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通过绘制信号网络中的差异磷酸化事件实现功能磷酸蛋白质组学研究。

Towards functional phosphoproteomics by mapping differential phosphorylation events in signaling networks.

作者信息

de la Fuente van Bentem Sergio, Mentzen Wieslawa I, de la Fuente Alberto, Hirt Heribert

机构信息

Department of Plant Molecular Biology, Max F. Perutz Laboratories, University of Vienna, Vienna, Austria.

出版信息

Proteomics. 2008 Nov;8(21):4453-65. doi: 10.1002/pmic.200800175.

DOI:10.1002/pmic.200800175
PMID:18972525
Abstract

Protein phosphorylation plays a central role in many signal transduction pathways that mediate biological processes. Novel quantitative mass spectrometry-based methods have recently revealed phosphorylation dynamics in animals, yeast, and plants. These methods are important for our understanding of how differential phosphorylation participates in translating distinct signals into proper physiological responses, and shifted research towards screening for potential cancer therapies and in-depth analysis of phosphoproteomes. In this review, we aim to describe current progress in quantitative phosphoproteomics. This emerging field has changed numerous static pathways into dynamic signaling networks, and revealed protein kinase networks that underlie adaptation to environmental stimuli. Mass spectrometry enables high-throughput and high-quality analysis of differential phosphorylation at a site-specific level. Although determination of differential phosphorylation between treatments is analogous to detecting differential gene expression, the large body of statistical techniques that has been developed for analysis of differential gene expression is not generally applied for detecting differential phosphorylation. We suggest possible improvements for analysis of quantitative phosphorylation by increasing the number of biological replicates and adapting statistical tests used for gene expression profiling and widely implemented in freely available software tools.

摘要

蛋白质磷酸化在介导生物过程的许多信号转导途径中起着核心作用。基于定量质谱的新方法最近揭示了动物、酵母和植物中的磷酸化动态变化。这些方法对于我们理解差异磷酸化如何参与将不同信号转化为适当的生理反应非常重要,并将研究转向筛选潜在的癌症治疗方法和对磷酸化蛋白质组的深入分析。在这篇综述中,我们旨在描述定量磷酸化蛋白质组学的当前进展。这个新兴领域已经将众多静态途径转变为动态信号网络,并揭示了构成对环境刺激适应基础的蛋白激酶网络。质谱能够在位点特异性水平上对差异磷酸化进行高通量和高质量分析。尽管处理之间差异磷酸化的测定类似于检测差异基因表达,但为分析差异基因表达而开发的大量统计技术通常并不用于检测差异磷酸化。我们建议通过增加生物学重复的数量以及采用用于基因表达谱分析且在免费软件工具中广泛应用的统计测试,来改进定量磷酸化分析。

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