wastes and by-products, and demonstration of their cost-efficient and energy-saving production using novel biomanufacturing technologies.