Deciphering Biochemical Networks in Single Dendritic Spines

破译单树突棘中的生化网络

• 批准号: 9330948
• 负责人: Ryohei Yasuda
• 金额: $ 95.5万
• 依托单位: MAX PLANCK FLORIDA CORPORATION
• 依托单位国家: 美国
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-09-30 至 2020-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9330948
• 关键词: Autistic Disorder; Biochemical; Complex; Data; Data Set; Dementia; Dendritic Spines; Disease; Elements; Failure; Fluorescence Resonance Energy Transfer; Goals; Impairment; Lead; Learning; Measurement; Measures; Mediating; Memory; Mental Retardation; Nerve Degeneration; Neurons; Output; Play; Proteins; Psyche structure; Signal Transduction; Signaling Protein; Surface; Synaptic plasticity; Systems Development; Techniques; Vertebral column; base; imaging system; improved; insight; postsynaptic; public health relevance; sensor

 DESCRIPTION (provided by applicant): Synaptic plasticity, a cellular basis of learning and memory, is mediated by a complex biochemical signaling network consists of hundreds of signaling proteins. In particular, Ca2+- dependent signaling in dendritic spines, tiny postsynaptic compartments emanating from dendritic surface, plays a key role in the induction of long-term synaptic plasticity. In order to understand the operational principles of this network and the mechanisms underlying synaptic plasticity, the activity of hundreds of proteins under many manipulations needs to be measured in single dendritic spines during synaptic plasticity. The activity of proteins in spines has been measured using advanced fluorescence resonance energy transfer (FRET)-based techniques. However, thus far only a small fraction of the entire network has been measured. Our understanding of signaling networks is limited by this scarcity of measurements for signaling components. Thus, the goal of this project is to establish a high-throughput system for the development and optimization of signaling sensors, and a fully automated system for imaging signal transduction during plasticity in single dendritic spines. Using this high-throughput imaging system, we aim to improve the overall efficiency of data output by orders of magnitude, producing large data sets that could be further analyzed for information flow in the signaling network and connectivity between network elements. Thus, this project is expected to lead to a dramatic advance in our understanding of intracellular signaling in neurons and provide key insights into the mechanisms underlying synaptic plasticity and ultimately learning and memory.

 描述（由申请人提供）：突触可塑性是学习和记忆的细胞基础，由数百种信号蛋白组成的复杂生化信号网络介导。特别是，树突棘中的钙依赖性信号，微小的突触后 从树突表面发出的隔室，在诱导长时程突触可塑性中起关键作用。为了理解这个网络的运作原理和突触可塑性的机制，需要在突触可塑性期间在单个树突棘中测量数百种蛋白质在许多操作下的活性。使用先进的基于荧光共振能量转移（FRET）的技术测量了棘中蛋白质的活性。然而，到目前为止，只有整个网络的一小部分被测量。我们对信令网络的理解受到信令组件测量稀缺的限制。因此，本项目的目标是建立一个高通量的系统，用于开发和优化信号传感器，以及一个全自动的系统，用于在单个树突棘的可塑性过程中成像信号转导。使用这种高通量成像系统，我们的目标是提高数据输出的整体效率的数量级，产生大的数据集，可以进一步分析信令网络中的信息流和网络元素之间的连接。因此，该项目预计将导致我们对神经元细胞内信号传导的理解取得巨大进展，并为突触可塑性和最终学习和记忆的机制提供关键见解。