We developed a novel approach to enlarge phosphoproteome coverage using successive elution of phosphopeptides with various buffers in series from a single microcolumn packed with hydroxy acid-modified metal oxides, such as titania and zirconia. Elution conditions were investigated to maximize the recovery of phosphopeptides from three standard phosphoproteins. Secondary amines, such as piperidine and pyrrolidine, provided better efficiency than the conventional conditions using ammonium hydroxide and phosphate buffers. Furthermore, elution with these secondary amines provided unique phosphopeptides that were not eluted under the conventional conditions in the analysis of HeLa cell lysates. On the basis of these results, we fractionated phosphopeptides captured by a single metal oxide microcolumn using successive elution with 5% ammonium hydroxide solution, 5% piperidine solution and 5% pyrrolidine solution in series. We identified 1,803 nonredundant phosphopeptides from 100 microg of HeLa cells, which represented a 1.6-fold increase in phosphopeptide number and a 1.9-fold increase in total peak area of phosphopeptides in comparison with the results obtained under the conventional conditions. Since this approach is applicable to any single tip-based protocol without coupling with other enrichment methods, this simple strategy can be easily incorporated as an option into existing protocols for phosphopeptide enrichment, and would be suitable for high-throughput analysis in a parallel format.

We have developed an on-line automated system for phosphoproteome analysis using titania-based phosphopeptide enrichment followed by nanoLC-MS/MS. Titania beads were prepared by calcination of commercial chromatographic titania beads at 800˚C to convert the crystalline structure. The obtained rutile-form titania exhibited higher selectivity in phosphopeptide enrichment than commercial titania, even in the absence of a competitive chelating reagent for nonphosphopeptides. For phosphoproteome analysis of human cervical cancer HeLa cells, tryptic digests of the cell extracts were directly injected into this on-line system, and 696 non-redundant phosphopeptides with 671 unambiguously determined phosphorylation sites, derived from 512 phosphoproteins, were successfully identified. This is the first successful application of an on-line automated phosphoproteome analysis system to complex biological samples.

Personalized medicine allows the selection of treatments best suited to an individual patient and disease phenotype. To implement personalized medicine, effective tests predictive of response to treatment or susceptibility to adverse events are needed, and to develop a personalized medicine test, both high quality samples and reliable data are required. We review key features of state-of-the-art proteomic profiling and introduce further analytic developments to build a proteomic toolkit for use in personalized medicine approaches. The combination of novel analytical approaches in proteomic data generation, alignment and comparison permit translation of identified biomarkers into practical assays. We further propose an expanded statistical analysis to understand the sources of variability between individuals in terms of both protein expression and clinical variables and utilize this understanding in a predictive test.