Multiple reaction monitoring for robust quantitative proteomic analysis of cellular signaling networks

被引:391
作者
Wolf-Yadlin, Alejandro
Hautaniemi, Sampsa
Lauffenburger, Douglas A.
White, Forest M.
机构
[1] MIT, Biol Engn Div, Cambridge, MA 02139 USA
[2] MIT, Canc Res Ctr, Cambridge, MA 02139 USA
[3] Univ Helsinki, Inst Biomed, Computat Syst Biol Lab, FIN-00014 Helsinki, Finland
[4] Univ Helsinki, Genome Scale Biol Res Program, FIN-00014 Helsinki, Finland
关键词
epidermal growth factor receptor; mass spectrometry; signal transduction; tyrosine phosphorylation;
D O I
10.1073/pnas.0608638104
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Although recent developments in MS have enabled the identification and quantification of hundreds of phosphorylation sites from a given biological sample, phosphoproteome analysis by MS has been plagued by inconsistent reproducibility arising from automated selection of precursor ions for fragmentation, identification, and quantification. To address this challenge, we have developed a new MS-based strategy, based on multiple reaction monitoring of stable isotope-labeled peptides, that enables highly reproducible quantification of hundreds of nodes (phosphorylation sites) within a signaling network and across multiple conditions simultaneously. We have applied this strategy to quantify temporal phosphorylation profiles of 222 tyrosine phosphorylated peptides across seven time points following EGF treatment, including 31 tyrosine phosphorylation sites not previously known to be regulated by EGF stimulation. With this approach, 88% of the signaling nodes were reproducibly quantified in four analyses, as compared with only 34% by typical information-dependent analysis. As a result of the improved reproducibility, full temporal phosphorylation profiles were generated for an additional 104 signaling nodes with the multiple reaction monitoring strategy, an 88% increase in our coverage of the signaling network. This method is broadly applicable to multiple signaling networks and to a variety of samples, including quantitative analysis of signaling networks in clinical samples. Using this approach, it should now be possible to routinely monitor the phosphorylation status of hundreds of nodes across multiple biological conditions.
引用
收藏
页码:5860 / 5865
页数:6
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