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The structural repertoire of Fusarium oxysporum f. sp. lycopersici effectors revealed by experimental and computational studies.

Daniel S Yu | Megan A Outram | Ashley Smith | Carl L McCombe | Pravin B Khambalkar | Sharmin A Rima | Xizhe Sun | Lisong Ma | Daniel J Ericsson | David A Jones | Simon J Williams
eLife | 2024

Plant pathogens secrete proteins, known as effectors, that function in the apoplast or inside plant cells to promote virulence. Effector recognition by cell-surface or cytosolic receptors results in the activation of defence pathways and plant immunity. Despite their importance, our general understanding of fungal effector function and recognition by immunity receptors remains poor. One complication often associated with effectors is their high sequence diversity and lack of identifiable sequence motifs precluding prediction of structure or function. In recent years, several studies have demonstrated that fungal effectors can be grouped into structural classes, despite significant sequence variation and existence across taxonomic groups. Using protein X-ray crystallography, we identify a new structural class of effectors hidden within the secreted in xylem (SIX) effectors from Fusarium oxysporum f. sp. lycopersici (Fol). The recognised effectors Avr1 (SIX4) and Avr3 (SIX1) represent the founding members of the Fol dual-domain (FOLD) effector class, with members containing two distinct domains. Using AlphaFold2, we predicted the full SIX effector repertoire of Fol and show that SIX6 and SIX13 are also FOLD effectors, which we validated experimentally for SIX6. Based on structural prediction and comparisons, we show that FOLD effectors are present within three divisions of fungi and are expanded in pathogens and symbionts. Further structural comparisons demonstrate that Fol secretes effectors that adopt a limited number of structural folds during infection of tomato. This analysis also revealed a structural relationship between transcriptionally co-regulated effector pairs. We make use of the Avr1 structure to understand its recognition by the I receptor, which leads to disease resistance in tomato. This study represents an important advance in our understanding of Fol-tomato, and by extension plant-fungal interactions, which will assist in the development of novel control and engineering strategies to combat plant pathogens.

Pubmed ID: 38411527

Research resources used in this publication

None found

Antibodies used in this publication

None found

Associated grants

  • Agency: Australian Research Council,
    Id: DP200100388
  • Agency: Australian Research Council,
    Id: FT200100135
  • Agency: Australian Research Council,
    Id: DE170101165
  • Agency: Australian Institute of Nuclear Science and Engineering,
    Id: Postgraduate Research Award
  • Agency: Australian National University,
    Id: Future scheme
  • Agency: Australian Academy of Science,
    Id: Thomas Davies Grant
  • Agency: ICAR - National Agricultural Science Fund,
    Id: PhD International Fellowship

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This is a list of tools and resources that we have found mentioned in this publication.


CCP4 (tool)

RRID:SCR_007255

Portal for Macromolecular X-Ray Crystallography to produce and support an integrated suite of programs that allows researchers to determine macromolecular structures by X-ray crystallography, and other biophysical techniques. Used in the education and training of scientists in experimental structural biology for determination and analysis of protein structure.

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Joint Center for Structural Genomics (tool)

RRID:SCR_008251

The JCSG is a multi-institutional consortium that aims to explore the expanding protein universe to find new challenges and opportunities to significantly contribute to new biology, chemistry and medicine through development of HT approaches to structural genomics. The mission of JCSG is to to operate a robust HT protein structure determination pipeline as a large-scale production center for PSI-2. A major goal is to ensure that innovative high-throughput approaches are developed that advance not only structural genomics, but also structural biology in general, via investigation of large numbers of high-value structures that populate protein fold and family space and by increasing the efficiency of structure determination at substantially reduced cost. The JCSG centralizes each core activity into single dedicated sites, each handling distinct, but interconnected objectives. This unique approach allows each specialized group to focus on its own area of expertise and provides well-defined interfaces among the groups. In addition, this approach addresses the requirements for the scalability needed to process large numbers of targets at a greatly reduced cost per target. JCSG production groups are: - Administrative Core - Bioinformatics Core - Crystallomics Core - Structure Determination Core - NMR Core JCSG is deeply committed to the development of new technologies that facilitate high throughput structural genomics. The areas of development include hardware, software, new experimental methods, and adaptation of existing technologies to advance genome research. In the hardware arena, their commitment is to the development of technologies that accelerate structure solution by increasing throughput rates at every stage of the production pipeline. Therefore, one major area of hardware development has been the implementation of robotics. In the software arena, they have developed enterprise resource software that track success, failures, and sample histories from target selection to PDB deposition, annotation and target management tools, and helper applications aimed at facilitating and automating multiple steps in the pipeline. Sponsors: The Joint Center for Structural Genomics is funded by the National Institute of General Medical Sciences (NIGMS), as part of the second phase of the Protein Structure Initiative (PSI) of the National Institutes of Health (U54 GM074898).

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New England Biolabs (tool)

RRID:SCR_013517

An Antibody supplier

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Coot (tool)

RRID:SCR_014222

Software for macromolecular model building, model completion and validation, and protein modelling using X-ray data. Coot displays maps and models and allows model manipulations such as idealization, rigid-body fitting, ligand search, Ramachandran plots, non-crystallographic symmetry and more. Source code is available.

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Phenix (tool)

RRID:SCR_014224

A Python-based software suite for the automated determination of molecular structures using X-ray crystallography and other methods. Phenix includes programs for assessing data quality, experimental phasing, molecular replacement, model building, structure refinement, and validation. It also includes tools for reflection data and creating maps and models. Phenix can also be used for neutron crystallography. Tutorials and examples are available in the documentation tab.

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AlphaFold Protein Structure Database (tool)

RRID:SCR_023662

Database of protein structure predictions by AlphaFold that are freely and openly available to global scientific community. Included are nearly all catalogued proteins known to science. Provides programmatic access to and interactive visualization of predicted atomic coordinates, per residue and pairwise model confidence estimates and predicted aligned errors.

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