Raijmakers Reinout, Berkers Celia R, de Jong Annemieke, Ovaa Huib, Heck Albert J R, Mohammed Shabaz
Biomolecular Mass Spectrometry and Proteomics Group, Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Sorbonnelaan 16, 3584 CA Utrecht, The Netherlands.
Mol Cell Proteomics. 2008 Sep;7(9):1755-62. doi: 10.1074/mcp.M800093-MCP200. Epub 2008 Jun 4.
Quantitation of protein abundance is a vital component in the proteomic analysis of biological systems, which can be achieved by differential stable isotopic labeling. To analyze tissue-derived samples, the isotopic labeling can be performed using chemical labeling of the peptides post-digestion. Standard chemical labeling procedures often require many manual sample handling steps, reducing the accuracy of measurements. Here, we describe a fully automated, online (in nanoLC columns), labeling procedure, which allows protein quantitation using differential isotopic dimethyl labeling of peptide N termini and lysine residues. We show that the method allows reliable quantitation over a wide dynamic range and can be used to quantify differential protein abundances in lysates and, more targeted, differences in composition between purified protein complexes. We apply the method to determine the differences in composition between bovine liver and spleen 20 S core proteasome complexes. We find that although all catalytically active immunoproteasome subunits were up-regulated in spleen (compared with liver), only one of the normal catalytic subunits was down-regulated, suggesting that the tissue-specific immunoproteasome assembly is more diverse than previously assumed.
蛋白质丰度的定量分析是生物系统蛋白质组学分析的重要组成部分,可通过差异稳定同位素标记实现。为了分析组织来源的样本,可在肽段消化后使用化学标记法进行同位素标记。标准的化学标记程序通常需要许多手动样本处理步骤,从而降低了测量的准确性。在此,我们描述了一种全自动的在线(在纳流液相色谱柱中)标记程序,该程序允许使用肽段N端和赖氨酸残基的差异同位素二甲基标记进行蛋白质定量。我们表明,该方法能够在很宽的动态范围内进行可靠的定量分析,可用于定量裂解物中差异蛋白质丰度,更具针对性地定量纯化蛋白质复合物之间的组成差异。我们应用该方法来确定牛肝脏和脾脏20S核心蛋白酶体复合物之间的组成差异。我们发现,尽管脾脏中所有具有催化活性的免疫蛋白酶体亚基均上调(与肝脏相比),但只有一个正常催化亚基下调,这表明组织特异性免疫蛋白酶体组装比以前认为的更加多样化。