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通过自动化多维荧光显微镜分析蛋白质组拓扑结构和功能。

Analyzing proteome topology and function by automated multidimensional fluorescence microscopy.

作者信息

Schubert Walter, Bonnekoh Bernd, Pommer Ansgar J, Philipsen Lars, Böckelmann Raik, Malykh Yanina, Gollnick Harald, Friedenberger Manuela, Bode Marcus, Dress Andreas W M

机构信息

Molecular Pattern Recognition Research (MPRR) Group, Institute of Medical Neurobiology, Otto-von-Guericke-University Magdeburg, D-39120 Magdeburg, Germany.

出版信息

Nat Biotechnol. 2006 Oct;24(10):1270-8. doi: 10.1038/nbt1250. Epub 2006 Oct 1.

Abstract

Temporal and spatial regulation of proteins contributes to function. We describe a multidimensional microscopic robot technology for high-throughput protein colocalization studies that runs cycles of fluorescence tagging, imaging and bleaching in situ. This technology combines three advances: a fluorescence technique capable of mapping hundreds of different proteins in one tissue section or cell sample; a method selecting the most prominent combinatorial molecular patterns by representing the data as binary vectors; and a system for imaging the distribution of these protein clusters in a so-called toponome map. By analyzing many cell and tissue types, we show that this approach reveals rules of hierarchical protein network organization, in which the frequency distribution of different protein clusters obeys Zipf's law, and state-specific lead proteins appear to control protein network topology and function. The technology may facilitate the development of diagnostics and targeted therapies.

摘要

蛋白质的时空调节有助于其发挥功能。我们描述了一种用于高通量蛋白质共定位研究的多维显微机器人技术,该技术可在原位进行荧光标记、成像和漂白循环。这项技术结合了三项进展:一种能够在一个组织切片或细胞样本中绘制数百种不同蛋白质图谱的荧光技术;一种通过将数据表示为二元向量来选择最突出组合分子模式的方法;以及一个用于在所谓的拓扑组图谱中对这些蛋白质簇的分布进行成像的系统。通过分析多种细胞和组织类型,我们表明这种方法揭示了蛋白质网络层次组织的规则,其中不同蛋白质簇的频率分布服从齐普夫定律,并且状态特异性主导蛋白似乎控制着蛋白质网络的拓扑结构和功能。该技术可能有助于诊断和靶向治疗的发展。

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