Immobilized pH gradient isoelectric focusing as a first-dimension separation in shotgun proteomics

Abstract

Shotgun proteomics, where a tryptic digest of a complex proteome sample is directly analyzed by either single dimensional or multidimensional liquid chromatography tandem mass spectrometry, has gained acceptance in the proteomics community at large and is widely used in core facilities. Here we review the development in our laboratory of an alternative first-dimension separation technique for shotgun proteomics, immobilized pH gradient isoelectric focusing (IPG-IEF). The key advantages of the technology over other multidimensional separation formats (simplicity, high resolution, and high sensitivity) are discussed. The concept of using peptide pI to filter large shotgun proteomics datasets generated by the IPG-IEF technique to minimize false positives and negatives is also introduced. Finally, an account of the comparison of the technique with the established gold standard for multidimensional separation of peptides, strong cation exchange chromatography, is presented, along with the prospects for the use of peptide pI along with accurate mass measurement for the identification of peptides.

FIGURE 1

The overall strategy for the integration of immobilized pH gradient isoelectric focusing (IPG-IEF) in shotgun proteomics. IEF, isoelectric focusing; K, lysine; R, arginine.

FIGURE 2

Theoretical pI of peptides from the E. coli proteome as a function of mass for no missed cleavages of trypsin (upper panel) and one missed cleavage of trypsin (lower panel). (Reproduced with permission from J Proteome Res, 2004;3:112–119, Copyright © 2004 American Chemical Society.)

FIGURE 3

Three-dimensional plot of data obtained from a wide range (pH 3–10) IPG-IEF separation of the soluble E. coli proteome as a function of number of peptides identified, IPG fraction number, and mean peptide pI. (Reproduced with permission from Electrophoresis 2004;25:936–945. Copyright © 2004, John Wiley and Sons.)

FIGURE 4

The use of pI as a filtering criterion. The graphs depict all protein hits from SEQUEST searches of an nrIPG-IEF shotgun proteomics analysis of the R. norvigicus testicular proteome, plotted as a function of SEQUEST cross-correlation score (X_corr) and pI. A: Hits obtained from searching the forward orientation of the database only. B: Hits obtained when the reversed database approach was used to determine X_corr cutoffs for a peptide false positive identification rate of ~1%. Reversed database hits are shown in red. C: Application of the pI 3.5–4.5 filter to the data, showing that the X_corr cutoffs can be relaxed while maintaining a false positive peptide identification rate of ~1%. (Figure based on data originally published in reference .)

FIGURE 5

Graph of the cumulative number of unique proteins identified from a sample of R. norvigicus testis lysate as a function of fraction number for IPG-IEF (triangles) and SCX (circles). Note that in the SCX experiment, although 128 fractions were collected, every other fraction was analyzed to minimize peptide redundancy. (Figure based on data originally published in reference .)

FIGURE 6

Venn diagram depicting the number of unique proteins and peptides identified by nrIEF-IPG and SCX experiments on the R. norvigicus testicular proteome. Note that approximately 75% of the “unique” peptides found via SCX were greater than pI 4.6. SCX, strong cation exchange.