Signaling network reconstruction from biosensor image fluctuations

从生物传感器图像波动重建信号网络

• 批准号: 8607468
• 负责人: Marco Antonio Vilela
• 金额: $ 2.75万
• 依托单位: HARVARD MEDICAL SCHOOL
• 依托单位国家: 美国
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-01-01 至 2014-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8607468
• 关键词: Abnormal Cell; Address; Algorithms; Amino Acids; Behavior; Biochemical; Biosensor; Cell physiology; Cells; Complex; Computer Analysis; Data; Detection; Development; Disease; Event; Family; Feedback; Fluorescence Resonance Energy Transfer; Generic Drugs; Goals; Guanosine Triphosphate Phosphohydrolases; Heterogeneity; Human Pathology; Image; Laboratories; Lead; Life; Location; Measurement; Measures; Mediating; Methods; Monomeric GTP-Binding Proteins; Movement; Mutation; Pathway interactions; Pattern; Phosphorylation; Process; Proteins; Regulation; Relative (related person); Series; Signal Pathway; Signal Transduction; Signaling Molecule; Technology; Testing; Time; base; cell motility; cellular imaging; computerized tools; human disease; migration; natural flow; novel; public health relevance; reconstruction; research study; rho; spatiotemporal; time use; tool

DESCRIPTION (provided by applicant): Most human diseases and disorders can be seen as a projection of disrupted cellular components. Such anomalies restrain and/or modify the natural flow of information among the cellular processes, impairing appropriate cell decision. For instance, mutation of the small GTPase proteins can lead to abnormal cell migration. This simplistic description of an aberrant process highlights the importance of probing not only how information is transmitted, e.g. through amino acid phosphorylation, but also the direction it takes from a given point. The discovery of this directionality potentially defines the function of given cellular component. For example, an active form of a protein switches on a specific cellular behavior at a particular region of the cell. Biosensor technology has been proposed to overcome the current limitations of classical biochemical methods on the process of establishing signaling pathway functionality. These fluorescent constructs allow the measurement of the localization and the active state of the studied molecule in living cells. Because proteins can interact with different molecules in different cellular locations, biosensor technology stands out as a powerful tool to address questions of how differently regulated a given protein is in time and space. This proposal focuses on the computational analysis of biosensor imaging data. The main goal is to build a set of computational tools that will infer paths among molecules and specific cellular behavior from biosensor images. As a proof of concept, the second part of this project focuses on the elucidation of Rac1 regulation at the lamellipodia region of cells using the proposed computational tools. This challenge sets up the suitability and relevance of the computational tools proposed here.

描述（由申请人提供）：大多数人类疾病和失调可以看作是细胞成分被破坏的投影。这种异常抑制和/或改变了细胞过程中信息的自然流动，损害了细胞的适当决策。例如，小GTPase蛋白的突变会导致细胞异常迁移。这种对异常过程的简单描述不仅强调了探测信息如何传递的重要性，例如通过氨基酸磷酸化，而且还强调了从给定点出发的方向。这种方向性的发现潜在地定义了给定细胞成分的功能。例如，蛋白质的活性形式在细胞的特定区域开启特定的细胞行为。生物传感器技术的提出是为了克服目前经典生化方法在建立信号通路功能过程中的局限性。这些荧光结构允许在活细胞中测量所研究分子的定位和活性状态。由于蛋白质可以与不同细胞位置的不同分子相互作用，生物传感器技术作为解决特定蛋白质在时间和空间中如何受到不同调节的问题的强大工具脱颖而出。本提案的重点是生物传感器成像数据的计算分析。主要目标是建立一套计算工具，从生物传感器图像中推断分子之间的路径和特定的细胞行为。作为概念的证明，本项目的第二部分重点是阐明细胞板足区Rac1的调控