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
基本信息
- 批准号:8414128
- 负责人:
- 金额:$ 21.06万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 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:
- 关键词:AddressAnimalsBone MarrowCell Culture TechniquesCellsCommunitiesComplexGene ExpressionGoalsHeterogeneityImageImage AnalysisImaging technologyImmuneImmune systemImmunologyIndividualLibrariesLifeLocationMeasurementMeasuresMethodsMicrofluidicsMicroscopyMonitorMovementNatureOutputPopulationProteinsRNAResearchResourcesScienceSignal PathwaySignal TransductionStimulusSystemTechniquesTechnologyTimecellular imagingcomputational network modelingimaging modalityin vivonew technologynovelresponsetooltranscription factor
项目摘要
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):了解单细胞中先天免疫信号网络的动态是免疫学的基本目标。 Covert 实验室采用结合活细胞成像、高通量图像分析、微流体细胞培养和计算网络建模的最新技术的方法,通过测量 NFkB 对多种因素组合的单细胞反应,研究细胞如何解码复杂的环境信息。刺激和时间依赖性刺激(Nature,2010;Science Signaling 2009)。尽管这些方法和类似的方法对于表征细胞群内的表型异质性非常有用(例如,在研究 p53 时),但从中得出的结论受到可测量输出数量相对较少以及事实上,到目前为止,几乎所有此类研究都是在培养细胞中进行的。我们建议大幅扩大免疫系统活细胞动态成像的范围,开发新技术以大幅增加可测量输出的数量,并实现体内测量。我们的具体目标是:(1) 创建一个构建体和细胞库,能够在单个细胞中同时监测多种因素,包括多个平行信号通路和内源表达水平。 (2) 为了了解网络动态如何控制基因表达,我们建议通过将最近开发的 RNA FISH 技术与我们的活细胞成像技术相结合,开发将单细胞中转录因子的动态与内源基因表达的动态相关联的方法。这将是第一次将动态转录因子活性与单个细胞中的基因表达直接进行比较。 (3) Covert 实验室将与加州大学圣地亚哥分校的 Tannishtha Reya 合作,将我们用于单细胞中蛋白质定位成像和定量的方法与她用于监测体内细胞运动的开创性工具相结合。通过结合这些方法,我们将成为第一个观察单个细胞中转录因子在完整动物骨髓中移动时的动态变化的人。在实现这些目标的过程中,我们期望对环境信息如何在信号网络动态中编码获得更详细的系统级理解,并为科学界开发一些首创的技术。
公共健康相关性:监测个体细胞和体内免疫系统的新方法 项目叙述 近年来,科学家们已经意识到我们体内的每个个体细胞的重要性,以及即使是两个相邻的同类细胞也可以表现得相当重要。不同。有一些方法可以实时观察单个细胞,特别是关键蛋白质的激活,但该技术存在许多局限性。我们提议开发一些新技术,使追踪单个细胞中发生的免疫反应变得更加容易——即使细胞在活体动物体内移动。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Markus W Covert其他文献
Markus W Covert的其他文献
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{{ truncateString('Markus W Covert', 18)}}的其他基金
Multi-scale, model-driven exploration of sub-generational gene expression in bacteria: individual consequences, population benefits
细菌亚代基因表达的多尺度、模型驱动探索:个体后果、群体效益
- 批准号:
10298623 - 财政年份:2021
- 资助金额:
$ 21.06万 - 项目类别:
Multi-scale, model-driven exploration of sub-generational gene expression in bacteria: individual consequences, population benefits
细菌亚代基因表达的多尺度、模型驱动探索:个体后果、群体效益
- 批准号:
10654847 - 财政年份:2021
- 资助金额:
$ 21.06万 - 项目类别:
Deep Curation via an Integrated Whole-Cell Computational Model
通过集成的全细胞计算模型进行深度管理
- 批准号:
10557790 - 财政年份:2020
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$ 21.06万 - 项目类别:
Deep Curation via an Integrated Whole-Cell Computational Model
通过集成的全细胞计算模型进行深度管理
- 批准号:
10357850 - 财政年份:2020
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$ 21.06万 - 项目类别:
Deep Curation via an Integrated Whole-Cell Computational Model
通过集成的全细胞计算模型进行深度管理
- 批准号:
10153881 - 财政年份:2020
- 资助金额:
$ 21.06万 - 项目类别:
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:
8537822 - 财政年份:2012
- 资助金额:
$ 21.06万 - 项目类别:
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