Signaling interactions between pattern- and effector-triggered immunity in plants

植物有一个免疫系统，当它们检测到病原体攻击时就会被激活。植物免疫有两种模式，每一种都是由不同类型的病原体衍生分子作为攻击线索触发的。这两种免疫模式如何相互影响以改变免疫反应尚不清楚。该项目将精确测量每种模式对其他模式的影响，并寻求发现介导跨模式相互作用的植物蛋白。由于这两种模式是植物免疫的核心，该项目将有可能扩展我们对植物如何利用其免疫系统保护自己免受病原体侵害的理解。这项工作的潜在应用包括提高农业环境中植物免疫系统性能的工具和知识，这可能导致在对环境影响较小的情况下更好地控制作物疾病。这个项目的另一个重要方面是培养时间有限的本科生进行研究工作。虽然该项目是一个新的本科培训平台的试点案例，但该平台将很容易扩展到多个地点的更多学生。因此，它具有改善大量本科生生物教育的潜力。由于该项目涉及统计和计算部分以及生物部分，因此将培养广泛的科学和工程领域的博士后，博士和本科生。

Plants have an immune system that is activated when they detect pathogen attack. There are two modes of plant immunity, each triggered by different types of pathogen-derived molecules as cues of attack. How these two modes of immunity influence each other to modify the immune response is not well understood. This project will precisely measure the influence of each mode upon the other and seek to discover the plant proteins that mediate cross-mode interactions. Since the two modes are central in plant immunity, this project will potentially extend our understanding of how plants use their immune system to defend themselves against pathogens. Potential applications of the work include tools and knowledge to improve the performance of the plant immune system in agricultural settings, which can lead to better control of crop diseases with less impact on the environment. Another important aspect of this project is training undergraduate students who have limited time for research work. While this project functions as a pilot case for a new undergraduate training platform, the platform will be easily expanded to involve more students at multiple sites. Therefore, it has the potential to improve biology education for a large number of undergraduate students. Since this project involves statistical and computational components as well as biological components, post-doctoral, doctoral, and undergraduate students will be trained in broad areas of science and engineering.