Discovery of pathogen virulence and plant defense mechanisms by proximity labelling

Szymansky, Camille-Madeleine (2025) Discovery of pathogen virulence and plant defense mechanisms by proximity labelling. Doctoral thesis, University of East Anglia.

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Abstract

Plants detect pathogens through nucleotide-binding leucine-rich repeat (NLR) immune receptors, which activate effector-triggered immunity (ETI) after recognizing pathogen effectors. NLRs are classified into TIR NLRs (TNL), coiled-coil NLRs (CNL), and RPW8-like NLRs (RNL), and can function independently or in pairs, specializing in sensing pathogen effectors (sensor NLRs) or activating immune signalling (executor/helper NLRs). TNLs rely on EDS1, SAG101, and PAD4 for immune response activation, with the helper RNLs NRG1 and ADR1. In Solanaceous plants, many sensor CNLs depend on NRCs for immune signalling. Thus, plant immune responses involve complex protein-protein interactions (PPIs) in pathogen recognition and defense activation. This study aimed to explore these interactions using TurboID-based proximity labelling, which offers higher sensitivity for identifying PPIs compared to traditional approaches.

The first part of this work optimized TurboID for capturing effectors that interact with TurboID-tagged host proteins during native infection (Chapter 3). This knowledge was then applied to capture two previously reported Phytophthora infestans effectors, AVRamr1 and AVRamr3, recognized by the sensor CNLs Rpi-amr1 and Rpi-amr3 from Solanum americanum, respectively (Chapter 4). Additionally, we captured Albugo candida CCG effectors recognized by the sensor TNL WRR4A from Arabidopsis thaliana, identifying two novel effectors, CCG14 and CCG41, which had not been previously reported (Chapter 4). A. candida is particularly effective at suppressing TNL-mediate immunity. Therefore, we tested TurboID's ability to capture effectors targeting EDS1 signalling hubs downstream of TNLs, identifying CCG82, which may interfere with the EDS1-PAD4-ADR1 complex (Chapter 5). Lastly, TurboID captured the transient interaction between sensor CNLs and helper NRCs, shedding light on their dynamic communication (Chapter 6).

This work demonstrates TurboID's utility in enhancing our understanding of plant-pathogen interactions and establishes a foundation for future effector discovery.

Item Type:	Thesis (Doctoral)
Faculty \ School:	Faculty of Science > School of Biological Sciences
Depositing User:	Chris White
Date Deposited:	07 Jul 2025 10:12
Last Modified:	07 Jul 2025 10:12
URI:	https://ueaeprints.uea.ac.uk/id/eprint/99843
DOI:

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