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. 65 205-212

Subject Categories

Biological Sciences

DOI

10.1016/j.copbio.2020.04.002

PubMed

32485576

More information

Latest update

12/2/2021