Multi-scale data-driven engineering for biosynthetic titer improvement
Review article, 2020
Industrial biosynthesis is a very complex process which depends on a range of different factors, from intracellular genes and metabolites, to extracellular culturing conditions and bioreactor engineering. The identification of species that improve the titer of some reaction is akin to the task of finding a needle in a haystack. This review aims to summarize state-of-the-art biosynthesis titer improvement on different scales separately, particularly regarding the advancement of metabolic pathway rewiring and data-driven process optimization and control. By integrating multi-scale data and establishing a mathematical replica of a real biosynthesis, more refined quantitative insights can be gained for achieving a higher titer than ever.
Author
Zhixing Cao
East China University of Science and Technology
Jiaming Yu
East China University of Science and Technology
Weishan Wang
Chinese Academy of Sciences
East China University of Science and Technology
Hongzhong Lu
Chalmers, Biology and Biological Engineering, Systems and Synthetic Biology
Xuekui Xia
Qilu University of Technology
Hui Xu
Chinese Academy of Sciences
Xiuliang Yang
Shandong Jincheng Bio-Pharmaceutical Co., Ltd.
Lianqun Bao
Shijiazhuang Xingbai Bioengineering Co., Ltd
Qing Zhang
Inner Mongolia New Veyong Biochemical Co., Ltd
Huifeng Wang
East China University of Science and Technology
SL. Zhang
East China University of Science and Technology
Lixin Zhang
East China University of Science and Technology
Current Opinion in Biotechnology
0958-1669 (ISSN) 1879-0429 (eISSN)
Vol. 65 205-212Subject Categories
Biological Sciences
DOI
10.1016/j.copbio.2020.04.002
PubMed
32485576