Proteome analysis of subsarcolemmal cardiomyocyte mitochondria: a comparison of different analytical platforms.
Proteome analysis of subsarcolemmal cardiomyocyte mitochondria: a comparison of different analytical platforms.
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DOI：
10.3390/ijms15069285
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发表时间：
2014-05-26
影响因子：
5.6
通讯作者：
Beranova-Giorgianni S
中科院分区：
文献类型：
--
作者：
Giorgianni F;Koirala D;Weber KT;Beranova-Giorgianni S
Mitochondria are complex organelles that play critical roles in diverse aspects of cellular function. Heart disease and a number of other pathologies are associated with perturbations in the molecular machinery of the mitochondria. Therefore, comprehensive, unbiased examination of the mitochondrial proteome represents a powerful approach toward system-level insights into disease mechanisms. A crucial aspect in proteomics studies is design of bioanalytical strategies that maximize coverage of the complex repertoire of mitochondrial proteins. In this study, we evaluated the performance of gel-based and gel-free multidimensional platforms for profiling of the proteome in subsarcolemmal mitochondria harvested from rat heart. We compared three different multidimensional proteome fractionation platforms: polymeric reversed-phase liquid chromatography at high pH (PLRP), sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE), and isoelectric focusing (IEF) separations combined with liquid chromatography-mass spectrometry/mass spectrometry (LC-MS/MS), and bioinformatics for protein identification. Across all three platforms, a total of 1043 proteins were identified. Among the three bioanalytical strategies, SDS-PAGE followed by LC-MS/MS provided the best coverage of the mitochondrial proteome. With this platform, 890 proteins with diverse physicochemical characteristics were identified; the mitochondrial protein panel encompassed proteins with various functional roles including bioenergetics, protein import, and mitochondrial fusion. Taken together, results of this study provide a large-scale view of the proteome in subsarcolemmal mitochondria from the rat heart, and aid in the selection of optimal bioanalytical platforms for differential protein expression profiling of mitochondria in health and disease.
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影响因子：
2.9
作者：
Gilar, Martin;Olivova, Petra;Gebler, John C.
通讯作者：
Gebler, John C.
DOI：
10.1093/bioinformatics/btp101
发表时间：
2009-04-15
期刊：
Bioinformatics (Oxford, England)
影响因子：
--
作者：
Bindea G;Mlecnik B;Hackl H;Charoentong P;Tosolini M;Kirilovsky A;Fridman WH;Pagès F;Trajanoski Z;Galon J
通讯作者：
Galon J
影响因子：
3
作者：
Gandhi MS;Deshmukh PA;Kamalov G;Zhao T;Zhao W;Whaley JT;Tichy JR;Bhattacharya SK;Ahokas RA;Sun Y;Gerling IC;Weber KT
通讯作者：
Weber KT
影响因子：
4.4
作者：
Nakamura, Tatsuji;Kuromitsu, Junro;Oda, Yoshiya
通讯作者：
Oda, Yoshiya
影响因子：
4.3
作者：
Giorgianni, Francesco;Khan, M. Usman;Weber, Karl T.;Gerling, Ivan C.;Beranova-Giorgianni, Sarka
通讯作者：
Beranova-Giorgianni, Sarka