Molecular Signal Integration for Root Growth Control

用于根生长控制的分子信号集成

• 批准号: 10459320
• 负责人: Wolfgang Busch
• 金额: $ 40.4万
• 依托单位: SALK INSTITUTE FOR BIOLOGICAL STUDIES
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-08-01 至 2023-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10459320
• 关键词: Alleles; Arabidopsis; Area; Binding; Biochemistry; Biological Models; Cells; Complex; Conflict (Psychology); Cues; Data; Disease; Event; Flagellin; Genes; Genetic; Genetic Variation; Genetic study; Genomics; Genotype; Growth; Growth and Development function; Health; Individual; Iron; Lead; Longevity; Malignant Neoplasms; Mammals; Measures; Mediating; Microscopy; Modeling; Molecular; Monitor; Mononuclear; Mouse-ear Cress; Nutrient; Organ; Organism; Other Genetics; Pathway interactions; Patients; Pattern; Perception; Phenotype; Phosphorylation; Phosphotransferases; Plant Model; Plant Roots; Plants; Process; Protein Kinase; Proteins; Quinate; Regulation; Regulatory Pathway; Research; Signal Transduction; Soil; Structure; System; Testing; Time; Tissues; Variant; Water; base; cell growth; cell type; defense response; design; experimental study; extracellular; fitness; genetic approach; genetic variant; genome wide association study; insight; member; microbial; mutant; non-invasive imaging; organ growth; pathogen; personalized medicine; phenomics; protein protein interaction; public health relevance; receptor; response

Abstract Multicellular organisms must precisely control the growth and size of tissues and organs. For this, cells reproducibly and accurately interpret information conveyed by extrinsic signals and perceived by a large array of sensing machinery. Malfunction of these growth-regulatory pathways decreases organismal fitness and can lead to diseases like cancer. While several major pathways controlling organ and tissue growth have been well characterized, there are two very important areas that are not well understood. First, how are multiple, often conflicting growth regulatory extrinsic signals integrated to impact growth? Second, how does natural genetic variation impact these growth pathways and their responses to extrinsic signals? The root of the model plant Arabidopsis thaliana is ideal for studying the genetic and molecular bases for how organ growth is adjusted based on multiple signals, and how these responses are modulated by genotype. This is because plants, in particular their root systems, have evolved mechanisms for tightly coordinating all aspects of growth and development to environmental conditions. Moreover, it is possible to efficiently and quantitatively monitor root growth over long periods of time without sacrificing the organism (as is the case for mammals). Moreover, it is possible to monitor thousands of plants in parallel, enabling large-scale genetic approaches for assessing multiple environmental conditions. To date, 1135 isogenic strains of Arabidopsis have been fully sequenced and many of these strains respond in distinct ways to environmental signals, providing a platform for phenomics and genome-wide association studies to identify gene variants responsible for these contrasting growth responses. Taken together, the Arabidopsis root is a unique system for studying how organ growth is coordinated to multiple environmental signals, and how this coordination is modulated by genotype. It has recently been shown that root growth responses to low iron levels are largely determined by natural genetic variation within a group of receptor kinases and a protein kinase. At least two of these genes are also involved in responses to flagellin, a pathogen associated molecular pattern. Based on these data, a model has been formulated that this receptor kinase "module" integrates iron and defense cues (which promote and inhibit growth, respectively) to regulate root growth. In this proposal, experiments will test the hypotheses that protein- protein interactions and their dynamics within this receptor kinase module modulate root growth in response to iron and flagellin (Aim 1), and that allelic variation in the receptor kinase module determines growth sensitivities to iron and microbial signals, as well as the integration of these signals (Aim 2). Finally, mechanistic studies will be performed to determine the molecular processes by which root growth is regulated in response to iron levels (Aim 3). Overall, this project will provide insights into how multiple signals are integrated to regulate organ growth, and how each individual's genotype modulates this process.

摘要 多细胞生物必须精确地控制组织和器官的生长和大小。为此，细胞 可再现地和准确地解释由外部信号传达的信息和由大阵列感知的信息 传感器的机器。这些生长调节途径的功能障碍会降低生物体的适应性， 导致癌症等疾病。虽然控制器官和组织生长的几个主要途径已经很好地 有两个非常重要的领域尚未得到很好的理解。第一，如何多，经常 相互冲突的生长调节外在信号整合影响生长？二、天然遗传如何 变异影响这些生长途径及其对外在信号的反应？ 模式植物拟南芥的根是研究遗传和分子基础的理想选择， 器官生长是根据多种信号以及基因型如何调节这些反应来调节的。这 是因为植物，特别是它们的根系，已经进化出了紧密协调各个方面的机制， 生长和发育的环境条件。此外，可以有效地和定量地 在不牺牲有机体的情况下长时间监测根的生长（如哺乳动物的情况）。 此外，可以同时监测数千种植物，从而实现大规模的遗传方法， 评估多种环境条件。到目前为止，1135个拟南芥等基因株已完全被 测序和许多这些菌株以不同的方式响应环境信号，提供了一个平台 表型组学和全基因组关联研究，以确定基因变异负责这些对比 增长反应。总之，拟南芥根是研究器官生长如何影响植物生长的独特系统。 协调多个环境信号，以及这种协调是如何由基因型调制。 最近的研究表明，根对低铁水平的生长反应在很大程度上是由自然遗传决定的。 一组受体激酶和蛋白激酶内的变异。这些基因中至少有两个也与 鞭毛蛋白是病原体相关的分子模式。根据这些数据，一个模型已经被 该受体激酶“模块”整合了铁和防御信号（其促进和抑制 生长，分别），以调节根生长。在这项提议中，实验将测试蛋白质- 蛋白质相互作用及其在该受体激酶模块中的动力学调节根的生长， 铁和鞭毛蛋白（Aim 1），且受体激酶模块中等位基因变异决定生长敏感性 铁和微生物信号，以及这些信号的整合（目的2）。最后，机械研究将 进行，以确定响应铁水平调节根生长的分子过程 (Aim（3）第三章。总的来说，该项目将提供关于如何整合多种信号以调节器官生长的见解， 以及每个个体的基因型如何调节这一过程。

项目成果

The receptor kinase SRF3 coordinates iron-level and flagellin dependent defense and growth responses in plants.

• DOI: 10.1038/s41467-022-32167-6
• 发表时间: 2022-08-01
• 期刊: Nature communications
• 影响因子: 16.6

Spatial IMA1 regulation restricts root iron acquisition on MAMP perception.

• DOI: 10.1038/s41586-023-06891-y
• 发表时间: 2024-01
• 期刊: Nature
• 影响因子: 64.8
• 作者: Min Cao;M. Platre;Huei-Hsuan Tsai;Ling Zhang;Tatsuya Nobori;Laia Armengot;Yintong Chen;Wenrong He;Lukas Brent;Núria S Coll;J. Ecker;Niko Geldner;Wolfgang Busch

Plasmodesmata mediate cell-to-cell transport of brassinosteroid hormones

• DOI: 10.1038/s41589-023-01346-x
• 发表时间: 2023-06
• 期刊: Nature chemical biology
• 影响因子: 14.8
• 作者: Yaowei Wang;Jessica Pérez-Sancho;M. Platre;B. Callebaut;M. Smokvarska;Karoll Ferrer;Yongming Luo;Trevor M. Nolan;Takeo Sato;Wolfgang Busch;P. Benfey;M. Kvasnica;Johan M. Winne;E. Bayer;Nemanja Vukašinović;E. Russinova