Low molecular weight thiol molecules play an important role in antibiotic drug resistance. There are many enzymes inside cells which facilitate the reaction of these thiol molecules with antibiotics and their subsequent detoxification and removal from the cell. For this purpose, humans (and other mammals) use a thiol molecule called glutathione, which is made from amino acids building blocks. However, not all organisms are able to produce and utilise glutathione. Recently, we have discovered a novel class of carbohydrate-like biothiol, called Bacillithiol, amongst a number of microbial pathogens. These include bacteria associated with anthrax, food poisoning, urinary tract infections and MRSA. The aim of this project is to identify and characterise the ways in which these bacteria utilise bacillithiol to detoxify various antibiotics. Understanding the differences between glutathione and bacillithiol and their respective enzymes could provide exciting opportunities to design new drugs that will selectively target antibiotic detoxification mechanisms in drug resistant bacteria without affecting the glutathione processing enzymes found in humans.

Regenerative medicine (RM) is a convergence of conventional pharmaceutical sciences, medical devices and surgical intervention employing novel cell and biomaterial based therapies. RM products replace or regenerate damaged or defective tissues such as skin, bone, and even more complex organs, to restore or establish normal function. They can also be used to improve drug testing and disease modelling. RM is an emerging industry with a unique opportunity to contribute to the health and wealth of the UK. It is a high value science-based manufacturing industry whose products will reduce the economic and social impact of an aging population and increasing chronic disease.The clinical and product opportunities for RM have become clear and a broad portfolio of products have now entered the translational pipeline from the science bench to commercialisation and clinical application. The primary current focus for firms introducing these products is first in man studies; however, success at this stage is followed by a requirement for a rapid expansion of delivery capability - the 'one-to-many' translation process. This demands increasing attention to regulatory pathways, product reimbursement and refinement of the business model, a point emphasised by recent regulatory decisions demanding more clarity in the criteria that define product performance, and regulator initiatives to improve control of manufacturing quality. The IMRC will reduce the attrition of businesses at this critical point in product development through an industry facing portfolio of business driven research activities focussed on these translational challenges. The IMRC will consist of a platform activity and two related research themes. The platform activity will incorporate studies designed to influence public policy, regulation and the value system; to explore highly speculative and high value ideas (particularly clinically driven studies); and manufacturing-led feasibility and pilot studies using state of the art production platforms and control. The research themes will focus on areas identified as particular bottlenecks in RM product translation. The first theme will explore the delivery, manufacturing and supply processes i.e. the end to end production of an RM product. Specifically this theme will explore using novel pharmaceutical technology to control the packaged environment of a living RM product during shipping, and the design of a modular solution for manufacturing different cell based therapies to the required quality in a clinical setting. The second research theme will apply quality by design methods to characterise the quality of highly complex RM products incorporating cells and carrier materials. In particular it will consider optical methods for non-invasive process and product quality control and physicochemical methods for process monitoring.The IMRC will be proactively managed under the direction of a Board and Liaison Group consisting of leading industrialists to ensure that the Centre delivers maximum value to the requirements of the business model and assisting the growth of this emerging industry.

Tropical ecosystems are major sources of the greenhouse gases (GHGs) methane (CH4) and nitrous oxide (N2O), which are 25 and 298 times more effective than carbon dioxide (CO2), respectively, in trapping long-wave radiation in the atmosphere. Increases in CH4 and N2O concentrations since the start of the Industrial Revolution are responsible for over one-third of global warming, and future changes in the atmospheric budgets of these GHGs have implications for the Earth's climate and environmental conditions. N2O emissions, in particular, are projected to rise in the future due to agricultural expansion and enhanced atmospheric nitrogen deposition. Recent studies of the global budgets of CH4 and N2O using satellite imagery, atmospheric measurements, and modelling suggest that significantly more CH4 and N2O are released from the tropics than previously thought due to unaccounted sources of CH4 and N2O. It is critical for us to identify and characterise these 'missing' sources if we wish to understand the current contribution of the tropics to GHG budgets. Knowledge of these 'missing' sources is also necessary for predicting how tropical GHG emissions are likely to respond to future environmental or climatic change. One strong potential candidate for these 'missing' sources of CH4 and N2O are tropical uplands. Tropical uplands have been conspicuously absent from existing atmospheric budgets, because scientific attention has largely focused on CH4 and N2O emissions from lowland forests, savannas, or wetlands. Studies from tropical uplands suggest that they are potentially large sources of CH4 and N2O, with emissions that are equal to or greater than those from lowland environments. Upland rainforests in Puerto Rico, for example, emit more CH4 than lowland forests, with emission rates that are on par with northern wetlands, the largest natural sources of CH4 worldwide. To address these gaps in knowledge, we will conduct a comprehensive study of CH4 and N2O cycling in the Peruvian Andes, using a mixture of field measurements, controlled environment studies, and mathematical modelling. Specifically, we will: 1. Investigate how CH4 and N2O fluxes vary in space and time along an environmental gradient that spans 3000 m of altitude, from lowland rainforest to upper montane rainforest. 2. Explore how key environmental variables (e.g., plant productivity, climate, soil moisture, carbon and nitrogen availability, oxygen) influence CH4 and N2O emissions. 3. Determine if existing mathematical models are able to simulate CH4 and N2O emissions from tropical ecosystems, adapting these models as necessary to better simulate field observations. 4. Determine if GHG emissions from the Andes are able to account for some of the 'missing' tropical sources of CH4 and N2O by extrapolating our field observations to the regional scale using a combination of mathematical modelling, satellite imagery, and land cover databases (i.e., GIS). The proposed research will greatly advance our understanding of CH4 and N2O emissions for an important but understudied region, and will help us determine the relative contribution of Andean ecosystems to the CH4 and N2O budgets for South America. Knowledge of the emission rates and environmental controls on CH4 and N2O fluxes from upland Andean ecosystems will also help us evaluate whether other tropical uplands are likely to be sources of CH4 and N2O, and assess their potential contributions to the global atmospheric budgets of CH4 and N2O. Lastly, the development and adaptation of mathematical models that accurately simulate tropical CH4 and N2O fluxes will allow us to predict the likely response of tropical uplands to future environmental or climatic change.

