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通过质谱和生物信息学对脂肪细胞蛋白质组进行深入分析。

In-depth analysis of the adipocyte proteome by mass spectrometry and bioinformatics.

作者信息

Adachi Jun, Kumar Chanchal, Zhang Yanling, Mann Matthias

机构信息

Department of Proteomics and Signal Transduction, Max Planck Institute for Biochemistry, Am Klopferspitz 18, D-82152 Martinsried, Germany.

出版信息

Mol Cell Proteomics. 2007 Jul;6(7):1257-73. doi: 10.1074/mcp.M600476-MCP200. Epub 2007 Apr 4.

Abstract

Adipocytes are central players in energy metabolism and the obesity epidemic, yet their protein composition remains largely unexplored. We investigated the adipocyte proteome by combining high accuracy, high sensitivity protein identification technology with subcellular fractionation of nuclei, mitochondria, membrane, and cytosol of 3T3-L1 adipocytes. We identified 3,287 proteins while essentially eliminating false positives, making this one of the largest high confidence proteomes reported to date. Comprehensive bioinformatics analysis revealed that the adipocyte proteome, despite its specialized role, is very complex. Comparison with microarray data showed that the mRNA abundance of detected versus non-detected proteins differed by less than 2-fold and that proteomics covered as large a proportion of the insulin signaling pathway. We used the Endeavour gene prioritization algorithm to associate a number of factors with vesicle transport in response to insulin stimulation, a key function of adipocytes. Our data and analysis can serve as a model for cellular proteomics. The adipocyte proteome is available as supplemental material and from the Max-Planck Unified Proteome database.

摘要

脂肪细胞是能量代谢和肥胖流行的核心参与者,但其蛋白质组成在很大程度上仍未被探索。我们通过将高精度、高灵敏度的蛋白质鉴定技术与3T3-L1脂肪细胞核、线粒体、膜和细胞质的亚细胞分级分离相结合,对脂肪细胞蛋白质组进行了研究。我们鉴定出3287种蛋白质,同时基本消除了假阳性,使其成为迄今为止报道的最大的高可信度蛋白质组之一。全面的生物信息学分析表明,尽管脂肪细胞蛋白质组具有特殊作用,但其非常复杂。与微阵列数据的比较表明,检测到的蛋白质与未检测到的蛋白质的mRNA丰度差异小于2倍,并且蛋白质组学覆盖了胰岛素信号通路的很大一部分。我们使用奋进基因优先级算法将许多因素与胰岛素刺激下的囊泡运输联系起来,胰岛素刺激是脂肪细胞的一项关键功能。我们的数据和分析可作为细胞蛋白质组学的一个模型。脂肪细胞蛋白质组可作为补充材料从马克斯·普朗克统一蛋白质组数据库获得。

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