Evolution of the plant immune signaling network

植物免疫信号网络的进化

• 批准号: 1645460
• 负责人: Fumiaki Katagiri
• 金额: $ 91.37万
• 依托单位: University of Minnesota-Twin Cities
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-04-15 至 2023-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1645460&HistoricalAwards=false
• 关键词: Evolution; plant; immune; signaling; network

Upon recognition of pathogen attack, plants turn on immune responses to defend themselves from pathogens. The immune signaling network controls the immune response. This research is aimed at answering two questions. (1) How did the sophisticated immune signaling network in contemporary land plants arise during their evolution? (2) How much diversity in the signaling network exists among different flowering plants? Question (2) will be answered by comparing in detail how the signaling network operates in three diverse flowering plant species, tomato, rice, and the model plant Arabidopsis. The results of the research will provide an example of how sophisticated biological systems can evolve. They will also provide ideas about how the plant immune signaling network can be engineered to improve disease resistance in crops. As outreach, a mobile conservatory will be developed and used to teach 3rd grade students about how plants adapt to their environments.The immune signaling network in the model plant Arabidopsis is highly resilient against pathogen attack on its components. This research will investigate when during the evolution of land plants such a highly resilient signaling network was acquired. This will be achieved by interrogating when specific immune-related subfamilies neofunctionalized within larger protein families using phylogenetic analysis of protein families of diverse land plant species. The subfamily analysis method will be automated and applied at the genome scale to investigate the times at which the networks controlling various other biological processes evolved. Key network components are generally conserved among angiosperms. However, it has never been investigated whether the state of a network (the set of network parameters) is also conserved. The immune signaling network state will be compared among three diverse angiosperm species, Arabidopsis, tomato, and rice. It will be achieved by combinatorially perturbing key network hubs using mutations, measuring the effects of the perturbations on the immune response using transcriptome analysis and other methods, and comparing the relationships among the key network hubs among the three species. This research will provide insights into how a highly resilient biological network has evolved and reveal the extent to which the structure and state of the immune signaling network have diverged among angiosperms. This project is co-funded by the Plant Biotic Interactions Program, the Plant Genome Research Program and the Systems and Synthetic Biology Cluster.

在识别病原体攻击时，植物启动免疫反应以保护自己免受病原体的侵害。免疫信号网络控制免疫反应。本研究旨在回答两个问题。(1)当代陆地植物复杂的免疫信号网络是如何在进化过程中出现的？(2)在不同的开花植物中，信号网络有多少多样性？ 问题（2）将通过详细比较信号网络在三种不同的开花植物物种（番茄、水稻和模式植物拟南芥）中的运作来回答。研究结果将为复杂的生物系统如何进化提供一个例子。他们还将提供有关如何改造植物免疫信号网络以提高作物抗病性的想法。作为推广，将开发一个移动的温室，用于教三年级学生植物如何适应环境。模式植物拟南芥中的免疫信号网络对病原体对其组件的攻击具有高度弹性。这项研究将调查在陆地植物的进化过程中，何时获得了这种高度弹性的信号网络。这将通过询问当特定的免疫相关的亚家族neofunctionalized在较大的蛋白质家族内使用不同的陆地植物物种的蛋白质家族的系统发育分析。亚家族分析方法将自动化，并在基因组规模上应用，以调查控制各种其他生物过程的网络进化的时间。被子植物中的关键网络成分通常是保守的。然而，从来没有研究过网络的状态（网络参数集）是否也是守恒的。免疫信号网络的状态将在三种不同的被子植物，拟南芥，番茄和水稻。它将通过使用突变组合扰动关键网络枢纽，使用转录组分析和其他方法测量扰动对免疫反应的影响，并比较三个物种之间关键网络枢纽之间的关系来实现。这项研究将提供深入了解一个高弹性的生物网络是如何进化的，并揭示免疫信号网络的结构和状态在被子植物中的分化程度。该项目由植物生物相互作用计划，植物基因组研究计划和系统与合成生物学集群共同资助。

项目成果

Pathogen‐driven coevolution across the CBP60 plant immune regulator subfamilies confers resilience on the regulator module

CBP60 植物免疫调节子家族中病原体驱动的协同进化赋予调节器模块弹性

• DOI: 10.1111/nph.17769
• 发表时间: 2021
• 期刊: New Phytologist
• 影响因子: 9.4
• 作者: Zheng, Qi;Majsec, Kristina;Katagiri, Fumiaki
• 通讯作者: Katagiri, Fumiaki

How might highly resilient plant immunity have evolved? A “multiverse” hypothesis

高弹性植物免疫力是如何进化的？

• DOI: 10.1016/j.pmpp.2023.101968
• 发表时间: 2023
• 期刊: Physiological and Molecular Plant Pathology
• 影响因子: 2.7
• 作者: Katagiri, Fumiaki