Research

Our laboratory is dedicated to developing innovative technologies—including translational control, targeted protein-condensate degradation, and genetically modified endophyte—integrated with artificial intelligence to investigate the synergistic interactions among plant immune strategies, disease tolerance and resistance. Our work is guided by two central biological frameworks: the Bio-triangle relationship, which examines the dynamic interactions among plants, pathogens, and endophytes; and the Trait-triangle relationship, which focuses on balancing immunity, yield, and quality to address the global need for healthier and more productive crops. By uncovering the molecular logic behind these interactions, we aim to engineer crops with improved disease resistance and tolerance—offering sustainable solutions to the challenges facing modern agriculture.

In addition, we further expand the translational potential of plant systems across disciplinary boundaries by establishing plants as rapid development models and constructing a new paradigm of “plant model–driven human drug development and production.” Specifically, this approach includes: (1) developing plant models for the rapid iteration and validation of targeted protein-condensate degradation strategies, leveraging the high-throughput, low-cost, and genetically tractable nature of plant systems to enable systematic optimization of key degradation modules and subsequent translation of optimized strategies into human drug development pipelines; and (2) building upon strategy validation, utilizing translational control mechanisms to enhance the expression efficiency and stability of therapeutic proteins—including those related to targeted protein degradation—in plants, thereby establishing scalable plant-based production systems and promoting the integration of drug development and manufacturing.

Keywords

Immune strategies; Disease tolerance; Disease resistance; Growth–defense trade-offs; Disease symptoms; Plant immunity; Tissue damage control; Effector-triggered immunity; Hypersensitive cell death; Necrotrophic diseases; Rhizoctonia solani; Endoplasmic reticulum; ER–autophagy interplay; Membraneless organelles; Phase separation; Protein condensation; RNA regulatory elements; 5′-leader; Upstream open reading frames (uORFs); Translational control; Translation efficiency; Translational homeostasis; mRNA annotation; RNA-binding proteins; Ribosome profiling; TRIBE-mediated RNA editing; Rational engineering; Targeted protein-condensate degradation; Microbiome; Endophytes; Genetically modified endophytes; Human diseases

主要研究概述

我们实验室致力于开发新技术，包括翻译调控、蛋白团聚体靶向降解以及内生菌遗传赋能，并结合人工智能研究植物耐病性与抗病性两种免疫策略的协同作用。我们的研究围绕两个核心生物学框架展开：生物三角关系（Bio-triangle：plant-pathogen-endophyte），即植物、病原体与内生菌之间的动态相互作用；以及性状三角关系（Trait-triangle: defense-yield-quality），旨在在免疫力、产量和品质之间寻求平衡，以应对全球对更多、更健康粮食的需求。通过揭示这些相互作用背后的分子机制，我们的目标是设计出具备更强抗病性和耐病性的作物，从而为现代农业所面临的挑战提供可持续的解决方案。

此外，我们进一步拓展植物体系在跨界转化中的应用潜力，探索以植物作为快速研发模型，构建“植物模型驱动的人类药物开发与生产”新路径，具体包括：（1）构建用于蛋白质团聚体靶向降解策略快速迭代与验证的植物模型，依托植物体系高通量、低成本和易遗传操作的优势，实现关键降解模块的系统优化，并将优化策略转化至人类新药研发体系；（2）在策略验证基础上，基于翻译调控机制提升治疗性蛋白（包括靶向降解相关蛋白药物）在植物中的表达效率与稳定性，建立可规模化的植物生产体系，推动研发与生产体系的有机衔接。