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Experimental and computational framework for a dynamic protein atlas of human cell division

机译:人类细胞分裂动态蛋白质图谱的实验和计算框架

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Essential biological functions, such as mitosis, require tight coordination of hundreds of proteins in space and time. Localization, the timing of interactions and changes in cellular structure are all crucial to ensure the correct assembly, function and regulation of protein complexes(1-4). Imaging of live cells can reveal protein distributions and dynamics but experimental and theoretical challenges have prevented the collection of quantitative data, which are necessary for the formulation of a model of mitosis that comprehensively integrates information and enables the analysis of the dynamic interactions between the molecular parts of the mitotic machinery within changing cellular boundaries. Here we generate a canonical model of the morphological changes during the mitotic progression of human cells on the basis of four-dimensional image data. We use this model to integrate dynamic three-dimensional concentration data of many fluorescently knocked-in mitotic proteins, imaged by fluorescence correlation spectroscopy-calibrated microscopy(5). The approach taken here to generate a dynamic protein atlas of human cell division is generic; it can be applied to systematically map and mine dynamic protein localization networks that drive cell division in different cell types, and can be conceptually transferred to other cellular functions.
机译:基本的生物学功能(例如有丝分裂)需要在空间和时间上紧密结合数百种蛋白质。定位,相互作用的时机和细胞结构的变化对于确保蛋白质复合物的正确组装,功能和调控都是至关重要的(1-4)。活细胞的成像可以揭示蛋白质的分布和动态,但是实验和理论上的挑战阻止了定量数据的收集,这对于建立有丝分裂模型是必要的,该模型可以全面整合信息并能够分析分子之间的动态相互作用不断变化的细胞边界内的有丝分裂机制的变化。在此,我们基于三维图像数据生成了人类细胞有丝分裂进程中形态变化的典型模型。我们使用此模型来整合许多荧光敲入的有丝分裂蛋白的动态三维浓度数据,该数据通过荧光相关光谱校准的显微镜成像(5)。这里生成人类细胞分裂的动态蛋白质图谱的方法是通用的。它可以用于系统地定位和挖掘驱动不同细胞类型中细胞分裂的动态蛋白质定位网络,并且可以从概念上转移到其他细胞功能。

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