RATIONALE: Despite advances in mass spectrometry (MS)-based identification, effective phosphopeptide enrichment is a prerequisite towards comprehensive phosphoproteomic analysis. Based on the different binding affinities and coordination geometries of the Ti(4+) and Fe(3+) ions with the phosphate group, we report a complementary metal-directed immobilized metal ion affinity chromatography (IMAC) method to increase the identification coverage of a phosphoproteome. METHODS: Phosphopeptides from standard phosphoproteins and Raji B cells were enriched from Ti(4+)-IMAC and Fe(3+)-IMAC methods, followed by matrix-assisted laser desorption/ionization (MALDI) MS and Orbitrap MS analysis. Optimal enrichment specificity was achieved by selection of acid structure/concentration and organic solvent to compete with non-phosphopeptides. The effect of the metal ion and the chelating compound was evaluated by the comparison of the characteristics of enriched phosphopeptides between Ti(4+)-IMAC, Fe(3+)-IMAC and TiO(2) methods. RESULTS: To address the low enrichment specificity of the Ti(4+)-IMAC method, a simple one-step acid/solvent controlled IMAC method was developed with significantly improved specificity (88%) and recovery (93%). The most striking discovery is that the optimal Ti(4+)-IMAC and Fe(3+)-IMAC methods have low overlapping percentage (10%) among the 2905 enriched phosphopeptides from Raji cells, comprised of the distinct characteristics including hydrophobicity, amino acid compositions, and frequency of multiple phosphorylation of the phosphopeptides. CONCLUSIONS: The reported Fe(3+)-IMAC and Ti(4+)-IMAC methods can complementarily enrich acidic and basic phosphopeptides to effectively increase the identification coverage of an heterogeneous phosphoproteome (twice than the single approach). Given the reproducibility and low sample loss, the combination of our enrichment strategy with a quantitative technique could be feasible for quantitative phosphoproteomics.
RATIONALE: Despite advances in mass spectrometry (MS)-based identification, effective phosphopeptide enrichment is a prerequisite towards comprehensive phosphoproteomic analysis. Based on the different binding affinities and coordination geometries of the Ti(4+) and Fe(3+) ions with the phosphate group, we report a complementary metal-directed immobilized metal ion affinity chromatography (IMAC) method to increase the identification coverage of a phosphoproteome. METHODS: Phosphopeptides from standard phosphoproteins and Raji B cells were enriched from Ti(4+)-IMAC and Fe(3+)-IMAC methods, followed by matrix-assisted laser desorption/ionization (MALDI) MS and Orbitrap MS analysis. Optimal enrichment specificity was achieved by selection of acid structure/concentration and organic solvent to compete with non-phosphopeptides. The effect of the metal ion and the chelating compound was evaluated by the comparison of the characteristics of enriched phosphopeptides between Ti(4+)-IMAC, Fe(3+)-IMAC and TiO(2) methods. RESULTS: To address the low enrichment specificity of the Ti(4+)-IMAC method, a simple one-step acid/solvent controlled IMAC method was developed with significantly improved specificity (88%) and recovery (93%). The most striking discovery is that the optimal Ti(4+)-IMAC and Fe(3+)-IMAC methods have low overlapping percentage (10%) among the 2905 enriched phosphopeptides from Raji cells, comprised of the distinct characteristics including hydrophobicity, amino acid compositions, and frequency of multiple phosphorylation of the phosphopeptides. CONCLUSIONS: The reported Fe(3+)-IMAC and Ti(4+)-IMAC methods can complementarily enrich acidic and basic phosphopeptides to effectively increase the identification coverage of an heterogeneous phosphoproteome (twice than the single approach). Given the reproducibility and low sample loss, the combination of our enrichment strategy with a quantitative technique could be feasible for quantitative phosphoproteomics.
Authors: Michael Adams; Jennifer R Fleming; Eva Riehle; Tiankun Zhou; Thomas Zacharchenko; Marija Markovic; Olga Mayans Journal: Protein J Date: 2019-04 Impact factor: 2.371
Authors: Guolin Zhang; Hannah Scarborough; Jihye Kim; Andrii I Rozhok; Yian Ann Chen; Xiaohui Zhang; Lanxi Song; Yun Bai; Bin Fang; Richard Z Liu; John Koomen; Aik Choon Tan; James Degregori; Eric B Haura Journal: Sci Signal Date: 2016-10-18 Impact factor: 8.192
Authors: Barbara Sivakova; Jan Jurcik; Veronika Lukacova; Tomas Selicky; Ingrid Cipakova; Peter Barath; Lubos Cipak Journal: Int J Mol Sci Date: 2021-02-09 Impact factor: 5.923