《生命科学》 2021, 33(12): 1429-1435

合成生物学的科学问题

罗　楠¹ , 赵国屏^2,3,4,5,6,* , 刘陈立^1,7,*

¹中国科学院深圳先进技术研究院合成生物学研究所，深圳合成生物学创新研究院，中国科学院定量工程生物 学重点实验室，深圳 518055 ²中国科学院分子植物科学卓越创新中心合成生物学重点实验室，上海 200032 ³中国科学院上海营养与健康研究所生物医学大数据中心，上海 200031 ⁴中国科学院天津工业生物技术研究所 国家合成生物技术创新中心，天津 300308 ⁵复旦大学生命科学学院微生物学与微生物工程系，上海 200438 ⁶山东大学公共卫生学院健康医疗大数据研究院，济南 250002 ⁷中国科学院大学，北京 100049

摘　要：

合成生物学不仅推动了生物工程应用的革命性发展，也为生命科学基础研究带来了崭新机遇。本文提出了合成生物学目前的核心科学问题，一方面是解答生命功能跨层次涌现的原理，另一方面是基于涌现性原理解决生命系统的理性设计与构建这一瓶颈问题；总结了在合成生物学研究中，当功能涌现原理已知或未知时的不同研究范式，并讨论了合成生物学的定量研究方法，包括基于“定量表征+ 数理建模”的白箱模型与基于“自动化+ 人工智能”的黑箱模型。通过结合自上而下的工程研究范式与定量化、理论化的研究方法，定量合成生物学这一新领域将有望推动基础生命科学与合成生物学的双重变革。

通讯作者：赵国屏 , Email:gpzhao@sibs.ac.cn 刘陈立 , Email:cl.liu@siat.ac.cn

Scientific questions for synthetic biology

LUO Nan¹ , ZHAO Guo-Ping^2,3,4,5,6,* , LIU Chen-Li^1,7,*

¹CAS Key Laboratory of Quantitative Engineering Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Science, Shenzhen 518055, China ²Key Laboratory of Synthetic Biology, CAS Center for Excellence in Molecular Plant Sciences, Shanghai Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai 200032, China ³Biomedical Big Data Center, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai 200031, China ⁴National Technology Innovation Center of Synthetic Biology, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin 300308, China ⁵Department of Microbiology and Microbial Engineering, School of Life Sciences, Fudan University, Shanghai 200438, China ⁶Health and Medical Research Institute, School of Public Health, Shandong University, Jinan 250002, China ⁷University of Chinese Academy of Sciences, Beijing 100049, China

Abstract:

Synthetic biology not only has revolutionized bioengineering, but also brings new opportunities to the basic research in life sciences. We propose that the key scientific questions for synthetic biology are to understand the principles underlying the emergence of life functions on one hand, and based on these principles, to rationally design and build synthetic living systems on the other hand. Here, we summarize three types of research paradigms and quantitative methodologies for synthetic biology, including white box modeling based on quantitative observations and biophysical models, and black box modeling based on automated data acquisition and artificial intelligence. Quantitative approaches will allow the predictable design of synthetic biological systems and provide a deeper understanding of life function emergence. Therefore, we envision that quantitative synthetic biology as an emerging young field will drive the next revolution in both synthetic biology and fundamental life sciences.

Communication Author：ZHAO Guo-Ping , Email:gpzhao@sibs.ac.cn LIU Chen-Li , Email:cl.liu@siat.ac.cn