Thiele Ines, Jamshidi Neema, Fleming Ronan M T, Palsson Bernhard Ø
University of California San Diego, La Jolla, California, United States of America.
PLoS Comput Biol. 2009 Mar;5(3):e1000312. doi: 10.1371/journal.pcbi.1000312. Epub 2009 Mar 13.
Metabolic network reconstructions represent valuable scaffolds for '-omics' data integration and are used to computationally interrogate network properties. However, they do not explicitly account for the synthesis of macromolecules (i.e., proteins and RNA). Here, we present the first genome-scale, fine-grained reconstruction of Escherichia coli's transcriptional and translational machinery, which produces 423 functional gene products in a sequence-specific manner and accounts for all necessary chemical transformations. Legacy data from over 500 publications and three databases were reviewed, and many pathways were considered, including stable RNA maturation and modification, protein complex formation, and iron-sulfur cluster biogenesis. This reconstruction represents the most comprehensive knowledge base for these important cellular functions in E. coli and is unique in its scope. Furthermore, it was converted into a mathematical model and used to: (1) quantitatively integrate gene expression data as reaction constraints and (2) compute functional network states, which were compared to reported experimental data. For example, the model predicted accurately the ribosome production, without any parameterization. Also, in silico rRNA operon deletion suggested that a high RNA polymerase density on the remaining rRNA operons is needed to reproduce the reported experimental ribosome numbers. Moreover, functional protein modules were determined, and many were found to contain gene products from multiple subsystems, highlighting the functional interaction of these proteins. This genome-scale reconstruction of E. coli's transcriptional and translational machinery presents a milestone in systems biology because it will enable quantitative integration of '-omics' datasets and thus the study of the mechanistic principles underlying the genotype-phenotype relationship.
代谢网络重建是“组学”数据整合的重要框架,并用于通过计算探究网络特性。然而,它们并未明确考虑大分子(即蛋白质和RNA)的合成。在此,我们首次对大肠杆菌的转录和翻译机制进行了全基因组规模的精细重建,该机制以序列特异性方式产生423种功能基因产物,并涵盖了所有必要的化学转化过程。我们查阅了来自500多篇出版物和三个数据库的传统数据,并考虑了许多途径,包括稳定RNA的成熟和修饰、蛋白质复合物的形成以及铁硫簇的生物合成。这种重建代表了大肠杆菌中这些重要细胞功能最全面的知识库,其范围是独一无二的。此外,它被转化为一个数学模型,并用于:(1)将基因表达数据作为反应约束进行定量整合,以及(2)计算功能网络状态,并与已报道的实验数据进行比较。例如,该模型在没有任何参数化的情况下准确预测了核糖体的产生。此外,计算机模拟的rRNA操纵子缺失表明,需要在剩余的rRNA操纵子上保持高RNA聚合酶密度,才能重现报道的实验核糖体数量。此外,还确定了功能性蛋白质模块,发现其中许多模块包含来自多个子系统的基因产物,突出了这些蛋白质的功能相互作用。大肠杆菌转录和翻译机制的这种全基因组规模重建是系统生物学的一个里程碑,因为它将实现“组学”数据集的定量整合,从而研究基因型-表型关系背后的机制原理。