Mueller Lukas N, Brusniak Mi-Youn, Mani D R, Aebersold Ruedi
Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland.
J Proteome Res. 2008 Jan;7(1):51-61. doi: 10.1021/pr700758r. Epub 2008 Jan 4.
Over the past decade, a series of experimental strategies for mass spectrometry based quantitative proteomics and corresponding computational methodology for the processing of the resulting data have been generated. We provide here an overview of the main quantification principles and available software solutions for the analysis of data generated by liquid chromatography coupled to mass spectrometry (LC-MS). Three conceptually different methods to perform quantitative LC-MS experiments have been introduced. In the first, quantification is achieved by spectral counting, in the second via differential stable isotopic labeling, and in the third by using the ion current in label-free LC-MS measurements. We discuss here advantages and challenges of each quantification approach and assess available software solutions with respect to their instrument compatibility and processing functionality. This review therefore serves as a starting point for researchers to choose an appropriate software solution for quantitative proteomic experiments based on their experimental and analytical requirements.
在过去十年中，已经产生了一系列基于质谱的定量蛋白质组学实验策略以及用于处理所得数据的相应计算方法。在此，我们概述了用于分析液相色谱-质谱联用（LC-MS）产生的数据的主要定量原理和可用软件解决方案。已经引入了三种概念上不同的进行定量LC-MS实验的方法。第一种方法是通过谱图计数实现定量，第二种方法是通过差异稳定同位素标记，第三种方法是在无标记LC-MS测量中使用离子流。我们在此讨论每种定量方法的优点和挑战，并根据仪器兼容性和处理功能评估可用软件解决方案。因此，本综述可作为研究人员根据其实验和分析要求为定量蛋白质组学实验选择合适软件解决方案的起点。
