We are currently recruiting for the below project. Further information on how to apply can be found here. The deadline for applications is Sunday 30th April 2023. Please note this project is open to Home fee status students only.
Employing AI-guided approaches to discover and engineer plant disease resistance proteins
- Lead supervisor: Dr Tolga Bozkurt (Imperial College London)
- Co-supervisor: Dr Nikolai Windbichler (Imperial College London)
Plant diseases are responsible for up to 30% of global food crop losses and causing billions of dollars in agricultural trade losses each year. A sustainable way to combat pathogens is through genetic improvement of crops. However, the capacity of pathogens to adapt and evade the plant immune system has constrained resistance breeding.
Plants defend against parasites through specialized disease resistance proteins that are encoded as immune sensors. These receptors activate plant immunity upon sensing pathogen molecules. Yet, some pathogens evade plant disease resistance, limiting the use of these immune sensors in agriculture. Engineering of diseases resistance functions is an alternative strategy but has been limited by our superficial understanding of underlying mechanisms. Recent advances in Cryo-EM structures of plant immune receptors and the rapid development of protein structure prediction tools, such as AlphaFold2, have vastly increased our ability to design synthetic disease-resistant proteins. Here we propose an AI-guided synthetic biology approach to discover and engineer plant immune receptors with new disease resistance gene specificities. In collaboration with our industrial partners Resurrect Bio, we will establish a digital approach to generate libraries of ligand-receptor complexes from plant-pathogen genomes in order to create new disease resistance traits. We will then employ a hight-throughput screen, using transient gene expression in a model plant species, to identify compatible ligand-sensor pairs and improve them via further mutagenesis.
At the completion, we expect to establish an AI-guided pipeline to discover and design synthetic immune receptors that confer broad-spectrum pathogen resistance. We expect that our approach can augment current strategies to fight with plant pathogens including pesticide usage and timely in efficient resistance gene cloning methodologies.
This project will be based at Imperial College London and is supported by Resurrect Bio.