文献类型：期刊文献

英文题名：Multi-scale data-driven engineering for biosynthetic titer improvement

作者：Cao, Zhixing[1,2];Yu, Jiaming[1];Wang, Weishan[1,3];Lu, Hongzhong[9];Xia, Xuekui[4];Xu, Hui[5];Yang, Xiuliang[6];Bao, Lianqun[7];Zhang, Qing[8];Wang, Huifeng[2];Zhang, Siliang[1];Zhang, Lixin[1]

机构：[1]East China Univ Sci & Technol, State Key Lab Bioreactor Engn, Shanghai 200237, Peoples R China;[2]East China Univ Sci & Technol, MOE Key Lab Adv Control & Optimizat Chem Proc, Shanghai 200237, Peoples R China;[3]Chinese Acad Sci, Inst Microbiol, State Key Lab Microbial Resources, Beijing 100101, Peoples R China;[4]QiluUniv Technol, Shandong Acad Sci, Inst Biol, Key Biosensor Lab Shandong Prov, Jinan 250013, Peoples R China;[5]Chinese Acad Sci, Inst Appl Ecol, Shenyang 110016, Peoples R China;[6]Shandong Jincheng Biopharmaceut Co Ltd, 117 Qixing River Rd, Zibo 255130, Shandong, Peoples R China;[7]Shijiazhuang XingbaiBioengn Co Ltd, Shijiazhuang 050000, Hebei, Peoples R China;[8]Inner Mongolia New VeyongBiochem Co Ltd, Dalad Banner 014300, Peoples R China;[9]Chalmers Univ Technol, Dept Biol & Biol Engn, Kemivagen 10, SE-41296 Gothenburg, Sweden

年份：2020

卷号：65

起止页码：205

外文期刊名：CURRENT OPINION IN BIOTECHNOLOGY

收录：;EI(收录号：20202208774977);WOS:【SCI-EXPANDED(收录号:WOS:000589902000026)】；

基金：This work was supported by the National Natural Science Foundation of China#31720103901, the '111' Project of China#B18022, the Fundamental Research Funds for the Central Universities#22221818014S, the Open Project Funding of the State Key Laboratory of Bioreactor Engineering, and the Shandong Taishan Scholar Award to L.Z. We are grateful for the proofreading by James Holehouse at the University of Edinburgh.

语种：英文

外文关键词：Biochemistry - Metabolites - Optimization

摘要：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.