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Prokisch, H. ; Scharfe, C.* ; Camp, D.G.* ; Xiao, W.* ; David, L.* ; Andreoli, C. ; Monroe, M.E.* ; Moore, R.J.* ; Gritsenko, M.A.* ; Kozany, C. ; Hixson, K.K.* ; Mottaz, H.M.* ; Zischka, H. ; Ueffing, M. ; Herman, Z.S.* ; Davis, R.W.* ; Meitinger, T. ; Oefner, P.J.* ; Smith, R.D.* ; Steinmetz, L.M.

Integrative analysis of the mitochondrial proteome in yeast.

PLoS Biol. 2, 795-804:e160 (2004)
Publ. Version/Full Text Volltext DOI PMC
Open Access Gold
Creative Commons Lizenzvertrag
In this study yeast mitochondria were used as a model system to apply, evaluate, and integrate different genomic approaches to define the proteins of an organelle. Liquid chromatography mass spectrometry applied to purified mitochondria identified 546 proteins. By expression analysis and comparison to other proteome studies, we demonstrate that the proteomic approach identifies primarily highly abundant proteins. By expanding our evaluation to other types of genomic approaches, including systematic deletion phenotype screening, expression profiling, subcellular localization studies, protein interaction analyses, and computational predictions, we show that an integration of approaches moves beyond the limitations of any single approach. We report the success of each approach by benchmarking it against a reference set of known mitochondrial proteins, and predict approximately 700 proteins associated with the mitochondrial organelle from the integration of 22 datasets. We show that a combination of complementary approaches like deletion phenotype screening and mass spectrometry can identify over 75% of the known mitochondrial proteome. These findings have implications for choosing optimal genome-wide approaches for the study of other cellular systems, including organelles and pathways in various species. Furthermore, our systematic identification of genes involved in mitochondrial function and biogenesis in yeast expands the candidate genes available for mapping Mendelian and complex mitochondrial disorders in humans.
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Publication type Article: Journal article
Document type Scientific Article
Corresponding Author
Keywords SACCHAROMYCES-CEREVISIAE; MASS-SPECTROMETRY; GLOBAL ANALYSIS; SYSTEMATIC IDENTIFICATION; SUBCELLULAR-LOCALIZATION; PROTEINS; DATABASE; EXPRESSION; SCALE; SEQUENCES
ISSN (print) / ISBN 1544-9173
e-ISSN 1545-7885
Journal PLoS Biology
Quellenangaben Volume: 2, Issue: 6, Pages: 795-804, Article Number: e160 Supplement: ,
Publisher Public Library of Science (PLoS)
Non-patent literature Publications
Reviewing status Peer reviewed
Institute(s) Institute of Human Genetics (IHG)