NCS-FO: Identifying Design Principles of Neural Cells

NCS-FO：确定神经细胞的设计原理

• 批准号: 1533708
• 负责人: Amina Qutub
• 金额: $ 92万
• 依托单位: William Marsh Rice University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-08-01 至 2018-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1533708&HistoricalAwards=false
• 关键词: NCS; FO; Identifying; Design; Principles

PI: Qutub, Amina Proposal Number: 1533708This proposal seeks to develop a robust theory of how single neural cells form electrically active networks. The project integrates emerging methods in computer science, systems biology, neuroengineering and developmental biology to offer insight into the brain's organization. Results of experiments performed in this project have the potential to impact the design of new computing devices, a $300B industry. Methods introduced by the investigators can be used broadly by scientists to rapidly characterize brain cells, and can aid in the discovery of new therapies for neurological diseases, which affect 1 in 6 people worldwide.Neural differentiation, the process of neural progenitor cells transforming into neurons, holds the key to understanding the brain's ability to self-repair. Understanding this complex process can inform us how the structure of neural networks relates to their function, which is an important unsolved problem in neuroengineering. This project's ultimate goal is a mechanistically-detailed theory of how neural networks form as a result of decisions made by single neural progenitor cells. Integrating methods from three disciplines (systems biology, nanotechnology and developmental biology), the investigators will identify single cell features critical to network formation, and predict how heterogeneity and noise in the cell population defines the network's function. The investigators will employ three emerging methods (proteomic barcoding, ImageOmics, and E-phFACS) to define neural cell phenotypes as a function of chemical signaling, morphology and electrical activity (Aim 1). Observed changes in these single cell phenotypes will be mapped to neural network formation by coupling a state machine model with a graph-based analysis (Aim 2). The effects of cell heterogeneity will be explored computationally using a new framework developed by the investigators and iteratively compared to in vitro live-imaging assays, and in vivo assays. The tight coupling of chemical, morphological and electrical measurements enabled by the technologies introduced here, can be broadly applicable paradigm for integrative scientific research. Understanding how cells interact to form neural networks has relevance to organism development and tissue engineering. State-machines can be adapted across tissues and species to develop theories of cell decision-making. The phenotyping tools that correlate electrophysiology and protein expression with multi-cellular network topology will provide a powerful resource for neurobiologists. Furthermore, the E-phFACS device provides a high-throughput way to record electrical activity and sort cells. To further engage the scientific community, the investigators will (1) provide an open source ImageOmics platform and (2) host an international crowd-sourced neuronal network Design Challenge.

PI：Qutub，Amina 提案编号：1533708该提案旨在发展一个关于单个神经细胞如何形成电活性网络的强大理论。该项目整合了计算机科学、系统生物学、神经工程和发育生物学的新兴方法，以深入了解大脑的组织。在这个项目中进行的实验结果有可能影响新的计算设备的设计，这是一个价值3000亿美元的行业。研究人员介绍的方法可以被科学家广泛用于快速表征脑细胞，并有助于发现神经系统疾病的新疗法，这些疾病影响全球六分之一的人。神经分化，神经祖细胞转化为神经元的过程，是理解大脑自我修复能力的关键。理解这个复杂的过程可以告诉我们神经网络的结构如何与它们的功能相关联，这是神经工程中一个重要的未解决的问题。该项目的最终目标是建立一个详细的理论，解释神经网络是如何由单个神经祖细胞做出决定的。 整合来自三个学科（系统生物学，纳米技术和发育生物学）的方法，研究人员将确定对网络形成至关重要的单细胞特征，并预测细胞群中的异质性和噪声如何定义网络的功能。研究人员将采用三种新兴方法（蛋白质组条形码，ImageOmics和E-phFACS）来定义神经细胞表型作为化学信号，形态和电活动的函数（Aim 1）。观察到的这些单细胞表型的变化将通过将状态机模型与基于图的分析相结合来映射到神经网络形成（目标2）。细胞异质性的影响将使用研究人员开发的新框架进行计算探索，并与体外活体成像测定和体内测定进行迭代比较。这里介绍的技术所实现的化学、形态学和电学测量的紧密耦合，可以成为综合科学研究的广泛适用的范例。了解细胞如何相互作用形成神经网络与生物体发育和组织工程有关。状态机可以跨组织和物种进行调整，以发展细胞决策理论。将电生理学和蛋白质表达与多细胞网络拓扑结构相关联的表型分析工具将为神经生物学家提供强大的资源。此外，E-phFACS设备提供了一种高通量的方式来记录电活性和分选细胞。为了进一步吸引科学界的参与，研究人员将（1）提供开源ImageOmics平台，（2）举办国际众包神经网络设计挑战赛。