Prokisch Holger, Scharfe Curt, Camp David G, Xiao Wenzhong, David Lior, Andreoli Christophe, Monroe Matthew E, Moore Ronald J, Gritsenko Marina A, Kozany Christian, Hixson Kim K, Mottaz Heather M, Zischka Hans, Ueffing Marius, Herman Zelek S, Davis Ronald W, Meitinger Thomas, Oefner Peter J, Smith Richard D, Steinmetz Lars M
Institute of Human Genetics, GSF National Research Center for Environment and Health, Neuherberg, Germany.
PLoS Biol. 2004 Jun;2(6):e160. doi: 10.1371/journal.pbio.0020160. Epub 2004 Jun 15.
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.
在本研究中,酵母线粒体被用作一个模型系统,以应用、评估和整合不同的基因组学方法来确定一个细胞器的蛋白质。应用于纯化线粒体的液相色谱质谱法鉴定出了546种蛋白质。通过表达分析并与其他蛋白质组研究进行比较,我们证明蛋白质组学方法主要鉴定出了高丰度蛋白质。通过将我们的评估扩展到其他类型的基因组学方法,包括系统缺失表型筛选、表达谱分析、亚细胞定位研究、蛋白质相互作用分析和计算预测,我们表明方法的整合超越了任何单一方法的局限性。我们通过将每种方法与一组已知线粒体蛋白质的参考集进行基准测试来报告每种方法的成功,并通过整合22个数据集预测了约700种与线粒体细胞器相关的蛋白质。我们表明,像缺失表型筛选和质谱法这样的互补方法组合可以鉴定出超过75%的已知线粒体蛋白质组。这些发现对于为研究其他细胞系统(包括各种物种中的细胞器和途径)选择最佳全基因组方法具有启示意义。此外,我们对酵母中参与线粒体功能和生物发生的基因进行的系统鉴定,扩展了可用于绘制人类孟德尔和复杂线粒体疾病图谱的候选基因。