《生命科学》 2021, 33(12): 1476-1482

代谢研究新技术助力合成生物学

杨　琛^1,* , 徐　健^2,* , 杨　弋^3,*

¹中国科学院合成生物学重点实验室，中国科学院分子植物科学卓越创新中心，上海 200032 ²中国科学院 青岛生物能源与过程研究所单细胞中心，中国科学院生物燃料重点实验室，山东能源研究院，青岛 266101 ³华东理工大学光遗传学与合成生物学交叉学科研究中心，生物反应器工程国家重点实验室，上海 200237

摘　要：

合成生物学通过构建人工代谢途径，不仅可以发展高效的生物制造技术，还可以用于人类重要疾病的诊疗，为催生新的生物产业革命、促进经济可持续发展提供了重大机遇。该文围绕代谢组与代谢流量分析以及代谢建模、单细胞代谢表型组分析与分选、代谢物生物传感与时空调控等前沿技术，介绍现有状况和水平，综述分析这些技术如何助推合成生物学设计- 构建- 测试- 学习(DBTL) 循环，并对其发展前景进行展望。

通讯作者：杨　琛 , Email:cyang@cemps.ac.cn 徐　健 , Email:xujian@qibebt.ac.cn 杨　弋 , Email:yiyang@ecust.edu.cn

Advanced techniques of metabolic sciences for synthetic biology

YANG Chen^1,* , XU Jian^2,* , YANG Yi^3,*

¹CAS Key Laboratory of Synthetic Biology, CAS Center for Excellence in Molecular Plant Sciences, Chinese Academy of Sciences (CAS), Shanghai 200032, China ²Single-Cell Center, CAS Key Laboratory of Biofuels, Shandong Energy Institute, Qingdao Institute of BioEnergy and Bioprocess Technology, CAS, Qingdao 266101, China ³Optogenetics & Synthetic Biology Interdisciplinary Research Center, State Key Laboratory of Bioreactor Engineering, East China University of Science and Technology, Shanghai 200237, China

Abstract:

Cellular metabolism is being engineered through synthetic biology for an increasingly diverse array of applications, from chemical production to human health. In this review, we highlight the recent advances in the techniques of metabolic sciences, including metabolomics, metabolic flux analysis, genome-scale metabolic modeling, single-cell metabolic phenome, Raman-activated cell sorting, spatiotemporal metabolic analysis, single-cell optogenetic control, and metabolic phenomics. These techniques are accelerating the design, build, test, and learn (DBTL) cycles for synthetic biology. The emerging challenges and future developments in these techniques and their applications in synthetic biology are discussed.

Communication Author：YANG Chen , Email:cyang@cemps.ac.cn XU Jian , Email:xujian@qibebt.ac.cn YANG Yi , Email:yiyang@ecust.edu.cn