Comprehensive and Reproducible Phosphopeptide Enrichment Using Iron Immobilized Metal Ion Affinity Chromatography (Fe-IMAC) Columns

Advances in phosphopeptide enrichment methods enable the identification of thousands of phosphopeptides from complex samples. Current offline enrichment approaches using TiO2, Ti, and Fe immobilized metal ion affinity chromatography (IMAC) material in batch or microtip format are widely used, but they suffer from irreproducibility and compromised selectivity. To address these shortcomings, we revisited the merits of performing phosphopeptide enrichment in an HPLC column format. We found that Fe-IMAC columns enabled the selective, comprehensive, and reproducible enrichment of phosphopeptides out of complex lysates. Column enrichment did not suffer from bead-to-sample ratio issues and scaled linearly from 100 mu g to 5 mg of digest. Direct measurements on an Orbitrap Velos mass spectrometer identified > 7500 unique phosphopeptides with 90% selectivity and good quantitative reproducibility (median cv of 15%). The number of unique phosphopeptides could be increased to more than 14,000 when the IMAC eluate was subjected to a subsequent hydrophilic strong anion exchange separation. Fe-IMAC columns outperformed Ti-IMAC and TiO2 in batch or tip mode in terms of phosphopeptide identification and intensity. Permutation enrichments of flow-throughs showed that all materials largely bound the same phosphopeptide species, independent of physicochemical characteristics. However, binding capacity and elution efficiency did profoundly differ among the enrichment materials and formats. As a result, the often quoted orthogonality of the materials has to be called into question. Our results strongly suggest that insufficient capacity, inefficient elution, and the stochastic nature of data-dependent acquisition in mass spectrometry are the causes of the experimentally observed complementarity. The Fe-IMAC enrichment workflow using an HPLC format developed here enables rapid and comprehensive phosphoproteome analysis that can be applied to a wide range of biological systems.