Top-Down Quantitative Proteomic Analysis Using a Highly Multiplexed Isobaric Mass Tagging Strategy

Proteomic analysis has proved to be key to determining drug mechanisms and assessing toxicologic potential during preclinical screening studies. A major goal in proteomics is to accurately measure changes in the relative abundance of large sets of proteins in complex biological systems as a function of experimental parameters, such as drug dose or exposure time. Until recently, top-down quantitative proteomics has been restricted to two-dimensional gel analyses or two-plex mass tagging. A new top-down approach based on isobaric mass tagging (ExacTag) for highly multiplexing (up to 10-plex) protein quantification is presented, involving chemically tagging cysteine or lysine residues of intact proteins isolated from cells, tissues, or biological fluids. As many as 10 labeled samples are then combined, fractionated, proteolytically digested, and analyzed by gel electrophoresis or liquid chromatography–tandem mass spectrometry. Proteins are identified using public domain search engines, such as Mascot (Matrix Science Ltd., London, UK) and quantified using an in-house developed software package. During the fragmentation, the tag-labeled peptides generate a set of low mass reporters that are unique to each sample. Measurement of the intensity of these reporters allows the relative quantification of the peptides and consequently the proteins from which they originated. The capabilities of the approach are demonstrated by analysis of the HeLa cell nucleolar proteome after treatment with the metabolic inhibitor actinomycin D for various time periods. A total of 440 proteins are qualitatively identified and quantified. The quantification data demonstrate that the nucleolar proteome changes significantly over time in response to differences in growth conditions, which is consistent with previous observations from several groups. The highly multiplexed and quantitative nature of the new technology should herald in new opportunities to provide diagnostic and functional insights into the proteomics discovery process.