A Systematic Characterization of Mitochondrial Proteome from Human T Leukemia Cells

• DOI: 10.1074/mcp.m400115-mcp200
• Publication Date: 2004-12-15T02:58:24Z
• Authors: Karim Rezaul; Linfeng Wu; Viveka Mayya; Sun-Il Hwang; David Han
• Keywords: Electrophoresis, Agar Gel; Proteomics; 0301 basic medicine; Leukemia, T-Cell; Blotting, Western; Molecular Sequence Data; Computational Biology; Hydrogen-Ion Concentration; Mass Spectrometry; Mitochondria; Molecular Weight; Jurkat Cells; Oxidative Stress; 03 medical and health sciences; Proto-Oncogene Proteins c-bcl-2; Cell Line, Tumor; Humans; Electrophoresis, Polyacrylamide Gel; Amino Acid Sequence; Peptides; Glycolysis; Chromatography, Liquid

Global understanding of tissue-specific differences in mitochondrial signal transduction requires comprehensive mitochondrial protein identification from multiple cell and tissue types. Here, we explore the feasibility and efficiency of protein identification using the one-dimensional gel electrophoresis in combination with the nano liquid-chromatography tandem mass spectrometry (GeLC-MS/MS). The use of only 40 mug of purified mitochondrial proteins and data analysis using stringent scoring criteria and the molecular mass validation of the gel slices enables the identification of 227 known mitochondrial proteins (membrane and soluble) and 453 additional proteins likely to be associated with mitochondria. Replicate analyses of 60 mug of mitochondrial proteins on the faster scanning LTQ mass spectrometer validate all the previously identified proteins and most of the single hit proteins except the 81 single hit proteins. Among the identified proteins, 466 proteins are known to functionally participate in various processes such as respiration, tricarboxylic acid cycle (TCA cycle), amino acid and nucleotide metabolism, glycolysis, protection against oxidative stress, mitochondrial assembly, molecular transport, protein biosynthesis, cell cycle control, and many known cellular processes. The distribution of identified proteins in terms of size, pI, and hydrophobicity reveal that the present analytical strategy is largely unbiased and very efficient. Thus, we conclude that this approach is suitable for characterizing subcellular proteomes form multiple cells and tissues.