Principal Supervisor: Professor Murray Grant
Secondary Supervisor(s): Professor Vardis Ntoukakis
University of Registration: University of Warwick
BBSRC Research Themes:
Plant disease resistance (R) genes are widely deployed in plant breeding and confer protection against a vast array of plant pathogens. Unfortunately, R-gene mediated resistance is often overcome in the field as strong selective pressure drives pathogens to rapidly adapt and evolve sophisticated ways of avoiding detection. This is primarily achieved through a suite of host adapted “effectors”.
Plants initially perceive pathogens via surface receptors that recognise non-self. This is termed PTI (Pathogen associated molecular Pattern Triggered Immunity). Pathogen effectors both suppress PTI and reconfigure host cells to provide a favourable environment for pathogen multiplication. R proteins are primarily intracellular receptors which perceive these pathogen effectors to confer effector triggered immunity (ETI) by either direct interaction, or indirectly initiating the hypersensitive response (HR), a form of programmed cell death. R proteins come in two flavours dictated by whether they have a coiled-coil or TIR (Toll-like, Interleukin-1 receptor; TNL) N-terminal domain. Many of these “NLRs are termed “sensor” NLRs and rely on “Helper” NLRs (of the CNL class) to mediate signalling. For nearly 30 years following the discovery of plant disease resistance genes, our understanding of how activated R proteins function was fragmentary until structural biology gave us our first insights into how both classes of activated R proteins “work”. Briefly, CNLs for pentameric and TNLs tetrameric “resistosomes”. Moreover TNL resistosome formation results in TIR dimerization, and generation of NADase activity resulting in novel signalling nucleosides being generation.
While recent studies have shown PTI and ETI work synergistically, potentiating responses no one has yet explored cross-talk between TNLs and CNLs.
Using a unique combination of real time whole imaging approaches that capture temporal and spatial information on physiological changes during plant pathogen interactions elicited in the Arabidopsis thaliana – Pseudomonas syringae pathosystem. This system allows synchronous activation of ETI. Using this approach we have found that simultaneous delivery of combinations of CNLs or TNLs activating effectors lead to remarkable alterations (both synergistic and antagonistic depending on the effector combination) in these parameters which, impoertantly, faithfully report the ultimate output of an effective ETI interaction, the hypersensitive response (HR).
We hypothesise that we are modifying dynamics of resistosome formation by altering a “limited supply” of key components. Thus, we are in an ideal position to really dissect this process using our extensive collection of Arabidopsis mutants in the “helpers” (combinatorial across the classes) and specific R genes combined with P. syringae isolates designed to deliver different combinations of effectors in both wild type and mutant backgrounds.
You will be exposed to a range of technique including whole plant real time imaging (chlorophyll fluorescence and biophoton generation), RNA-seq, microbiology, CRISPR, genetically encoded reporters and targeted mass spectrometry (to report discriminant ETI compounds).
If you want to work at the cutting edge of plant immunity, are highly motivated and have a passion for plant molecular biology and imaging this project will allow you to develop a range of interdisciplinary skill sets for your future research career.
While this is a novel area and no publications currently exist on this subject (license to operate) please see references below for the current state of the field.
Contreras et al. 2023, EMBO Reports DOI 10.15252/embr.202357495
Chai et al. 2023 Current Opinion in Plant Biology DOI 10.1016/j.pbi.2022.102334
- Microbiology & plant pathology
- Plant Molecular Biology
- Targetted analytical chemistry (mass spectrometry)
- Genetically encoded reporter analysis & whole plant imaging
- Proteomics and RNA-seq
- Quantitative Image Analysis