The individual and network functions of cell surface receptors in plant stress responses

植物胁迫反应中细胞表面受体的个体和网络功能

• 批准号: RGPIN-2019-06395
• 负责人: Mott, Glenn
• 金额: $ 2.04万
• 依托单位: University of Toronto
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2019
• 资助国家: 加拿大
• 起止时间: 2019-01-01 至 2020-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=682872
• 关键词: individual; network; functions; cell; surface

One of the central goals of plant breeding is to produce disease-resistant crops without decreasing yield. A complete understanding of how plants regulate immunity and growth would allow for rationalization of this process. The long-term objective of my research program is to understand how plants use cell surface receptors to measure the environment and regulate energy expenditures to immunity and growth. Plants cannot move in order to avoid pathogenic attack or in search of improved environmental conditions. Instead, they have evolved to measure many aspects of their locale, including nutritional availability, environmental conditions, and pathogen presence. These disparate data streams are then integrated to appropriately guide energy expenditure to maximize survival and growth. Receptors belonging to the expanded leucine-rich repeat receptor kinase family (LRR-RKs) are known to play important roles in immunity and growth. While there is great interest in these proteins, most of the 225 LRR-RKs in the model plant Arabidopsis thaliana remain orphan receptors with no assigned function. ******This lack of knowledge presents an obvious obstacle to understanding how these receptors integrate information and regulate immunity and growth. The few characterized LRR-RKs are known to act as either direct ligand receptors, or to modulate signals in trans through physical interaction with the ligand receptors. We hypothesize that plants control immunity and growth through a signaling network governed by the formation of signaling-competent complexes via physical interactions between LRR-RKs.******To address this hypothesis and determine how this receptor network has evolved to function, we must first identify the biological function of the orphan LRR-RKs and then determine how these functions are integrated in the network. ******We will accomplish this by:*** Using several existing large datasets to predict novel biological function for orphan receptors.*** Experimentally validating these predictions and assigning biological function to orphan LRR-RKs and sub-networks.*** Mapping evolutionary data onto the network structure and combining that with functional information to understand how receptors and networks evolve and respond to stress.******Significance:***Fundamental biological processes such as immunity and growth are controlled by complex signaling networks rather than linear means. We now have approaches and datasets that allow us to interrogate these networks at a systems level and determine how these processes are controlled. An improved understanding of the underlying logic of these networks will allow designer production of improved crops through network manipulation. Our research program will also offer numerous training opportunities for HQP in laboratory and computational science, which will provide excellent preparation for a range of research fields and career paths.**

植物育种的中心目标之一是生产出不降低产量的抗病作物。对植物如何调节免疫和生长的全面了解将使这一过程合理化。我的研究计划的长期目标是了解植物如何利用细胞表面受体来测量环境和调节免疫和生长的能量消耗。植物不能为了躲避病原攻击或寻求改善的环境条件而移动。相反，他们已经进化到测量他们所在地区的许多方面，包括营养的可用性，环境条件和病原体的存在。然后将这些不同的数据流整合起来，适当地指导能量消耗，以最大限度地提高生存和生长。已知扩增的富亮氨酸重复受体激酶家族（LRR-RKs）的受体在免疫和生长中起重要作用。虽然人们对这些蛋白非常感兴趣，但模式植物拟南芥中的225个LRR-RKs中的大多数仍然是孤儿受体，没有指定的功能。******这种知识的缺乏给理解这些受体如何整合信息和调节免疫和生长带来了明显的障碍。已知少数具有特征的LRR-RKs要么直接充当配体受体，要么通过与配体受体的物理相互作用来调节信号。我们假设植物通过一个信号网络来控制免疫和生长，这个信号网络是通过LRR-RKs之间的物理相互作用形成的信号传导复合物来控制的。******为了解决这一假设并确定这种受体网络是如何进化的，我们必须首先确定孤儿LRR-RKs的生物学功能，然后确定这些功能如何整合到网络中。******我们将通过：***使用几个现有的大型数据集来预测孤儿受体的新生物学功能。***实验验证这些预测，并为孤儿LRR-RKs和子网络分配生物学功能。***将进化数据映射到网络结构上，并将其与功能信息相结合，以了解受体和网络如何进化并对压力做出反应。******意义：***免疫和生长等基本生物过程是由复杂的信号网络而不是线性手段控制的。我们现在有了方法和数据集，使我们能够在系统层面上询问这些网络，并确定这些过程是如何控制的。对这些网络的潜在逻辑的更好理解将允许通过网络操纵来设计生产改良作物。我们的研究项目还将为HQP在实验室和计算科学方面提供大量的培训机会，这将为一系列的研究领域和职业道路提供良好的准备