Off-Line High-pH Reversed-Phase Fractionation for In-Depth Phosphoproteomics

Research output: Contribution to journalJournal articleResearchpeer-review

Documents

  • pr500893m

    Final published version, 527 KB, PDF document

Protein phosphorylation is an important post-translational modification (PTM) involved in embryonic development, adult homeostasis, and disease. Over the past decade, several advances have been made in liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based technologies to identify thousands of phosphorylation sites. However, in-depth phosphoproteomics often require off-line enrichment and fractionation techniques. In this study, we provide a detailed analysis of the physicochemical characteristics of phosphopeptides, which have been fractionated by off-line high-pH chromatography (HpH) before subsequent titanium dioxide (TiO2) enrichment and LC-MS/MS analysis. Our results demonstrate that HpH is superior to standard strong-cation exchange (SCX) fractionation in the total number of phosphopeptides detected when analyzing the same number of fractions by identical LC-MS/MS gradients. From 14 HpH fractions, we routinely identified over 30 000 unique phosphopeptide variants, which is more than twice the number of that obtained from SCX fractionation. HpH chromatography displayed an exceptional ability to fractionate singly phosphorylated peptides, with minor benefits for doubly phosphorylated peptides over that with SCX. Further optimizations in the pooling and concatenation strategy increased the total number of multiphosphorylated peptides detected after HpH fractionation. In conclusion, we provide a basic framework and resource for performing in-depth phosphoproteome studies utilizing off-line basic reversed-phased fractionation. Raw data is available at ProteomeXchange (PXD001404).

Original languageEnglish
JournalJournal of Proteome Research
Volume13
Issue number12
Pages (from-to)6176-86
Number of pages11
ISSN1535-3893
DOIs
Publication statusPublished - 4 Nov 2014

Number of downloads are based on statistics from Google Scholar and www.ku.dk


No data available

ID: 127246133