The goal of this project is to develop a detailed understanding of microbial metabolism through computational modelling and therefore to guide rational design of microbes (i.e., identification of gene knockouts, up/down-regulation targets) into cell factories as a sustainable alternative to petrochemical production routes for low-carbon production of value-added molecules, such as recombinant protein and human milk ingredients. Computational simulation of microbial metabolic activities combined with experimental validation studies will provide new insights into microbial systems by making reliable predictions of the flow of various chemical substances in cell metabolism, which will be able to direct the design of cells by regulating cell's energy and carbon flow towards the synthesis of molecules of interests. In turn this will lead to the development of a new computational tool for effective cell factory design that maximises microbes' production performance and accelerates their deployment in biomanufacturing industry for the transition to a biological economy. Important outcomes of the project include not only new knowledge and understanding of microbial systems but also the development of a set of bioinformatics tools available for studying cell physiology and designing productive microbial systems for engineering biology applications.

The UK has a legally binding target of 'net zero' greenhouse gas (GHG) emissions for 2050 (Scotland, 2045) and the Food and Drink sector has a vitally important role to play in helping to achieve this. This must be done while also improving nutrition, protection of ecosystems, reduced risks to soil, water and air quality. Delivery against these ambitious targets will require a range of measures to be adopted across the agri-food supply chain - not just primary producers but also processors, retailers and ultimately consumers. Over the last few decades rapid advances in processes to collect, monitor, disclose, and disseminate information (broadly classified under the concept of 'transparency') have contributed towards the development of entirely new modes of environmental monitoring and governance for supply chains. Unfortunately, existing approaches often suffer from limitations in terms of collection and dissemination of data; over-simplification of supply chains; power dynamics influencing information inclusion/exclusion decisions; and potentially perverse outcomes regarding how the information is used, by whom and to what effect. Given these issues, we need to consider how best to capture information about supply chains in order to document existing sustainability practices in sufficient detail; this is necessary to not only support monitoring and reporting needs of all stakeholders, but also to promote additional pro-environmental behaviours and even re-configuration of the supply chain. Our vision is built around an actionable information ecosystem whose purpose is to deliver transparent sustainability - realised via three pillars that we refer to as: SEE-SHARE-ACT. The first of these encompasses the role of sensors and carbon reporting tools in capturing data about agri-food processes (SEE); the second is a trusted digital platform able to manage sustainability data and report it across supply chain actors(SHARE); the third is the use of data-analytics and machine learning to support decision-making and action (ACT). But what would a trusted infrastructure for transparent sustainability look like, and how would it be framed by (and operate within) its wider environmental, social and economic context? Also - how would such a framework go beyond simply documenting the elements of a supply chain (actors, processes, inputs, outputs) to enable a holistic approach to monitoring, pro-environmental decision-making and action? We have assembled an interdisciplinary team of academics and user organisations spanning the livestock, soft-fruit and brewing sectors to investigate transparent sustainability. Together we will explore the following questions: What datasets, indicators and decision-making processes are relevant to the different actors participating in supply chains to realize sustainable food futures (in the DE)? How do we formulate appropriate vocabularies with which to characterise sustainability practices, their context and rationale, and facilitate data capture and integration? Can we realize a provenance-based sustainability solution for supply chains, operating across a range of technologies and organisational boundaries, that is trusted and able to facilitate pro-environmental decision-making and action? How do we exploit sustainability data assets and ML/AI technologies to inform decision making towards net-zero, resulting in demonstrable changes to practice and behaviour? Answers to these (and the many other questions that will certainly emerge) will lead us to develop prototype solutions that will be evaluated with project partners. Our ambition is to create a means by which farmers and other food and drink supply chain stakeholders can create a more sustainable economy built upon trusted data regarding the lifecycle history of products for enhanced environmental and product safety in (therefore more resilient) food supply chains.

The Ocean-REFuel project brings together a multidisciplinary, world-leading team of researchers to consider at a fundamental level a whole-energy system to maximise ocean renewable energy (Offshore wind and Marine Renewable Energy) potential for conversion to zero carbon fuels. The project has transformative ambition addressing a number of big questions concerning our Energy future: How to maximise ocean energy potential in a safe, affordable, sustainable and environmentally sensitive manner? How to alleviate the intermittency of the ocean renewable energy resource? How ocean renewable energy can support renewable heat, industrial and transport demands through vectors other than electricity? How ocean renewable energy can support local, national and international whole energy systems? Ocean-REFuel is a large project integrating upstream, transportation and storage to end use cases which will over an extended period of time address these questions in an innovative manner developing an understanding of the multiple criteria involved and their interactions.