Potato is a major food crop and crucial for global food security. However, potato production is threatened by the pathogen Phytophthora infestans, infamous for the Irish famine. Traditional resistance breeding using resistance genes has been ineffective due to the pathogen’s rapid adaptation. A recently discovered receptor family that recognizes conserved pathogen molecules promises to contribute to more durable resistance. This project aims to enhance these receptors using AI-based protein structure prediction. By studying the coevolution of potato and Phytophthora, the project seeks to bioengineer improved immune receptors, leading to broader and more effective resistance strategies.

Potato (Solanum tuberosum) is a crucial crop for global food security. However, potato production is seriously affected by the devastating ever-emerging oomycete Phytophthora infestans. The most sustainable strategy is breeding resistant potatoes by introducing immune receptors, which occur as nucleotide-binding leucine-rich repeat (NLR) proteins and pattern recognition receptors (PRRs). Resistance breeding has traditionally relied on NLRs only, however, these target fast-evolving avirulence genes and therefore are quickly defeated. In contrast, PRRs sense conserved patterns and thus offer better potential for durable resistance. However, they generally confer lower levels of resistance. This project aims to genetically enhance PRRs using artificial intelligence (AI)-based protein structure prediction tools. Specifically, we focus on our recently identified PRR, PERU, which recognizes transglutaminase-derived peptides (Pep13) of Phytophthora and exhibits extensive genetic diversity in wild potatoes.

First, we will study the co-evolutionary trajectory of PERU with Pep13 by exploring wild Solanum plants for recognition of Pep13 alleles. Second, we will combine obtained genetic variation with AlphaFold3-based structure predictions of the PERU - Pep13 binding interface, and mutate targeted amino acid residues in PERU to improve the Pep13 recognition. Our findings will be validated by functional assays in plants. Third, we will generate potato transformants expressing bioengineered PERU and determine the resistance by disease tests with P. infestans isolates. The concept of combining co-evolutionary insights with AI-based structure prediction tools offers an unprecedented opportunity to optimize plant immune receptors and improve host plant resistance.