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MitoMiner, an Integrated Database for the Storage and Analysis of Mitochondrial Proteomics Data

机译:MitoMiner,用于存储和分析线粒体蛋白质组学数据的集成数据库

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摘要

Mitochondria are a vital component of eukaryotic cells with functions that extend beyond energy production to include metabolism, signaling, cell growth, and apoptosis. Their dysfunction is implicated in a large number of metabolic, degenerative, and age-related human diseases. Therefore, it is important to characterize and understand the mitochondrion. Many experiments have attempted to define the mitochondrial proteome, resulting in large and complex data sets that are difficult to analyze. To address this, we developed a new public resource for the storage and investigation of this mitochondrial proteomics data, called MitoMiner, that uses a model to describe the proteomics data and associated biological information. The proteomics data of 33 publications from both mass spectrometry and green fluorescent protein tagging experiments were imported and integrated with protein annotation from UniProt and genome projects, metabolic pathway data from Kyoto Encyclopedia of Genes and Genomes, homology relationships from HomoloGene, and disease information from Online Mendelian Inheritance in Man. We demonstrate the strengths of MitoMiner by investigating these data sets and show that the number of different mitochondrial proteins that have been reported is about 3700, although the number of proteins common to both animals and yeast is about 1400, and membrane proteins appear to be underrepresented. Furthermore analysis indicated that enzymes of some cytosolic metabolic pathways are regularly detected in mitochondrial proteomics experiments, suggesting that they are associated with the outside of the outer mitochondrial membrane. The data and advanced capabilities of MitoMiner provide a framework for further mitochondrial analysis and future systems level modeling of mitochondrial physiology.
机译:线粒体是真核细胞的重要组成部分,其功能不仅限于能量产生,还包括新陈代谢,信号传导,细胞生长和凋亡。它们的功能障碍与许多新陈代谢,退化和与年龄有关的人类疾病有关。因此,表征和了解线粒体很重要。许多实验都试图定义线粒体蛋白质组,从而导致难以分析的庞大而复杂的数据集。为了解决这个问题,我们开发了一种用于线粒体蛋白质组学数据的存储和研究的新公共资源,称为MitoMiner,它使用一种模型来描述蛋白质组学数据和相关的生物学信息。导入了来自质谱法和绿色荧光蛋白标记实验的33种出版物的蛋白质组学数据,并将其与UniProt和基因组计划的蛋白质注释,京都议定书基因与基因组百科全书的代谢途径数据,同源基因的同源关系以及在线疾病信息整合在一起孟德尔式的人类继承。通过研究这些数据集,我们证明了MitoMiner的优势,并表明尽管动物和酵母共有的蛋白质数量约为1400,膜蛋白似乎代表性不足,但已报道的不同线粒体蛋白质的数量约为3700。 。进一步的分析表明,在线粒体蛋白质组学实验中定期检测到某些胞质代谢途径的酶,这表明它们与线粒体外膜的外部有关。 MitoMiner的数据和高级功能为进一步的线粒体分析和线粒体生理学的未来系统级建模提供了框架。

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