Abstract

Bio-based production of many chemicals is not yet possible due to the unknown biosynthetic pathways. Here, we report a strategy combining retrobiosynthesis and precursor selection step to design biosynthetic pathways for multiple short-chain primary amines (SCPAs) that have a wide range of applications in chemical industries. Using direct precursors of 15 target SCPAs determined by the above strategy, Streptomyces viridifaciens vlmD encoding valine decarboxylase is examined as a proof-of-concept promiscuous enzyme both in vitro and in vivo for generating SCPAs from their precursors. Escherichia coli expressing the heterologous vlmD produces 10 SCPAs by feeding their direct precursors. Furthermore, metabolically engineered E. coli strains are developed to produce representative SCPAs from glucose, including the one producing 10.67 g L−1 of iso-butylamine by fed-batch culture. This study presents the strategy of systematically designing biosynthetic pathways for the production of a group of related chemicals as demonstrated by multiple SCPAs as examples.

Short-chain primary amines (SCPAs) are industrially important compounds that are commonly produced under harsh synthetic conditions. Here, the authors report a combination of retrobiosynthesis and precursor selection step for design of biosynthetic pathways leading to production of SCPAs, using valine decarboxylase-expressing Escherichia coli strains.

Details

Title
Microbial production of multiple short-chain primary amines via retrobiosynthesis
Author
Kim Dong In 1 ; Chae, Tong Un 1   VIAFID ORCID Logo  ; Kim Hyun Uk 2   VIAFID ORCID Logo  ; Jang, Woo Dae 1   VIAFID ORCID Logo  ; Lee, Sang Yup 3   VIAFID ORCID Logo 

 Korea Advanced Institute of Science and Technology (KAIST), Metabolic and Biomolecular Engineering National Research Laboratory, Department of Chemical and Biomolecular Engineering, KAIST Institute for BioCentury, Daejeon, Republic of Korea (GRID:grid.37172.30) (ISNI:0000 0001 2292 0500); Systems Metabolic Engineering and Systems Healthcare Cross-Generation Collaborative Laboratory, KAIST, Daejeon, Republic of Korea (GRID:grid.37172.30) (ISNI:0000 0001 2292 0500) 
 Systems Metabolic Engineering and Systems Healthcare Cross-Generation Collaborative Laboratory, KAIST, Daejeon, Republic of Korea (GRID:grid.37172.30) (ISNI:0000 0001 2292 0500); Systems Biology and Medicine Laboratory, Department of Chemical and Biomolecular Engineering, KAIST, Daejeon, Republic of Korea (GRID:grid.37172.30) (ISNI:0000 0001 2292 0500); KAIST Institute for Artificial Intelligence, BioProcess Engineering Research Center and BioInformatics Research Center, KAIST, Daejeon, Republic of Korea (GRID:grid.37172.30) (ISNI:0000 0001 2292 0500) 
 Korea Advanced Institute of Science and Technology (KAIST), Metabolic and Biomolecular Engineering National Research Laboratory, Department of Chemical and Biomolecular Engineering, KAIST Institute for BioCentury, Daejeon, Republic of Korea (GRID:grid.37172.30) (ISNI:0000 0001 2292 0500); Systems Metabolic Engineering and Systems Healthcare Cross-Generation Collaborative Laboratory, KAIST, Daejeon, Republic of Korea (GRID:grid.37172.30) (ISNI:0000 0001 2292 0500); KAIST Institute for Artificial Intelligence, BioProcess Engineering Research Center and BioInformatics Research Center, KAIST, Daejeon, Republic of Korea (GRID:grid.37172.30) (ISNI:0000 0001 2292 0500) 
Publication year
2021
Publication date
2021
Publisher
Nature Publishing Group
e-ISSN
20411723
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2476251812
Copyright
© The Author(s) 2021. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.