Using ProtMAX to create high-mass-accuracy precursor alignments from label-free quantitative mass spectrometry data generated in shotgun proteomics experiments

被引:0
作者
Volker Egelhofer
Wolfgang Hoehenwarter
David Lyon
Wolfram Weckwerth
Stefanie Wienkoop
机构
[1] University of Vienna,Department of Molecular Systems Biology
[2] Present address: Proteome Analysis Research Group,undefined
[3] Leibniz Institute for Plant Biochemistry,undefined
[4] Halle,undefined
[5] Germany.,undefined
来源
Nature Protocols | 2013年 / 8卷
关键词
D O I
暂无
中图分类号
学科分类号
摘要
Recently, new software tools have been developed for improved protein quantification using mass spectrometry (MS) data. However, there are still limitations especially in high-sample-throughput quantification methods, and most of these relate to extensive computational calculations. The mass accuracy precursor alignment (MAPA) strategy has been shown to be a robust method for relative protein quantification. Its major advantages are high resolution, sensitivity and sample throughput. Its accuracy is data dependent and thus best suited for precursor mass-to-charge precision of ∼1 p.p.m. This protocol describes how to use a software tool (ProtMAX) that allows for the automated alignment of precursors from up to several hundred MS runs within minutes without computational restrictions. It comprises features for 'ion intensity count' and 'target search' of a distinct set of peptides. This procedure also includes the recommended MS settings for complex quantitative MAPA analysis using ProtMAX (http://www.univie.ac.at/mosys/software.html).
引用
收藏
页码:595 / 601
页数:6
相关论文
共 47 条
[1]  
Michalski A(2011)More than 100,000 detectable peptide species elute in single shotgun proteomics runs but the majority is inaccessible to data-dependent LC-MS/MS J. Proteome Res. 10 1785-1793
[2]  
Cox J(2011)Mass spectrometry-based proteomics using Q Exactive, a high-performance benchtop quadrupole Orbitrap mass spectrometer Mol. Cell. Proteomics 10 M111.011015-89
[3]  
Mann M(2011)Deep and highly sensitive proteome coverage by LC-MS/MS without prefractionation Mol. Cell Proteomics 10 M110.003699-1272
[4]  
Michalski A(2010)Label-free, normalized quantification of complex mass spectrometry data for proteomic analysis Nat. Biotechnol. 28 83-4201
[5]  
Thakur SS(2005)Exponentially modified protein abundance index (emPAI) for estimation of absolute protein amount in proteomics by the number of sequenced peptides per protein Mol. Cell Proteomics 4 1265-124
[6]  
Griffin NM(2004)A model for random sampling and estimation of relative protein abundance in shotgun proteomics Anal. Chem. 76 4193-18933
[7]  
Ishihama Y(2007)Absolute protein expression profiling estimates the relative contributions of transcriptional and translational regulation Nat. Biotechnol. 25 117-516
[8]  
Liu H(2006)Quantitative proteomic analysis of distinct mammalian Mediator complexes using normalized spectral abundance factors Proc. Natl. Acad. Sci. USA 103 18928-342
[9]  
Sadygov RG(2010)Quantitation in mass-spectrometry-based proteomics Annu. Rev. Plant Biol. 61 491-156
[10]  
Yates JR(2011)Global quantification of mammalian gene expression control Nature 473 337-941