Phospho-iTRAQ data article: Assessing isobaric labels for the large-scale study of phosphopeptide stoichiometry

• Main Authors: Pieter Glibert, Paulien Meert, Katleen Van Steendam, Lennart Martens, Dieter Deforce, Maarten Dhaenens
• Format: Article
• Language: English
• Published: Elsevier 2015-09-01
• Series: Data in Brief
• Online Access: http://www.sciencedirect.com/science/article/pii/S2352340915000542

The ability to distinguish between phosphopeptides of high and low stoichiometry is essential to discover the true extent of protein phosphorylation. We here extend the strategy whereby a peptide sample is briefly split in two identical parts and differentially labeled preceding the phosphatase treatment of one part (Pflieger et al., 2008. Mol. Cell. Proteomics, 7: 326–46 [1]; Wu et al., 2011. Nat. Methods, 8: 677–83 [2]). Our Phospho-iTRAQ method focuses on the unmodified counterparts of phosphorylated peptides, which thus circumvents the ionization, fragmentation, and phospho-enrichment difficulties that hamper quantitation of stoichiometry in most common phosphoproteomics methods. Since iTRAQ enables multiplexing, simultaneous (phospho)proteome comparison between internal replicates and multiple samples is possible. The technique was validated on multiple instrument platforms by adding internal standards of high stoichiometry to a complex lysate of control and EGF-stimulated HeLa cells. To demonstrate the flexibility of PhosphoiTRAQ with regards to the experimental setup and data mining, the proteome coverage was extended through gel fractionation, while an internal replicate measurement creates more stringent data analysis opportunities. The latter allows other researchers to set their own threshold for selecting potential phosphorylation events in the dataset presented here, depending on the biological question or corroboration under investigation. The latest developments in MS instrumentation promise to further increase the resolution of the stoichiometric measurement of Phospho-iTRAQ in the future. The data accompanying the manuscript on this approach (Glibert et al., 2015, J. Proteome Res. 14: 2015, 839–49 [5]) have been deposited to the ProteomeXchange with identifier PXD001574.