Related Experiment Video
Updated: May 11, 2026

09:16
A Spin-Tip Enrichment Strategy for Simultaneous Analysis of N-Glycopeptides and Phosphopeptides from Human Pancreatic Tissues
Published on: May 4, 2022
Phosphopeptide enrichment using offline titanium dioxide columns for phosphoproteomics.
1National Center for Toxicological Research, FDA, Jefferson, AR, USA.
Methods in Molecular Biology (Clifton, N.J.)
|April 30, 2013
Summary
This study presents an optimized titanium dioxide (TiO2) column method for enriching phosphopeptides. This technique enhances cancer biomarker discovery in phosphoproteomics by improving specificity and recovery rates.
Area of Science:
- Proteomics
- Biochemistry
- Analytical Chemistry
Background:
- Phosphoprotein and phosphopeptide identification is crucial for cancer biomarker discovery.
- Low stoichiometric phosphorylation necessitates enrichment before mass spectrometry.
- Titanium dioxide (TiO2) is a common, effective material for phosphopeptide enrichment.
Purpose of the Study:
- To describe an optimized offline phosphopeptide enrichment protocol using TiO2 columns.
- To improve the efficiency and specificity of phosphopeptide enrichment for biomarker discovery.
- To facilitate large-scale phosphoproteomic analysis from various sample amounts.
Main Methods:
- Utilized TiO2 columns for offline phosphopeptide enrichment from proteome lysates.
- Employed acidic conditions for peptide loading and washing with aqueous, organic, and ammonium glutamate (NH4Glu) buffers.
- Eluted phosphopeptides using a high pH ammonia solution.
Main Results:
- Achieved a high phosphopeptide recovery rate of 84%.
- Demonstrated significant reduction in nonspecific binding through the use of NH4Glu.
- Optimized the protocol for sample amounts ranging from sub-milligram to milligrams.
Conclusions:
- The described TiO2 column enrichment method is efficient and specific for phosphopeptide analysis.
- This protocol supports large-scale phosphoproteomic studies and phosphoprotein biomarker discovery.
- The method offers a robust approach for identifying potential cancer biomarkers.

