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蛋白质基因组学与系统生物学:探寻最终缺失的环节

Proteogenomics and systems biology: quest for the ultimate missing parts.

机构信息

CEA, DSV, IBEB, Lab Biochim System Perturb, CEA Marcoule, DSV, iBEB, SBTN, Laboratoire de Biochimie des Systèmes Perturbés, F-30207 Bagnols-sur-Céze, France.

出版信息

Expert Rev Proteomics. 2010 Feb;7(1):65-77. doi: 10.1586/epr.09.104.

Abstract

This review describes how intimately proteogenomics and system biology are imbricated. Quantitative cell-wide monitoring of cellular processes and the analysis of this information is the basis for systems biology. Establishing the most comprehensive protein-parts list is an essential prerequisite prior to analysis of the cell-wide dynamics of proteins, their post-translational modifications, their complex network interactions and interpretation of these data as a whole. High-quality genome annotation is, thus, a crucial basis. Proteogenomics consists of high-throughput identification and characterization of proteins by extra-large shotgun MS/MS approaches and the integration of these data with genomic data. Discovery of the remaining unannotated genes, defining translational start sites, listing signal peptide processing events and post-translational modifications, are tasks that can currently be carried out at a full-genomic scale as soon as the genomic sequence is available. Proteomics is increasingly being used at the primary stage of genome annotation and such an approach may become standard in the near future for genome projects. Advantageously, the same experimental proteomic datasets may be used to characterize the specific metabolic traits of the organism under study. Undoubtedly, comparative genomics will experience a renaissance taking into account this new dimension. Synthetic biology aimed at re-engineering living systems will also benefit from these significant progresses.

摘要

这篇综述描述了蛋白质基因组学和系统生物学是如何紧密交织在一起的。对细胞过程进行定量的全细胞监测和对这些信息的分析是系统生物学的基础。在分析蛋白质的全细胞动态、它们的翻译后修饰、它们的复杂网络相互作用以及整体解释这些数据之前,建立最全面的蛋白质部分列表是一个必要的前提。高质量的基因组注释因此是一个关键的基础。蛋白质基因组学包括通过超大 shotgun MS/MS 方法对蛋白质进行高通量鉴定和表征,以及将这些数据与基因组数据进行整合。发现其余未注释的基因、定义翻译起始位点、列出信号肽处理事件和翻译后修饰,这些任务一旦基因组序列可用,就可以在全基因组范围内完成。蛋白质组学在基因组注释的初始阶段越来越多地被使用,这种方法可能在不久的将来成为基因组项目的标准。有利的是,相同的实验蛋白质组数据集可用于描述所研究生物体的特定代谢特征。毫无疑问,考虑到这一新维度,比较基因组学将经历复兴。旨在重新设计生命系统的合成生物学也将受益于这些重大进展。

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