Yuan Qianqian, Mao Zhitao, Yang Xue, Liao Xiaoping, Ma Hongwu
Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, 300308, China.
National Technology Innovation Center of Synthetic Biology, Tianjin 300308, China.
Sheng Wu Gong Cheng Xue Bao. 2022 Nov 25;38(11):4146-4161. doi: 10.13345/j.cjb.220590.
Various omics technologies are changing Biology into a data-driven science subject. Development of data-driven digital cell models is key for understanding system level organization and evolution principles of life, as well as for predicting cellular function under various environmental/genetic perturbations and subsequently for the design of artificial life. Consequently, the construction, analysis and design of digital cell models have become one of the core supporting technologies in synthetic biology. This paper summarized the research progress on digital cell models in the last ten years after the foundation of Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, with a focus on the development and quality control of genome-scale metabolic network for reliable metabolic pathway design and their application in guiding strain metabolic engineering. We also introduced the latest progress on developing cellular models with multiple constraints to improve prediction accuracy. At last, we briefly discussed the current challenges and future directions in digital cell model development. We believe that digital cell technology, along with genome sequencing, genome synthesis and genome editing, will greatly improve our ability in reading, writing, modifying and creating life.
各种组学技术正在将生物学转变为一门数据驱动的科学学科。开发数据驱动的数字细胞模型是理解生命系统水平的组织和进化原理、预测各种环境/基因扰动下的细胞功能以及随后设计人工生命的关键。因此，数字细胞模型的构建、分析和设计已成为合成生物学的核心支撑技术之一。本文总结了中国科学院天津工业生物技术研究所成立十年来数字细胞模型的研究进展，重点关注基因组规模代谢网络的开发和质量控制，以进行可靠的代谢途径设计及其在指导菌株代谢工程中的应用。我们还介绍了开发具有多种约束条件的细胞模型以提高预测准确性的最新进展。最后，我们简要讨论了数字细胞模型开发当前面临的挑战和未来方向。我们相信，数字细胞技术与基因组测序、基因组合成和基因组编辑一起，将极大地提高我们读取、书写、修改和创造生命的能力。
