bioRxivPlant BiologyPreprint
Effector-centred proximity-dependent labelling enables the discovery of cell-surface immune receptors in plants
Nicat CebrailogluiD, Esranur BudakiD, Sergio Landeo VillanuevaiD, Christiaan R. ScholiD, Casper ter WaarbekiD, Kezia EvertsziD, Sjef A. BoereniD, MATTHIEU H. A. J. JOOSTENiD
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Abstract
Identifying plant disease resistance proteins remains challenging, particularly for cell-surface receptors that perceive apoplastic pathogen effectors through transient or indirect interactions. Here, we establish effector-centred proximity-dependent labelling using TurboID as a protein-level approach to identify immune receptors and guarded host targets in planta. We fused three apoplastic effectors, Avr2 and Avr4 from Fulvia fulva and XEG1 from Phytophthora sojae, to TurboID and transiently expressed these fusion proteins in leaves of Nicotiana benthamiana and tomato (Solanum lycopersicum). The fusions significantly biotinylate their matching receptors, including Cf-4 by Avr4-TurboID and Cf-2 by Avr2-TurboID, as well as the guarded virulence target of Avr2, the Rcr3 protease, demonstrating that both direct and indirect recognition systems can be captured. Application of this approach to XEG1 revealed SlEix1 as the functional ortholog of NbRXEG1. Functional assays and structural modelling support SlEix1 as a signalling-competent receptor contributing to XEG1-triggered immunity. Together with previous studies, these findings position the tomato EIX locus as a multi-effector immune hub encoding closely related receptor-like proteins with distinct ligand specificities. Collectively, this study establishes effector-TurboID-mediated proximity-dependent labelling as a versatile approach for identifying cell surface plant immune receptors and apoplastic virulence targets, providing a scalable route to accelerate resistance gene discovery in crop species.
- organism: plant (other)
- assay: proteomics
- research focus: cell type annotation
- research focus: host-pathogen & immune response
- research focus: protein structure prediction
- approach: experimental assay
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