Lange Vinzenz, Malmström Johan A, Didion John, King Nichole L, Johansson Björn P, Schäfer Juliane, Rameseder Jonathan, Wong Chee-Hong, Deutsch Eric W, Brusniak Mi-Youn, Bühlmann Peter, Björck Lars, Domon Bruno, Aebersold Ruedi
Institute of Molecular Systems Biology, ETH Zurich, Zurich 8093, Switzerland.
Mol Cell Proteomics. 2008 Aug;7(8):1489-500. doi: 10.1074/mcp.M800032-MCP200. Epub 2008 Apr 13.
In many studies, particularly in the field of systems biology, it is essential that identical protein sets are precisely quantified in multiple samples such as those representing differentially perturbed cell states. The high degree of reproducibility required for such experiments has not been achieved by classical mass spectrometry-based proteomics methods. In this study we describe the implementation of a targeted quantitative approach by which predetermined protein sets are first identified and subsequently quantified at high sensitivity reliably in multiple samples. This approach consists of three steps. First, the proteome is extensively mapped out by multidimensional fractionation and tandem mass spectrometry, and the data generated are assembled in the PeptideAtlas database. Second, based on this proteome map, peptides uniquely identifying the proteins of interest, proteotypic peptides, are selected, and multiple reaction monitoring (MRM) transitions are established and validated by MS2 spectrum acquisition. This process of peptide selection, transition selection, and validation is supported by a suite of software tools, TIQAM (Targeted Identification for Quantitative Analysis by MRM), described in this study. Third, the selected target protein set is quantified in multiple samples by MRM. Applying this approach we were able to reliably quantify low abundance virulence factors from cultures of the human pathogen Streptococcus pyogenes exposed to increasing amounts of plasma. The resulting quantitative protein patterns enabled us to clearly define the subset of virulence proteins that is regulated upon plasma exposure.
在许多研究中，尤其是在系统生物学领域，至关重要的是要在多个样本中精确量化相同的蛋白质组，例如那些代表不同扰动细胞状态的样本。基于经典质谱的蛋白质组学方法尚未实现此类实验所需的高度可重复性。在本研究中，我们描述了一种靶向定量方法的实施，通过该方法，首先识别预定的蛋白质组，随后在多个样本中以高灵敏度可靠地进行量化。该方法包括三个步骤。首先，通过多维分级分离和串联质谱对蛋白质组进行广泛映射，并将生成的数据组装到PeptideAtlas数据库中。其次，基于此蛋白质组图谱，选择唯一识别感兴趣蛋白质的肽段，即蛋白型肽段，并通过MS2谱图采集建立和验证多反应监测（MRM）转换。本研究中描述的一套软件工具TIQAM（通过MRM进行定量分析的靶向鉴定）支持肽段选择、转换选择和验证的这一过程。第三，通过MRM对选定的目标蛋白质组在多个样本中进行量化。应用这种方法，我们能够可靠地量化来自暴露于越来越多血浆的人类病原体化脓性链球菌培养物中的低丰度毒力因子。所得的定量蛋白质模式使我们能够清楚地定义在血浆暴露时受到调节的毒力蛋白子集。
