Protecting crops from disease is essential for ensuring high yields, global food security, and achieving net zero goals. Resurrect Bio is at the forefront of pioneering research into plant immunity, with the aim of developing an agile, rapid trait discovery platform for precision breeding. A key component of this groundbreaking research is testing the interaction between plants, pests, and pathogens. To achieve this, a robust plant disease interaction platform must be established to rigorously evaluate our resistance traits in a controlled environment. Scaling this research requires suitable laboratory space, and we have identified an ideal location within the world-class plant research cluster at Norwich Research Park. The benefits of precision breeding are extensive. Each year, plant diseases cost the global economy approximately £170 billion, with yield losses directly impacting farmers and local economies. Global food security is also at risk, as the UN projects that over 600 million people will still face hunger by 2030\. Precision breeding not only improves yields but also significantly reduces the need for agrichemicals, which are often polluting and derived from petrochemicals. This approach also supports the UK and other regions in achieving their net zero climate goals. In summary, our project aims to establish a scalable plant disease interaction laboratory within the renowned plant science cluster at Norwich Research Park. This platform will rigorously test productivity-enhancing traits, bringing our innovative biotechnology closer to market readiness.

Protecting crops from disease is essential to ensuring yield and global food security. A pivotal aspect of this is understanding the interaction between plants and their pests & pathogens, which traditionally includes many time-consuming manual processes. Our project targets one aspect of the research and development process and aims to significantly reduce the time required to quantify plant immune responses using Artificial Intelligence (AI). Central to our initiative is to develop and test an easy to use computational tool which can intelligently quantify the programmed cell death on plant leaves. It does this by training an off the shelf, AI-powered image analysis tool with images collected in-house and by our collaboration partner, Imperial College London. The tool will then be pitted against human evaluators and, if successful, can be taken forward to a commercially ready tool. To validate our tool, we are collaborating with a leading group in plant science at Imperial College London to both help train our tool and test it in a real world research context outside of our own lab. This validation is crucial not only for the future refinement of our tool but also to demonstrate that such a tool can be used to significantly reduce research time in both a commercial and academic environment. In summary, our project aims to discover whether AI can significantly decrease research activities and time to market by training an image analyses tool to detect Programmed Cell Death. If successful, this accessible tool could be used by plant scientists in both the private and academic sectors, giving researchers more time to concentrate on higher value tasks.

In modern agriculture, safeguarding crops from diseases is paramount to ensuring both consistent yield and global food security. A pivotal aspect of this is understanding the interactions between plants and their pests & pathogens, which traditionally has been a laborious process fraught with trial and error. Our project aims to bring a significant technological advance to this domain by employing cutting-edge artificial intelligence (AI) to expedite the process of identifying key protein interactions between plants and parasites. Central to our initiative is the development of a sophisticated computational tool designed to sift through vast datasets of plant and parasite proteins. By evaluating the likelihood of interaction between these proteins, we aim to pinpoint the most promising targets for further analyses in the laboratory. This tool is propelled by the power of AI, specifically leveraging the revolutionary protein-folding capabilities of OpenFold and Google DeepMind's AlphaFold2\. By customising OpenFold with our curated datasets, we anticipate a substantial leap in both predictive accuracy and computational efficiency in analysing plant-parasite protein interactions. The backbone of our tool is a proprietary pipeline that integrates established scientific tools to process and analyse a comprehensive in-house database of protein structures. This fusion of AI with rigorous computational biology aims to significantly outpace traditional methods, offering a more rapid and precise approach to identifying potential plant-parasite interactions. To validate the practical utility of our AI-driven tool, we plan to conduct an extensive series of laboratory experiments. The predictions made by our tool will be tested empirically to ascertain their accuracy and relevance. This validation is crucial not only for refining our tool but also for paving the way for its integration into the broader scientific and agricultural communities. In summary, our project represents an innovative melding of AI, computational biology, and empirical validation aimed at enhancing the efficiency and accuracy of plant-parasite interaction analysis. By propelling an AI-driven approach to this critical area of study, we aspire to significantly advance our understanding and control of plant diseases. This endeavour not only holds promise for accelerating research in plant pathology but also contributes to the broader goals of sustainable agriculture and food security, aligning with the pressing global need for more resilient and productive agricultural systems.

Resurrect Bio has developed a technique for improving the immune system of crops using gene editing. They plan to use this technique to create sugar beet lines that are resistant to an aphid that spreads virus yellows, which can cause crop yields to decrease by up to 50%. The project will consist of three parts: defining the aphid's virulence proteins, decrypting the sugar beet's immune hubs, and determining which virulence proteins from the aphid are subverting the crop's natural defense response. The success of the project will allow Resurrect Bio to identify the specific immune receptors needed to make sugar beet resistant to the aphid. Targeted editing of these genes by plant breeding companies would allow farmers to reduce the use of pesticides, whilst increasing the yield of their crops.