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细胞信号传导质粒文库联盟:用于蛋白质定位研究和信号通路分析的灵活资源。

The alliance for cellular signaling plasmid collection: a flexible resource for protein localization studies and signaling pathway analysis.

作者信息

Zavzavadjian Joelle R, Couture Sam, Park Wei Sun, Whalen James, Lyon Stephen, Lee Genie, Fung Eileen, Mi Qingli, Liu Jamie, Wall Estelle, Santat Leah, Dhandapani Kavitha, Kivork Christine, Driver Adrienne, Zhu Xiaocui, Chang Mi Sook, Randhawa Baljinder, Gehrig Elizabeth, Bryan Heather, Verghese Mary, Maer Andreia, Saunders Brian, Ning Yuhong, Subramaniam Shankar, Meyer Tobias, Simon Melvin I, O'Rourke Nancy, Chandy Grischa, Fraser Iain D C

机构信息

Alliance for Cellular Signaling, California Institute of Technology, CA 94305, USA.

出版信息

Mol Cell Proteomics. 2007 Mar;6(3):413-24. doi: 10.1074/mcp.M600437-MCP200. Epub 2006 Dec 27.

Abstract

Cellular responses to inputs that vary both temporally and spatially are determined by complex relationships between the components of cell signaling networks. Analysis of these relationships requires access to a wide range of experimental reagents and techniques, including the ability to express the protein components of the model cells in a variety of contexts. As part of the Alliance for Cellular Signaling, we developed a robust method for cloning large numbers of signaling ORFs into Gateway entry vectors, and we created a wide range of compatible expression platforms for proteomics applications. To date, we have generated over 3000 plasmids that are available to the scientific community via the American Type Culture Collection. We have established a website at www.signaling-gateway.org/data/plasmid/ that allows users to browse, search, and blast Alliance for Cellular Signaling plasmids. The collection primarily contains murine signaling ORFs with an emphasis on kinases and G protein signaling genes. Here we describe the cloning, databasing, and application of this proteomics resource for large scale subcellular localization screens in mammalian cell lines.

摘要

细胞对随时间和空间变化的输入的反应,由细胞信号网络各组分之间的复杂关系所决定。分析这些关系需要使用多种实验试剂和技术,包括在各种背景下表达模型细胞蛋白质组分的能力。作为细胞信号联盟的一部分,我们开发了一种强大的方法,可将大量信号开放阅读框克隆到Gateway入门载体中,并且我们为蛋白质组学应用创建了多种兼容的表达平台。到目前为止,我们已生成了3000多个质粒,可通过美国模式培养物集存库提供给科学界。我们在www.signaling - gateway.org/data/plasmid/建立了一个网站,用户可以浏览、搜索和比对细胞信号联盟的质粒。该文库主要包含小鼠信号开放阅读框,重点是激酶和G蛋白信号基因。在此,我们描述了这种蛋白质组学资源在哺乳动物细胞系大规模亚细胞定位筛选中的克隆、数据库建立及应用。

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