Schwarz Emanuel, Levin Yishai, Wang Lan, Leweke F Markus, Bahn Sabine
Institute of Biotechnology, University of Cambridge, Cambridge, UK.
J Sep Sci. 2007 Sep;30(14):2190-7. doi: 10.1002/jssc.200700190.
A major challenge of proteomic studies is the accurate quantitation of proteins. LC-MS/MS-based methods are especially suited for profiling proteins in large sample sets. In this setup, the measurement of relative protein abundance relies on the correct quantitation of tryptic peptides. However, peptide intensities often do not unequivocally reflect the abundance of the native proteins in the sample. In this study, we show that peptides that accurately reflect relative protein abundances in large-scale sample sets can be selected based on the correlation to each other. This strategy was tested in a well-controlled experiment using a set of spiked serum samples as well as 55 clinical serum samples from schizophrenia patients and healthy volunteers. The peptide correlation analysis we present here provides an intuitive and simple procedure to obtain a high quality quantitative information from proteomics data.
蛋白质组学研究的一个主要挑战是蛋白质的准确定量。基于液相色谱-串联质谱（LC-MS/MS）的方法特别适合对大量样本中的蛋白质进行分析。在这种设置下，相对蛋白质丰度的测量依赖于胰蛋白酶肽段的准确定量。然而，肽段强度往往不能明确反映样本中天然蛋白质的丰度。在本研究中，我们表明，可以基于肽段之间的相关性来选择能够准确反映大规模样本集中相对蛋白质丰度的肽段。该策略在一个严格控制的实验中进行了测试，使用了一组加标的血清样本以及来自精神分裂症患者和健康志愿者的55份临床血清样本。我们在此介绍的肽段相关性分析提供了一种直观且简单的程序，可从蛋白质组学数据中获得高质量的定量信息。
