Automated, reproducible, titania-based phosphopeptide enrichment strategy for label-free quantitative phosphoproteomics.

Journal Article (Journal Article)

An automated phosphopeptide enrichment strategy is described using titanium dioxide (TiO2)-packed, fused silica capillaries for use with liquid chromatography (LC)-mass spectrometry (MS)/MS-based, label-free proteomics workflows. To correlate an optimum peptide:TiO2 loading ratio between different particle types, the ratio of phenyl phosphate-binding capacities was used. The optimum loading for the column was then verified through replicate enrichments of a range of quantities of digested rat brain tissue cell lysate. Fractions were taken during sample loading, multiple wash steps, and the elution steps and analyzed by LC-MS/MS to gauge the efficiency and reproducibility of the enrichment. Greater than 96% of the total phosphopeptides were detected in the elution fractions, indicating efficient trapping of the phosphopeptides on the first pass of enrichment. The quantitative reproducibility of the automated setup was also improved greatly with phosphopeptide intensities from replicate enrichments exhibiting a median coefficient of variation (CV) of 5.8%, and 80% of the identified phosphopeptides had CVs below 11.1%, while maintaining >85% specificity. By providing this high degree of analytical reproducibility, this method allows for label-free phosphoproteomics over large sample sets with complex experimental designs (multiple biological conditions, multiple biological replicates, multiple time-points, etc.), including large-scale clinical cohorts.

Full Text

Duke Authors

Cited Authors

  • Richardson, BM; Soderblom, EJ; Thompson, JW; Moseley, MA

Published Date

  • April 2013

Published In

Volume / Issue

  • 24 / 1

Start / End Page

  • 8 - 16

PubMed ID

  • 23542237

Pubmed Central ID

  • PMC3533261

Electronic International Standard Serial Number (EISSN)

  • 1943-4731

Digital Object Identifier (DOI)

  • 10.7171/jbt.13-2401-002


  • eng

Conference Location

  • United States