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Poster

Session: Session 2 Presenting Authors at Posters (Odds)

P-193 - AI-led engineering of a sensor NLR immune receptor to target a conserved Fusarium effector

Wednesday, July 16, 2025
13:30 - 15:15  
Location: Confex Hall 3
Engineering plant-microbe traits

Plant immunity extensively relies on nucleotide-binding leucine-rich repeat receptors (NLRs) to detect pathogen-secreted effectors and trigger defence responses. To improve plant resistance, NLR bioengineering can be applied to help plant hosts defend against diverse and evolving pathogens. Previously, by modifying the integrated domain of Pik-1, a sensor NLR from rice, with either direct mutagenesis or domain swapping, paired NLRs Pik-1/Pik-2 were developed as a platform for novel resistance profiles. However, such methods largely depend on well-studied effectors and their known targets, which limits application of this platform. Recent advances in both protein prediction and de novo protein design offer opportunities for generating new-to-nature receptors conferring resistance to effectors with unknown targets. Here, we focused on a conserved Fusarium effector, Fossp17, and generated new-to-nature Fossp17 binders (Fobinders) using de novo protein design tools. We validated that Fossp17 and selected Fobinders interact in yeast, in planta and/or in vitro. Cell-death assays of Pik-1_Fobinder/Pik-2 with or without the effector in Nicotiana benthamiana plants displayed diverse phenotypes including autoactive cell death, repression of autoactivity and effector-dependent cell death. Our proof-of-concept study highlights the potential of using AI-led bioengineering methods to generate new-to-nature receptors to combat emerging plant pathogens and future plant disease outbreaks.