High-resolution quantification of focal adhesion spatiotemporal dynamics in living cells.

High-resolution quantification of focal adhesion spatiotemporal dynamics in living cells.
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DOI:
10.1371/journal.pone.0022025
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发表时间:
2011
期刊:
影响因子:
3.7
通讯作者:
Gomez SM
Gomez SM
中科院分区:
综合性期刊3区
文献类型:
--
作者:
Berginski ME;Vitriol EA;Hahn KM;Gomez SM

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粘着斑(FAs)是在细胞与其外部环境之间提供连接的大分子复合物。在运动细胞中,粘着斑通过组装和拆卸的动态过程改变大小和位置来控制细胞迁移。为了更好地了解局灶性粘连的动态调节,我们开发了一种分析系统,用于活细胞中这些结构的自动检测、跟踪和数据提取。该分析系统用于定量NIH 3T3成纤维细胞中荧光标记的桩蛋白和FAK的动力学,然后通过全内反射荧光显微镜(TIRF)进行定量。高含量的时间序列包括存在于活细胞中的每个粘附的大小、形状、强度和位置。这些性能随时间推移,揭示粘附寿命和周转率,并分离到不同的区域的属性。作为概念验证,我们展示了在Jun激酶磷酸化位点丝氨酸178处的桩蛋白单点突变如何改变FA的大小、分布和组装速率。这项研究提供了一个详细的,定量的图片FA时空动力学以及一套工具和方法,以推进我们的了解如何局灶性粘连在活细胞中的动态调节。这个管道的完整的开源软件实现在http://gomezlab.bme.unc.edu/tools上提供。
Focal adhesions (FAs) are macromolecular complexes that provide a linkage between the cell and its external environment. In a motile cell, focal adhesions change size and position to govern cell migration, through the dynamic processes of assembly and disassembly. To better understand the dynamic regulation of focal adhesions, we have developed an analysis system for the automated detection, tracking, and data extraction of these structures in living cells. This analysis system was used to quantify the dynamics of fluorescently tagged Paxillin and FAK in NIH 3T3 fibroblasts followed via Total Internal Reflection Fluorescence Microscopy (TIRF). High content time series included the size, shape, intensity, and position of every adhesion present in a living cell. These properties were followed over time, revealing adhesion lifetime and turnover rates, and segregation of properties into distinct zones. As a proof-of-concept, we show how a single point mutation in Paxillin at the Jun-kinase phosphorylation site Serine 178 changes FA size, distribution, and rate of assembly. This study provides a detailed, quantitative picture of FA spatiotemporal dynamics as well as a set of tools and methodologies for advancing our understanding of how focal adhesions are dynamically regulated in living cells. A full, open-source software implementation of this pipeline is provided at http://gomezlab.bme.unc.edu/tools.
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