New methods for monitoring the immune system, in individual cells and in vivo

监测单个细胞和体内免疫系统的新方法

• 批准号: 8414128
• 负责人: Markus W Covert
• 金额: $ 21.06万
• 依托单位: STANFORD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-09-01 至 2014-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8414128
• 关键词: Address; Animals; Bone Marrow; Cell Culture Techniques; Cells; Communities; Complex; Gene Expression; Goals; Heterogeneity; Image; Image Analysis; Imaging technology; Immune; Immune system; Immunology; Individual; Libraries; Life; Location; Measurement; Measures; Methods; Microfluidics; Microscopy; Monitor; Movement; Nature; Output; Population; Proteins; RNA; Research; Resources; Science; Signal Pathway; Signal Transduction; Stimulus; System; Techniques; Technology; Time; cellular imaging; computational network modeling; imaging modality; in vivo; new technology; novel; response; tool; transcription factor

DESCRIPTION (provided by applicant): To understand the dynamics of the innate immune signaling network in single cells is a fundamental goal of immunology. Using an approach that combines the latest technologies for live-cell imaging, high-throughput image analysis, microfluidic cell culture and computational network modeling, the Covert Lab studies how cells decode complex environmental information by measuring the single-cell responses of NFkB to combinations of stimuli and time-dependent stimuli (Nature, 2010; Science Signaling 2009). Although these and similar approaches have been extremely useful in characterizing phenotypic heterogeneity within a population of cells (also in studying p53, for example), the conclusions that can be drawn from them are limited by the relatively low number of measureable outputs as well as the fact that until now, virtually all of this kind of research has been performed in cultued cells. We propose to dramatically expand the scope of live-cell dynamic imaging of the immune system, developing new technologies to dramatically increase the number of measureable outputs, and enable in vivo measurements. Our Specific Aims are: (1) to create a library of constructs and cells that will enable monitoring of a variety of factors, encompassing multiple parallel signaling pathways and at endogenous expression levels, simultaneously in individual cells. (2) To understand how network dynamics control gene expression, we propose to develop methods to correlate the dynamics of transcription factors with the dynamics of endogenous gene expression in single cells, by integrating recently developed techniques for RNA FISH with our live cell imaging technology. This will be the first time that dynamic transcription factor activity has ever been directly compared with gene expression in individual cells. (3) The Covert Lab will partner with Tannishtha Reya at UCSD to integrate our methods for imaging and quantifying protein localization in single cells with her pioneering tools for monitoring cellular movement in vivo. By combining these approaches, we will be the first to observe the dynamics of transcription factors in individual cells as they move through the bone marrow of intact animals. In achieving these goals, we expect to achieve a significantly more detailed and system-level understanding of how environmental information is encoded in signaling network dynamics, and to have produced some first-of-its-kind technology for the scientific community. PUBLIC HEALTH RELEVANCE: New methods for monitoring the immune system, in individual cells and in vivo Project Narrative In recent years, scientists have realized how important each individual cell in our bodies are, and how even two neighboring cells of the same kind can behave quite differently. There are some ways to observe individual cells, and specifically the activation of key proteins, in real- time, but there are many limitations of the technology. We are proposing to develop some new technology that will make it much easier to track and the immune response as it occurs in single cells -- even as the cells move around in a living animal.

描述（由申请人提供）：了解单个细胞中先天免疫信号网络的动态是免疫学的基本目标。使用一种结合实时成像，高通量图像分析，微流体细胞培养和计算网络建模的方法，Covert Lab研究细胞如何通过测量NFKB对刺激和时间依赖时间刺激的组合来解释复杂的环境信息（自然，2010; Science; Science 2009; Science 2009）。尽管这些和类似的方法在表征细胞群体内表型异质性方面非常有用（例如，在研究p53中），但可以从中得出的结论受到相对较少的可测量输出数量的限制，以及迄今为止，实际上所有此类研究已经在一个性培养的细胞中进行了。我们建议大大扩大免疫系统的活细胞动态成像的范围，开发新技术以显着增加可测量的输出数量，并实现体内测量。我们的具体目的是：（1）创建一个构造和单元的库，该库能够监视各种因素，涵盖多个平行信号通路，并在单个单元中同时在内源表达水平下进行。 （2）为了了解网络动力学如何控制基因表达，我们建议通过通过将最近开发的RNA FISH技术与活细胞成像技术整合到单个细胞中的单个细胞中的转录因子动力学与内源基因表达的动力学的方法。这将是第一次将动态转录因子活性直接与单个细胞中的基因表达进行比较。 （3）Covert Lab将与UCSD的Tannishtha Reya合作，以整合我们对单个细胞中蛋白质定位进行成像和量化蛋白质定位的方法，并与她的开拓性工具一起监测体内细胞运动。通过结合这些方法，我们将是第一个观察单个细胞中转录因子动态的人，它们在完整动物的骨髓中移动。在实现这些目标时，我们期望对信号网络动态中的环境信息如何编码，并为科学界生产一些首要技术。 公共卫生相关性：近年来，监测免疫系统，单个细胞和体内项目叙事的新方法，科学家意识到我们体内每个单个细胞的重要性以及即使是两个相同类型的邻近细胞的重要性。有一些方法可以在实时观察单个细胞，特别是关键蛋白的激活，但是该技术有许多局限性。我们提议开发一些新技术，这些技术将使跟踪和免疫反应在单个细胞中的发生 - 即使细胞在活的动物中移动时，它也会发生。