MULTIDIMENSIONAL PEPTIDE/PROTEIN ANALYSIS AND IDENTIFICATION BY SEQUENCE DATABASE SEARCH USING MASS SPECTROMETRIC DATA

Abstract

In order to generate proteomics data that are suitable to validate protein identification in complex mixtures using multidimensional liquid-chromatography-mass spectrometry approaches, we implemented an offline two-dimensional liquid chromatography method combining strong cation-exchange- and ion-pair reversed-phase chromatography followed by electrospray ionization tandem mass spectrormetry (ESI-MS/MS) for the analysis of a bovine serum albumin digest. The fragment ion spectra generated by ESI-MS/MS were subsequently analyzed via MASCOT database search. The obtained identification data were evaluated in terms of quality of protein/peptide identification by means of score values, reproducibility of identification in replicate measurements, distribution of tryptic peptides among different fractions, and overall number of unique identified proteins/peptides.
Finally, we improved the trapping conditions in the second dimension by using a more hydrophobic amphiphile in the loading buffer. The improvement was demonstrated by comparison of the obtained identification data, such as number of identified peptides, cumulative mowse scores and reproducibility of identification.