Structural mechanism of heavy metal-associated integrated domain engineering of paired nucleotide-binding and leucine-rich repeat proteins in rice

Front Plant Sci. 2023 Jun 28:14:1187372. doi: 10.3389/fpls.2023.1187372. eCollection 2023.

Abstract

Plant nucleotide-binding and leucine-rich repeat (NLR) proteins are immune sensors that detect pathogen effectors and initiate a strong immune response. In many cases, single NLR proteins are sufficient for both effector recognition and signaling activation. These proteins possess a conserved architecture, including a C-terminal leucine-rich repeat (LRR) domain, a central nucleotide-binding (NB) domain, and a variable N-terminal domain. Nevertheless, many paired NLRs linked in a head-to-head configuration have now been identified. The ones carrying integrated domains (IDs) can recognize pathogen effector proteins by various modes; these are known as sensor NLR (sNLR) proteins. Structural and biochemical studies have provided insights into the molecular basis of heavy metal-associated IDs (HMA IDs) from paired NLRs in rice and revealed the co-evolution between pathogens and hosts by combining naturally occurring favorable interactions across diverse interfaces. Focusing on structural and molecular models, here we highlight advances in structure-guided engineering to expand and enhance the response profile of paired NLR-HMA IDs in rice to variants of the rice blast pathogen MAX-effectors (Magnaporthe oryzae AVRs and ToxB-like). These results demonstrate that the HMA IDs-based design of rice materials with broad and enhanced resistance profiles possesses great application potential but also face considerable challenges.

Keywords: HMA IDs; molecular structure; paired NLRs; protein engineering; rice.

Publication types

  • Review

Grants and funding

This work was supported by the Natural Science Foundation of China (31901870), the Major Science and Technology Project of Yunnan Province (202202AE090036), High-level Talents Introduction Plan of Yunnan Province-Young Talents Special Project, and Yunnan Chen xuewei Expert Workstation(202305AF150124).