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

Clicks: 515
ID: 47756
2019
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal
Emerging

Ranked #4 of 128 articles by views in eLife

Most read Least read

Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 128 in total.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Sign in to mint
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.
Reference Key
de-la-concepcion2019proteinelife Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors De la Concepcion, Juan Carlos;Franceschetti, Marina;MacLean, Dan;Terauchi, Ryohei;Kamoun, Sophien;Banfield, Mark J;
Journal eLife
Year 2019
DOI
10.7554/eLife.47713
URL
Keywords
E. coli plant biology molecular biophysics structural biology

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

Comments

No comments yet. Be the first to comment on this article.