Informatics and Statistics for Analyzing 2-D Gel Electrophoresis Images

We describe a modification of two-dimensional (2-D) polyacrylamide gel electrophoresis that requires only a single gel to reproducibly detect differences between two protein samples. This was accomplished by fluorescently tagging the two samples with two different dyes, running them on the same 2-D gel, post-run fluorescence imaging of the gel into two images, and superimposing the images. The amine reactive dyes were designed to insure that proteins common to both samples have the same relative mobility regardless of the dye used to tag them. Thus, this technique, called difference gel electrophoresis (DIGE), circumvents the need to compare several 2-D gels. DIGE is reproducible, sensitive, and can detect an exogenous difference between two Drosophila embryo extracts at nanogram levels. Moreover, an inducible protein from E. coli was detected after 15 min of induction and identified using DIGE preparatively.

We describe an automated method for shotgun proteomics named multidimensional protein identification technology (MudPIT), which combines multidimensional liquid chromatography with electrospray ionization tandem mass spectrometry. The multidimensional liquid chromatography method integrates a strong cation-exchange (SCX) resin and reversed-phase resin in a biphasic column. We detail the improvements over a system described by Link et al. (Link, A. J.; Eng, J.; Schieltz, D. M.; Carmack, E.; Mize, G. J.; Morris, D. R.; Garvik, B. M.; Yates, J. R., III. Nat. Biotechnol. 1999, 17, 676-682) that separates and acquires tandem mass spectra for thousands of peptides. Peptides elute off the SCX phase by increasing pI, and elution off the SCX material is evenly distributed across an analysis. In addition, we describe the chromatographic benchmarks of MudPIT. MudPIT was reproducible within 0.5% between two analyses. Furthermore, a dynamic range of 10000 to 1 between the most abundant and least abundant proteins/peptides in a complex peptide mixture has been demonstrated. By improving sample preparation along with separations, the method improves the overall analysis of proteomes by identifying proteins of all functional and physical classes.