Large-Scale Characterization and Analysis of the Murine Cardiac Proteome
journal contributionposted on 03.04.2009, 00:00 by Nicolas Bousette, Thomas Kislinger, Vincent Fong, Ruth Isserlin, Johannes A. Hewel, Andrew Emili, Anthony O. Gramolini
Recent advances in mass spectrometry and bioinformatics have provided the means to characterize complex protein landscapes from a wide variety of organisms and cell types. Development of standard proteomes exhibiting all of the proteins involved in normal physiology will facilitate the delineation of disease mechanisms. Here, we examine the wild-type cardiac proteome using data obtained from a subcellular fractionation protocol in combination with a multidimensional protein identification proteomics approach. We identified 4906 proteins which were allocated to either cytosolic, microsomal, mitochondrial matrix or mitochondrial membrane fractions with relative abundance values in each fraction. We subjected these proteins to hierarchical clustering, gene ontology terms analysis, immunoblotting, comparison to publicly available protein databases, comparison to 4 distinct cardiac transcriptomes, and finally, to 6 other related proteomic data sets. This study provides an exhaustive analysis of the cardiac proteome and is the first large-scale investigation of the subcellular location for over 2000 unannotated proteins. With the use of a subtractive transcriptomics approach, we have also extended our analysis to identify ‘cardiac selective’ factors in our proteome. Finally, using specific filtering criteria, we identified proteotypic peptides for subsequent use in targeted studies of both mouse and human. Therefore, we offer this as a major contribution to the advancement of the field of proteomics in cardiovascular research.
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proteomic data setsmitochondrial membrane fractionssubcellular fractionation protocolmass spectrometrysubtractive transcriptomics approachMurine Cardiac ProteomeRecent advancesabundance valuesproteotypic peptidesprotein databasesprotein identification proteomics approachgene ontology terms analysisdisease mechanisms4906 proteins2000 unannotated proteinscell typesproteomesubcellular locationmitochondrial matrixprotein landscapes