The complete yeast mitochondrial proteome: Multidimensional separation techniques for mitochondrial proteomics
The complete yeast mitochondrial proteome: Multidimensional separation techniques for mitochondrial proteomics
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DOI：
10.1021/pr050477f
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发表时间：
2006-07-07
影响因子：
4.4
通讯作者：
Sickmann, Albert
中科院分区：
文献类型：
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作者：
Reinders, Joerg;Zahedi, Rene P.;Sickmann, Albert
不同亚细胞区室的蛋白质组学分析，即所谓的细胞器蛋白质组学，有助于在分子水平上理解细胞功能。在这项工作中，各种正交多维分离技术的蛋白质和肽的水平进行比较方面的数量确定的蛋白质，以及通过各自的方法访问的蛋白质类。最完整的概述是通过结合这种正交技术所示的酵母线粒体蛋白质组的分析。通过使用多维LC-MS/MS、1D-SDSPAGE结合nano-LC-MS/MS和2D-PAGE以及随后的MALDI-mass指纹图谱，共鉴定了851种不同的蛋白质（PROMITO数据集）。我们的PROMITO方法鉴定了749种蛋白质，这些蛋白质是在以前对酵母线粒体蛋白质组的最大研究中发现的，另外还有102种蛋白质，包括42个功能未知的开放阅读框架，为更详细地阐明线粒体过程提供了基础。不同方法的比较强调了2D-PAGE对具有非常高的等电点的蛋白质以及大的疏水蛋白质的偏倚，这些蛋白质可以通过其他方法更适当地获得。虽然2D-PAGE在可能分离蛋白质亚型和定量差异分析方面具有优势，但1D-SDS-PAGE与nano-LC-MS/MS和多维LCMS/MS更适合于有效的蛋白质鉴定，因为它们对不同类别的蛋白质的偏倚较小。因此，全面的蛋白质组分析只能通过这种正交方法的组合来实现，从而获得酵母线粒体蛋白质组的最大数据集。
Proteomic analyses of different subcellular compartments, so-called organellar proteomics, facilitate the understanding of cellular functions on a molecular level. In this work, various orthogonal multidimensional separation techniques both on the protein and on the peptide level are compared with regard to the number of identified proteins as well as the classes of proteins accessible by the respective methodology. The most complete overview was achieved by a combination of such orthogonal techniques as shown by the analysis of the yeast mitochondrial proteome. A total of 851 different proteins (PROMITO dataset) were identified by use of multidimensional LC-MS/MS, 1D-SDSPAGE combined with nano-LC-MS/MS and 2D-PAGE with subsequent MALDI-mass fingerprinting. Our PROMITO approach identified the 749 proteins, which were found in the largest previous study on the yeast mitochondrial proteome, and additionally 102 proteins including 42 open reading frames with unknown function, providing the basis for a more detailed elucidation of mitochondrial processes. Comparison of the different approaches emphasizes a bias of 2D-PAGE against proteins with very high isoelectric points as well as large and hydrophobic proteins, which can be accessed more appropriately by the other methods. While 2D-PAGE has advantages in the possible separation of protein isoforms and quantitative differential profiling, 1D-SDS-PAGE with nano-LC-MS/MS and multidimensional LCMS/MS are better suited for efficient protein identification as they are less biased against distinct classes of proteins. Thus, comprehensive proteome analyses can only be realized by a combination of such orthogonal approaches, leading to the largest dataset available for the mitochondrial proteome of yeast.