数字细胞模型的研究及应用

Digital cell models and their applications: a review

摘要:

组学分析技术的发展推动生物学逐渐成为一门以数据分析为中心的科学。依托生物数据在细胞整体系统水平建立数字细胞模型，对于理解细胞系统组织原理和生命产生进化规律，预测各种环境和基因扰动对细胞功能的影响并指导设计人工生命具有重要意义，因此数字细胞的构建模拟设计已成为合成生物学的核心研究内容与底层支撑技术。本文重点对天津工业生物技术研究所创立十年来在数字细胞研究方面的进展进行回顾介绍，重点包括基因组尺度代谢网络模型的构建、质控以及其在途径设计和指导菌种代谢工程改造方面的应用，进一步结合近年来细胞模型研究的前沿趋势，对整合多种约束的模型的构建和分析研究方面的最新成果进行了介绍，最后对数字细胞研究的未来发展方向进行展望。数字细胞技术将与基因组测序、合成和编辑等合成生物学前沿技术一起提升人们对生命进行读写改创的能力。

Abstract:

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.