全基因组范围代谢网络的构建和最小基因组研究

全基因组范围代谢网络（genome-scale metabolic network，GSMN）的构建是合成生物学研究的一个重要研究手段。通过整合各种组学数据和借助计算机进行模拟分析，将基因型与表型的关系进行定量关联，从而为从全局的角度探索和揭示生物代谢机制，进而对生物进行合理的重新设计和工程改造提供了有效的框架。该方法在最小基因组研究中也有着突出的优势，通过计算机辅助的基因组最小化模拟与分析，能够系统鉴定微生物基因组基因的必需性。迄今为止，已有近百个基因组范围的代谢网络发表，覆盖的生物包括原核生物、真核生物和古生生物，并广泛应用于医药、能源、环境、工业和农业等多个领域，展现出了广阔的应用前景。将对全基因组范围代谢网络构建的方法、应用，特别是其在最小基因组研究中的应用作简要的综述。

Genome-scale metabolic network reconstruction and minimal genome research

Genome-scale metabolic network reconstruction has become indispensable framework for systematically exploring and understanding biological system by integrating various -omics data and taking advantages of computational simulation and analysis. The complex metabolic properties of living organisms can be accurately mimicked, predicted, controlled, and even re-designed by genome-scale metabolic network. This method has an outstanding merit in the minimal genome research, which is one of the major subjects of synthetic biology. So far, nearly 100 genome-scale metabolic networks have been published covering prokaryotes, archaea and eukaryotes. Genome-scale metabolic reconstruction has a broad spectrum of basic and practical applications, including biological discovery, metabolic engineering, phenotypic behavior, and bacteria evolution, and has been successfully applied in medicine, energy, environmental, industrial, agricultural, and other fields. In this paper, the methods of genome-scale metabolic network reconstruction, its application, as well as minimal genome research will be reviewed briefly.