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

TitleMultiple reaction monitoring for robust quantitative proteomic analysis of cellular signaling networks.
Publication TypeJournal Article
Year of Publication2007
AuthorsWolf-Yadlin, A, Hautaniemi, S, Lauffenburger, DA, White, FM
JournalProc Natl Acad Sci U S A
Date Published2007 Apr 3
KeywordsCell Culture Techniques, Cells, Cultured, Cluster Analysis, Endothelium, Vascular, Epidermal Growth Factor, Epithelial Cells, Female, Humans, Kinetics, Mammary Glands, Human, Mass Spectrometry, Peptides, Phosphorylation, Proteome, Proteomics, Reproducibility of Results, Sequence Analysis, Protein, Signal Transduction, Tyrosine

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.

Alternate JournalProc. Natl. Acad. Sci. U.S.A.
PubMed ID17389395
PubMed Central IDPMC1851582
Grant ListCA96504 / CA / NCI NIH HHS / United States
P50-GM68762 / GM / NIGMS NIH HHS / United States
R33-AI65354 / AI / NIAID NIH HHS / United States