4.5 Article

TiSH - a robust and sensitive global phosphoproteomics strategy employing a combination of TiO2, SIMAC, and HILIC

期刊

JOURNAL OF PROTEOMICS
卷 75, 期 18, 页码 5749-5761

出版社

ELSEVIER
DOI: 10.1016/j.jprot.2012.08.007

关键词

Phosphoproteomics; Protein phosphorylation; Phosphopeptide enrichment; TiO2; Fractionation; Capillary HPLC HILIC

资金

  1. Lundbeck Foundation
  2. Novo Nordisk Foundation
  3. Novo Nordisk
  4. Sehested Hansen Foundation

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Large scale quantitative phosphoproteomics depends upon multidimensional strategies for peptide fractionation, phosphopeptide enrichment, and mass spectrometric analysis. Previously, most robust comprehensive large-scale phosphoproteomics strategies have relied on milligram amounts of protein. We have set up a multi-dimensional phosphoproteomics strategy combining a number of well-established enrichment and fraction methods: An initial TiO2 phosphopeptide pre-enrichment step is followed by post-fractionation using sequential elution from IMAC (SIMAC) to separate multi- and mono-phosphorylated peptides, and hydrophilic interaction liquid chromatography (HILIC) of the mono-phosphorylated peptides (collectively abbreviated TiSH). The advantages of the strategy include a high specificity and sample preparation workload reduction due to the TiO2 pre-enrichment step, as well as low adsorptive losses. We demonstrate the capability of this strategy by quantitative investigation of early interferon-gamma signaling in low quantities of insulinoma cells. We identified similar to 6600 unique phosphopeptides from 300 mu g of peptides/condition (22 unique phosphopeptides/mu g) in a duplex dimethyl labeling experiment, with an enrichment specificity>94%. When doing network analysis of putative phosphorylation changes it could be noted that the identified protein interaction network centered upon proteins known to be affected by the interferon-gamma pathway, thereby supporting the utility of this global phosphoproteomics strategy. This strategy thus shows great potential for interrogating signaling networks from low amounts of sample with high sensitivity and specificity. (C) 2012 Elsevier B.V. All rights reserved.

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