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이영준Youngjoon Lee

KAIST

Cell Syst., Available online 6 November 2023 | https://doi.org/10.1016/j.cels.2023.10.005 Genome-wide identification of overexpression and downregulation gene targets based on the sum of covariances of the outgoing reaction fluxes

Won Jun Kim ^1,2,5,6, Youngjoon Lee^1,2,5, Hyun Uk Kim ^2,3,4,5, Jae Yong Ryu ^1,7, Jung Eun Yang ^1,8, Sang Yup Lee ^1,2,4,9

1Metabolic and Biomolecular Engineering National Research Laboratory, Department of Chemical and Biomolecular Engineering (BK21 four), KAIST Institute for BioCentury, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Republic of Korea

2Systems Metabolic Engineering and Systems Healthcare Cross-Generation Collaborative Laboratory, KAIST, Daejeon 34141, Republic of Korea

3Systems Biology and Medicine Laboratory, Department of Chemical and Biomolecular Engineering, KAIST, Daejeon 34141, Republic of Korea

4BioProcess Engineering Research Center and BioInformatics Research Center, KAIST, Daejeon 34141, Republic of Korea

5These authors contributed equally

6Present address: Hanwha Solutions Research & Development Institute, Daejeon 34128, Republic of Korea

7Present address: Department of Biotechnology, Duksung Women’s University, Seoul 01369, Republic of Korea

8Present address: World Institute of Kimchi, Gwangju 61755, Republic of Korea

9Lead contact

Corresponding author : Sang Yup Lee

Abstract

In metabolic engineering, predicting gene overexpression targets remains challenging because both endogenous and heterologous genes in a large metabolic space can be candidates, in contrast to gene knockout targets that are confined to endogenous genes. We report the development of iBridge that identifies positive and negative metabolites exerting positive and negative impacts on product formation, respectively, based on the sum of covariances of their outgoing (consuming) reaction fluxes for a target chemical. Then, "bridge" reactions converting negative metabolites to positive metabolites are identified as overexpression targets, while the opposites as downregulation targets. Using iBridge, overexpression and downregulation targets are suggested for the production of 298 chemicals and validated for 36 chemicals experimentally demonstrated in previous studies. Finally, iBridge is employed to engineer Escherichia coli strains capable of producing 10.3 g/L of D-panthenol, a compound not previously produced, as well as putrescine and 4-hydroxyphenyllactate at enhanced titers, 63.7 and 8.3 g/L, respectively.

논문정보

형식Research article
게재일2023년 11월 (BRIC 등록일 2023-11-09)
연구진국내 연구진
분야 생명과학 > 응용생물화학

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