Application of Transient Intervention and Live-Imaging Methods to Resolve Cellular and Molecular Networks Regulating Stem-Cell Homeostatis in Arabidopsis Shoot Apex

应用瞬时干预和实时成像方法解决拟南芥芽尖干细胞稳态调节的细胞和分子网络

• 批准号: 0718046
• 负责人: Venugopala Gonehal
• 金额: $ 101.4万
• 依托单位: University of California-Riverside
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-08-01 至 2013-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0718046&HistoricalAwards=false
• 关键词: Application; Transient; Intervention; Live; Imaging

Venugopala Reddy Gonehal0718046Application of transient intervention and live-imaging methods to resolve cellular and molecular networks regulating stem-cell homeostasis in Arabidopsis shoot apex Cell division of stem-cells is critical to ensure proper development, maintenance and repair of tissues and organs of both animals and plants. In plants, the shoot tip (shoot apical meristem; SAM) harbors a set of stem-cells that are surrounded by differentiating cells. The stem-cell number remains constant, even though the stem-cell progeny are being continually diverted to differentiating cells. Thus, the SAM represents a dynamic network of different cell types in which growth and differentiation are dynamically regulated through a cell-cell communication network that precisely controls spatial and temporal patterns of gene expression. Understanding how cells interpret this complex mixture of signals to regulate cell division requires the development of new methods that identify network components and elucidate their regulatory dynamics and function. In this proposal, the PI will apply transient genetic and physical manipulations with live-imaging technologies to explore the function and regulation of key regulators of stem-cell maintenance. The PI also will combine transient gene manipulation and stem-cell enrichment methods with microarray technology to develop a dynamic map of cellular and molecular interactions in actively growing SAMs with the ultimate objective of developing predictive models of cell-cell communication that mediate stem cell homeostasis. Training will be provided for a post-doctoral fellow, graduate student and under-graduate students in designing new methods of transient gene manipulation, expression profiling and live-imaging. They will be exposed to state-of-the art imaging systems and image processing platforms for visualization, rendering and analysis of microscopic data. Early exposure of a new generation of scientists to dynamic methods of data acquisition and data handling would prepare them for future challenges of quantitative imaging.

Venugopala Reddy Gonehal0718046瞬态干预和实物现象方法的应用，以解决调节拟南芥中干细胞稳态的细胞和分子网络的干细胞芽细胞分裂至关重要，这对于确保对两种动物和植物的组织和组织的适当发育，维持和修复的适当发育，维护和修复。在植物中，芽尖（芽顶分生组织； sam）拥有一组被分化细胞所包围的干细胞。即使干细胞后代不断转移到分化细胞，干细胞数仍然保持恒定。 因此，SAM代表了不同细胞类型的动态网络，其中生长和分化通过细胞 - 细胞通信网络动态调节，该网络通信网络精确控制基因表达的空间和时间模式。了解细胞如何解释信号的这种复杂混合以调节细胞分裂需要开发新方法，以识别网络组件并阐明其调节动力学和功能。在此提案中，PI将使用现场成像技术应用瞬时遗传和物理操纵来探索Stem-Cell维护的关键调节剂的功能和调节。 PI还将将瞬时基因操纵和干细胞富集方法与微阵列技术相结合，以在主动生长的SAM中开发细胞和分子相互作用的动态图，并最终目标是开发介导干细胞稳态的细胞电池通信的预测模型。将为博士后研究员，研究生和本科生提供培训，以设计新的瞬时基因操纵，表达分析和现场模仿方法。它们将接触到最新的成像系统和图像处理平台，以进行显微镜数据的可视化，渲染和分析。新一代科学家的早期暴露于数据获取和数据处理的动态方法中，将为它们做好定量成像的未来挑战的准备。