# Precision Editing of NLRS Improves Effector Recognition for Enhanced Disease Resistance

## TL;DR

Scientists are improving plant immunity by precisely editing immune receptors to better recognize pathogens and boost disease resistance.

## Contribution

The paper introduces precision editing strategies for NLRs that enhance pathogen recognition while minimizing risks like autoimmunity.

## Key findings

- Mismatched pairing, domain swapping, and targeted mutagenesis improve NLR recognition of pathogens.
- Precision editing expands immune receptor breadth without causing autoimmunity or fitness penalties.
- Combining structural biology with AI tools offers new pathways for durable crop protection.

## Abstract

Plant pathogens pose a significant threat to global food security by causing up to 80% agricultural yield losses. Nucleotide‐binding, leucine‐rich repeat immune receptors (NLRs) were widely proved to protect plants from a wide array of pathogens evasion. Recent studies have shown significant progress in bioengineering NLRs to enhance plant immunity through improved pathogen recognition, investigation of immune evasion, and structural insights into NLR functions. However, bioengineering NLRs for enhanced plant immunity faces key challenges of maintaining specificity, addressing pathogen evolution, and minimizing autoactivity risks. Here, we synthesize recent advances in understanding NLR biology and highlight key bioengineering strategies, including mismatched pairs, domain swapping, and targeted mutagenesis, that leverage this knowledge to enhance disease resistance. The successful applications of NLRs precision editing strategies have also been demonstrated to improve resistance in various plants, showcasing their overall effectiveness. This review highlights promising avenues to strengthen plant immunity against pathogens, which have enormous potential for application in agriculture and breeding techniques.

Precision engineering of plant NLR immune receptors enables rational design of enhanced pathogen resistance through mismatched pairing, domain swapping, and targeted mutagenesis. These approaches achieve multi‐fold expansion in recognition breadth while minimizing autoimmunity risks and fitness penalties. Integration of structural biology with Artificial Intelligence (AI) design tools provides actionable pathways for developing durable, broad‐spectrum crop protection addressing global food security challenges.