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项目摘要/摘要 植物天然产物是小分子物质发现和发展的重要来源 药物。对基因组数据的分析表明,自然界的合成潜力在很大程度上 被低估了,而且大多数核动力源都没有被开发。在过去的二十年里,许多方法 已经被开发来更有效地从微生物中发现新的NPs。然而,这些都不是 策略适用于预测或激活神秘或效率极低的生物合成途径。 在植物中的正常条件下。植物NPs被认为在植物的天然免疫中起着不可或缺的作用 和防御框架。响应于通过模式识别来识别病原体或损害 受体(PRRs),植物激活NPs的生物合成,这些NPs起防御分子的作用,如 抗菌剂。PRRs是表面定位的、配体结合的、受体样激酶或蛋白质,识别和 对环境中的分子信号做出反应。基因组分析表明,植物编码的数量巨大 其中95%以上的功能尚不清楚,即使在模式植物拟南芥中也是如此。如果我们 可以激活未知PRR的下游通路,植物作为防御或 各种情况下的信号分子都会被激活和发现。因此,我们建议发展 一种改变植物免疫信号以发现新的植物NPs的策略。中心假说 1)植物感知复合体/免疫信号通路可以在面包酵母中进行功能重组 酿酒酵母;2)植物PRR可以被改造来识别改变的刺激;以及3)信号 目的植物PRRs下游的代谢通路可以通过导入工程菌而被激活 PRR和相应的刺激。凭借合成生物学和NP生物合成方面的专业知识,我们将验证 使用拟南芥,通过执行以下三个特定目标来假设和演示这一策略 目标1,建立一个能够实现植物免疫功能重组的酵母平台 复杂和高通量的表型;目标2,设计植物免疫受体,使其能够被 已知刺激;目标3,将嵌合免疫受体植入植物NP的模式植物中,并 生物合成的发现。该项目将产生1)发现可能无法合成的新型植物NPs 2)工程植物模式识别策略 可以激活各种植物免疫和新陈代谢反应的受体;3)对高度 复杂的植物信号通路(免疫、感知、生长因子、植物激素等)是相关的,并且 受监管的。这一方法的发展是朝着我的长期目标迈出的重要一步:(1)推进 对植物化学合成的基础认识,(2)促进新的植物化学物质的发现 用于医药用途;以及(3)开发具有高价值的植物化学物质的微生物生产 一种经济的方法。
英文摘要
Project Summary/Abstract Plant natural products (NPs) are important sources for the discovery and development of small molecule medicines. Analysis of the genome data implies that nature's synthetic potential has been largely underestimated, and the majority of NPs have been unexplored. Over the past twenty years, many approaches have been developed to more efficiently discover novel NPs from microbial organisms. However, none of these strategies are applicable to predicting or activating biosynthetic pathways that are cryptic or of very low efficiency under normal conditions in plants. Plant NPs are believed to play an indispensable role in plants' innate immunity and defense framework. In response to the recognition of pathogens or damage by the pattern recognition receptors (PRRs), the plant activates the biosynthesis of NPs that function as defensive molecules such as antimicrobials. PRRs are surface-localized, ligand-binding, receptor-like kinases or proteins that recognize and respond to molecular signals in the environment. Genome analysis indicates that plants encode a huge number of PRRs, with the function of more than 95% being unknown even in the model plant Arabidopsis thaliana. If we can activate the downstream pathways of the unknown PRRs, plant NPs that are produced as defense or signaling molecules under various situations will be activated and discovered. Therefore, we propose to develop a strategy to engineer and redirect plant immune signaling to discover novel plant NPs. The central hypotheses are 1) plant perception complex/immune signaling pathway can be functionally reconstituted in the baker's yeast Saccharomyces cerevisiae; 2) plant PRRs can be engineered to recognize altered stimulus; and 3) the signaling and metabolic pathways downstream of target plant PRRs can be activated through introducing the engineered PRR and the corresponding stimulus. With expertise in synthetic biology and NP biosynthesis, we will verify the hypotheses and demonstrate this strategy through executing the following three specific aims, using Arabidopsis thaliana as the testbed: Aim 1, establish a yeast platform that enables functional reconstitution of plant immune complex and high throughput phenotyping; Aim 2, engineer plant immune receptors so they can be activated by known stimulus; Aim 3, implement the chimeric immune receptors into the model plant for plant NP and biosynthesis discovery. The project will generate 1) discovery of novel plant NPs that may not be synthesized under normal conditions, and their native functions; 2) strategies for engineering plant pattern recognition receptors that can activate various plant immune and metabolic responses; 3) insights into how the highly complex plant signaling pathways (immune, perception, growth factor, plant hormone, etc.) are correlated and regulated. The development of this methodology is a significant step towards my long-term goals: (1) to advance the foundational understanding of phytochemical synthesis, (2) to promote the discovery of novel phytochemicals for pharmaceutical applications, and (3) to develop microbial bio-production of phytochemicals of high value as an economic approach.
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