Tropical ecosystems are major sources of the greenhouse gases (GHGs) methane (CH4) and nitrous oxide (N2O), which are 25 and 298 times more effective than carbon dioxide (CO2), respectively, in trapping long-wave radiation in the atmosphere. Increases in CH4 and N2O concentrations since the start of the Industrial Revolution are responsible for over one-third of global warming, and future changes in the atmospheric budgets of these GHGs have implications for the Earth's climate and environmental conditions. N2O emissions, in particular, are projected to rise in the future due to agricultural expansion and enhanced atmospheric nitrogen deposition. Recent studies of the global budgets of CH4 and N2O using satellite imagery, atmospheric measurements, and modelling suggest that significantly more CH4 and N2O are released from the tropics than previously thought due to unaccounted sources of CH4 and N2O. It is critical for us to identify and characterise these 'missing' sources if we wish to understand the current contribution of the tropics to GHG budgets. Knowledge of these 'missing' sources is also necessary for predicting how tropical GHG emissions are likely to respond to future environmental or climatic change. One strong potential candidate for these 'missing' sources of CH4 and N2O are tropical uplands. Tropical uplands have been conspicuously absent from existing atmospheric budgets, because scientific attention has largely focused on CH4 and N2O emissions from lowland forests, savannas, or wetlands. Studies from tropical uplands suggest that they are potentially large sources of CH4 and N2O, with emissions that are equal to or greater than those from lowland environments. Upland rainforests in Puerto Rico, for example, emit more CH4 than lowland forests, with emission rates that are on par with northern wetlands, the largest natural sources of CH4 worldwide. To address these gaps in knowledge, we will conduct a comprehensive study of CH4 and N2O cycling in the Peruvian Andes, using a mixture of field measurements, controlled environment studies, and mathematical modelling. Specifically, we will: 1. Investigate how CH4 and N2O fluxes vary in space and time along an environmental gradient that spans 3000 m of altitude, from lowland rainforest to upper montane rainforest. 2. Explore how key environmental variables (e.g., plant productivity, climate, soil moisture, carbon and nitrogen availability, oxygen) influence CH4 and N2O emissions. 3. Determine if existing mathematical models are able to simulate CH4 and N2O emissions from tropical ecosystems, adapting these models as necessary to better simulate field observations. 4. Determine if GHG emissions from the Andes are able to account for some of the 'missing' tropical sources of CH4 and N2O by extrapolating our field observations to the regional scale using a combination of mathematical modelling, satellite imagery, and land cover databases (i.e., GIS). The proposed research will greatly advance our understanding of CH4 and N2O emissions for an important but understudied region, and will help us determine the relative contribution of Andean ecosystems to the CH4 and N2O budgets for South America. Knowledge of the emission rates and environmental controls on CH4 and N2O fluxes from upland Andean ecosystems will also help us evaluate whether other tropical uplands are likely to be sources of CH4 and N2O, and assess their potential contributions to the global atmospheric budgets of CH4 and N2O. Lastly, the development and adaptation of mathematical models that accurately simulate tropical CH4 and N2O fluxes will allow us to predict the likely response of tropical uplands to future environmental or climatic change.

What is the relationship between the composition of an ecological community and its ecosystem function? How do changes in community composition affect carbon and nutrient cycling? How does a shift in ecosystem productivity (e.g. through fertilization) feed through to changes in diversity? These are perhaps the most important questions in ecology day, in the context of direct human pressure on ecosystems and indirect pressure through global atmospheric change. Here we propose to collect the data and develop and evaluate a framework to advance these ideas, in the context of tree community composition of tropical forests. We take advantage of three powerful tools that our team of investigators and project partners have developed: (i) an elevation transect of study sites in the Andes-Amazon where tree community composition and dynamics have been described in detail; (ii) airborne hyperspectral and lidar data that have recently been collected over this same transect, that enable determination of forest structure and chemistry in unprecedented detail, and (iii) a theoretical framework that utilises plant traits to propose a mechanistic approach to scale from community composition to ecosystem function. We will add to these datasets by: 1. Conducting an extensive leaf and wood traits collection campaign for seven sites along this transect, and 2. Collecting data on nitrogen and phosphorus cycling. Then we will develop a 3D model of the forest canopy of each plot (based on forest tree census and lidar data) to: 3. Explore the relationship between leaf traits and tree level characteristics (gross primary production, wood production, above-ground net primary production and nutrient cycling) 4. Scale from individual trees to the whole plot ecosystem characteristics (productivity, wood production, nutrient cycling) Having developed this detailed framework for relating individual tree properties to plot-level function, we will try to simplify the system to see if ecosystem level properties can be derived from an understanding of the mean value and distribution of traits in a community. Finally, we will explore how well tree-level characteristics can be described by airborne hyperspectra and lidar, and thus explore whether it is possible to describe landscape level ecosystem functioning at the scale of thousands of hectares. We have assembled a team of leading UK and USA researchers, and have an opportunity to make major advances and novel contributions to these important questions. Ultimately, we seek to acquire a mechanistic understanding of the relationship between forest community assembly and ecosystem level processes. Achievement of this goal would represent a major advance in ecology, in developing a both a theoretical and empirical toolkit with which to reach this goal.