UZH ETH Zurich, Functional Genomics Center Zurich, Winterthurerstrasse 190, CH-8057 Zurich, Switzerland.
J Proteomics. 2010 Aug 5;73(9):1740-6. doi: 10.1016/j.jprot.2010.05.011. Epub 2010 May 31.
Tandem mass spectrometry allows for fast protein identification in a complex sample. As mass spectrometers get faster, more sensitive and more accurate, methods were devised by many academic research groups and commercial suppliers that allow protein research also in quantitative respect. Since label-free methods are an attractive alternative to labeling approaches for proteomics researchers seeking for accurate quantitative results we evaluated several open-source analysis tools in terms of performance on two reference data sets, explicitly generated for this purpose. In this paper we present an implementation, T3PQ (Top 3 Protein Quantification), of the method suggested by Silva and colleagues for LC-MS(E) applications and we demonstrate its applicability to data generated on FT-ICR instruments acquiring in data dependent acquisition (DDA) mode. In order to validate this method and to show its usefulness also for absolute protein quantification, we generated a reference data set of a sample containing four different proteins with known concentrations. Furthermore, we compare three other label-free quantification methods using a complex biological sample spiked with a standard protein in defined concentrations. We evaluate the applicability of these methods and the quality of the results in terms of robustness and dynamic range of the spiked-in protein as well as other proteins also detected in the mixture. We discuss drawbacks of each method individually and consider crucial points for experimental designs. The source code of our implementation is available under the terms of the GNU GPLv3 and can be downloaded from sourceforge (http://fqms.svn.sourceforge.net/svnroot/fqms). A tarball containing the data used for the evaluation is available on the FGCZ web server (http://fgcz-data.uzh.ch/public/T3PQ.tgz).
串联质谱允许在复杂样品中快速鉴定蛋白质。随着质谱仪变得更快、更灵敏和更准确,许多学术研究小组和商业供应商设计了方法,允许在定量方面也进行蛋白质研究。由于无标记方法是对寻求准确定量结果的蛋白质组学研究人员具有吸引力的替代标记方法,我们根据性能评估了几个开源分析工具在两个参考数据集上,明确为此目的生成。在本文中,我们提出了一种 LC-MS(E) 应用 Silva 等人建议的方法的实现,即 T3PQ(Top 3 Protein Quantification),并证明了其在 FT-ICR 仪器上以数据依赖采集(DDA)模式生成的数据中的适用性。为了验证该方法并证明其也可用于绝对蛋白质定量,我们生成了一个包含四个具有已知浓度的不同蛋白质的样本的参考数据集。此外,我们使用在定义浓度下添加标准蛋白质的复杂生物样本比较了三种其他无标记定量方法。我们根据添加的蛋白质以及混合物中也检测到的其他蛋白质的稳健性和动态范围来评估这些方法的适用性和结果的质量。我们单独讨论了每种方法的缺点,并考虑了实验设计的关键点。我们的实现的源代码根据 GNU GPLv3 的条款提供,可以从 sourceforge(http://fqms.svn.sourceforge.net/svnroot/fqms)下载。用于评估的包含数据的 tarball 可在 FGCZ 网络服务器(http://fgcz-data.uzh.ch/public/T3PQ.tgz)上获得。