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Implementation and evaluation of relative and absolute quantification in shotgun proteomics with label-free methods.

机译:用无标签方法实现和评估shot弹枪蛋白质组学中相对和绝对定量。

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摘要

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).
机译:串联质谱可以快速鉴定复杂样品中的蛋白质。随着质谱仪变得更快,更灵敏,更准确,许多学术研究小组和商业供应商设计了方法,使蛋白质研究也可以在定量方面进行。由于无标签方法是蛋白质组学研究人员寻求准确定量结果的一种有吸引力的替代方法,因此我们针对两个参考数据集的性能评估了几种开源分析工具,这些工具是专门为此目的而生成的。在本文中,我们介绍了席尔瓦及其同事针对LC-MS(E)应用建议的方法的一种实现方法T3PQ(前3种蛋白质定量),我们展示了其对数据依赖型采集中FT-ICR仪器生成的数据的适用性(DDA)模式。为了验证该方法并显示其在绝对蛋白质定量分析中的有用性,我们生成了包含四个浓度已知的不同蛋白质的样品的参考数据集。此外,我们比较了使用复杂生物样品加标定浓度的标准蛋白质的其他三种无标记定量方法。我们根据掺入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,评估了这些方法的适用性和结果的质量。我们分别讨论每种方法的缺点,并考虑实验设计的关键点。我们的实现的源代码在GNU GPLv3的条款下可用,并且可以从sourceforge(http://fqms.svn.sourceforge.net/svnroot/fqms)下载。可以在FGCZ Web服务器(http://fgcz-data.uzh.ch/public/T3PQ.tgz)上找到包含用于评估的数据的压缩包。

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