Protein engineering expands the effector recognition profile of a rice NLR immune receptor

  1. Juan Carlos De la Concepcion
  2. Marina Franceschetti
  3. Dan MacLean
  4. Ryohei Terauchi
  5. Sophien Kamoun
  6. Mark J Banfield  Is a corresponding author
  1. John Innes Centre, United Kingdom
  2. The Sainsbury Laboratory, United Kingdom
  3. Iwate Biotechnology Research Center, Japan

Abstract

Plant NLR receptors detect pathogen effectors and initiate an immune response. Since their discovery, NLRs have been the focus of protein engineering to improve disease resistance. However, this has proven challenging, in part due to their narrow response specificity. Previously, we revealed the structural basis of pathogen recognition by the integrated HMA of the rice NLR Pikp (Maqbool, Saitoh et al. 2015). Here, we used structure-guided engineering to expand the response profile of Pikp to variants of the rice blast pathogen effector AVR-Pik. A mutation located within an effector binding interface of the integrated Pikp-HMA domain increased the binding affinity for AVR-Pik variants in vitro and in vivo. This translates to an expanded cell death response to AVR-Pik variants previously unrecognized by Pikp in planta. Structures of the engineered Pikp-HMA in complex with AVR-Pik variants revealed the mechanism of expanded recognition. These results provide a proof-of-concept that protein engineering can improve the utility of plant NLR receptors where direct interaction between effectors and NLRs is established, particularly via integrated domains.

Data availability

Protein structures, and the data used to derive these, have been deposited at the Protein DataBank (PDB) with accession codes 6R8K (Pikp-HMANK-KE/AVR-PikD) and 6R8M (Pikp-HMANK-KE/AVR-PikE).

The following data sets were generated

Article and author information

Author details

  1. Juan Carlos De la Concepcion

    Department of Biological Chemistry, John Innes Centre, Norwich, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  2. Marina Franceschetti

    Department of Biological Chemistry, John Innes Centre, Norwich, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  3. Dan MacLean

    The Sainsbury Laboratory, Norwich, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  4. Ryohei Terauchi

    Division of Genomics and Breeding, Iwate Biotechnology Research Center, Iwate, Japan
    Competing interests
    The authors declare that no competing interests exist.
  5. Sophien Kamoun

    The Sainsbury Laboratory, Norwich, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-0290-0315
  6. Mark J Banfield

    Department of Biological Chemistry, John Innes Centre, Norwich, United Kingdom
    For correspondence
    Mark.banfield@jic.ac.uk
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-8921-3835

Funding

Biotechnology and Biological Sciences Research Council (BB/J004553)

  • Sophien Kamoun
  • Mark J Banfield

Biotechnology and Biological Sciences Research Council (BB/P012574)

  • Sophien Kamoun
  • Mark J Banfield

Biotechnology and Biological Sciences Research Council (BB/M02198X)

  • Marina Franceschetti
  • Sophien Kamoun
  • Mark J Banfield

H2020 European Research Council (743165)

  • Sophien Kamoun
  • Mark J Banfield

John Innes Foundation

  • Juan Carlos De la Concepcion
  • Marina Franceschetti
  • Mark J Banfield

Gatsby Charitable Foundation

  • Sophien Kamoun

Japan Society for the Promotion of Science (15H05779)

  • Ryohei Terauchi

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Copyright

© 2019, De la Concepcion et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

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  1. Juan Carlos De la Concepcion
  2. Marina Franceschetti
  3. Dan MacLean
  4. Ryohei Terauchi
  5. Sophien Kamoun
  6. Mark J Banfield
(2019)
Protein engineering expands the effector recognition profile of a rice NLR immune receptor
eLife 8:e47713.
https://doi.org/10.7554/eLife.47713

Share this article

https://doi.org/10.7554/eLife.47713

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