Mining Phosphopeptide Signals in Liquid Chromatography-Mass Spectrometry Data for Protein Phosphorylation Analysis

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• 作者：Hsin-Yi Wu ; Vincent Shin-Mu Tseng ; Pao-Chi Liao
• 刊名：Journal of Proteome Research
• 出版年：2007
• 出版时间：May 2007
• 年：2007
• 卷：6
• 期：5
• 页码：1812 - 1821
• 全文大小：277K
• 年卷期：v.6,no.5(May 2007)
• ISSN：1535-3907

文摘

Protein phosphorylation is a key post-translational modification that governs biological processes.Despite the fact that a number of analytical strategies have been exploited for the characterization ofprotein phosphorylation, the identification of protein phosphorylation sites is still challenging. Weproposed here an alternative approach to mine phosphopeptide signals generated from a mixture ofproteins when liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis is involved.The approach combined dephosphorylation reaction, accurate mass measurements from a quadrupole/time-of-flight mass spectrometer, and a computing algorithm to differentiate possible phosphopeptidesignals obtained from the LC-MS analyses by taking advantage of the mass shift generated by alkalinephosphatase treatment. The retention times and m/z values of these selected LC-MS signals wereused to facilitate subsequent LC-MS/MS experiments for phosphorylation site determination. Unlikecommonly used neutral loss scan experiments for phosphopeptide detection, this strategy may notbias against tyrosine-phosphorylated peptides. We have demonstrated the applicability of this strategyto sequence more, in comparison with conventional data-dependent LC-MS/MS experiments, phosphopeptides in a mixture of - and -caseins. The analytical scheme was applied to characterize thenasopharyngeal carcinoma (NPC) cellular phosphoproteome and yielded 221 distinct phosphorylationsites. Our data presented in this paper demonstrated the merits of computation in mining phosphopeptide signals from a complex mass spectrometric data set.