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Quantitative analysis of membrane protein localization and signaling

机译:膜蛋白定位和信号传导的定量分析

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Fluorescence microscopy of labeled proteins yields a wealth of data on cell signaling processes. However, systems for quantitative analysis of such data have lagged behind the recent progress in data acquisition technology. As cellular protein redistribution plays a key role in proximal signaling and the establishment of cell polarity, quantitative information is critical for understanding many signaling networks. We have developed a robust automated system to analyze membrane protein redistribution based on datasets obtained via fluorescence video microscopy. Our system provides methods for cell surface segmentation and reconstruction, cell shape tracking, cell-surface parameterization, and cluster formation analysis. Our system is novel in both its integration and its surface-based approach, enabling model-free analysis of protein redistribution across the entire cell. We validate our system by measuring receptor clustering in T lymphocytes undergoing activation, obtaining clustering velocities consistent with the previously reported single-particle tracking data that serve as our reference standard. Our methods generalize to many cell-signaling phenomena, allowing quantitative measurement of these cell membrane processes and offering the ability to derive empiric parameters for spatial signaling network models.
机译:标记蛋白质的荧光显微镜检查可产生有关细胞信号转导过程的大量数据。但是,用于此类数据的定量分析的系统落后于数据采集技术的最新进展。由于细胞蛋白的重新分布在近端信号传导和细胞极性的建立中起着关键作用,因此定量信息对于理解许多信号传导网络至关重要。我们已经开发了一个强大的自动化系统,可以基于通过荧光视频显微镜获得的数据集来分析膜蛋白的重新分布。我们的系统提供了用于细胞表面分割和重建,细胞形状跟踪,细胞表面参数化以及簇形成分析的方法。我们的系统在集成和基于表面的方法方面都是新颖的,可以对整个细胞中的蛋白质重新分布进行无模型分析。我们通过测量正在激活的T淋巴细胞中的受体簇,验证簇系统的速度,该簇速度与先前报道的用作我们参考标准的单颗粒跟踪数据一致,从而验证了我们的系统。我们的方法适用于许多细胞信号现象,可以对这些细胞膜过程进行定量测量,并具有为空间信号网络模型推导经验参数的能力。

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