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  • Title: 2D gel proteomics: an approach to study age-related differences in protein abundance or isoform complexity in biological samples.
    Author: Kim H, Eliuk S, Deshane J, Meleth S, Sanderson T, Pinner A, Robinson G, Wilson L, Kirk M, Barnes S.
    Journal: Methods Mol Biol; 2007; 371():349-91. PubMed ID: 17634592.
    Abstract:
    This chapter describes protocols for two-dimensional (2D) gel electrophoresis (isoelectric focusing [IEF] followed by sodium-dodecyl sulfate (SDS)-polyacrylamide gel electro-phoresis [PAGE]), staining of gels with the fluorescent dye Sypro Ruby, 2D gel image analysis, peptide mass fingerprint (PMF) analysis using matrix-assisted laser desorption ionization (MALDI)-time-of-flight (TOF) mass spectrometry (MS), liquid chromatography (LC)-tandem mass spectrometry (MS/MS), Western blot analysis of protein oxidations, and mass spectrometric mapping of sites of protein oxidations. Many of these methods were used to identify proteins affected in rat brain following ingestion of grape seed extract (GSE), a dietary supplement touted for anti-oxidant activity. Although beneficial actions in cell and animal models of chronic disease have been described for GSE, it has not been shown whether specific proteins were affected, or the nature of the effects. Applying 2D gel proteomics technology allowed discovery of proteins targeted by GSE without a priori knowledge of which one(s) might be affected. The newer 2D blue native (BN) electrophoresis methodology, which resolves protein complexes in a nondenaturing first dimension and then the components of these complexes in a denaturing second dimension, is discussed as a complementary approach. Analysis of protein oxidations and protein-protein interactions have special relevance to aging-related research, since oxidative stress and altered protein interactions may be at the heart of aging-related diseases. Finally, quality control issues related to implementation of high throughput technologies are addressed, to underscore the importance of minimizing bias and randomizing human and technical error in generating large datasets that are expensive and time-consuming to repeat.
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