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Optimizing the downstream MVA pathway using a combination optimization strategy to increase lycopene yield in
Tao Cheng1,2, Lili Wang3, Chao Sun4,5
1State Key Laboratory Base of Eco-Chemical Engineering, College of Chemistry and Molecular Engineering, Qingdao University of Science and Technology, No. 53 Zhengzhou Road, Qingdao, 266042, China. chengtao@qibebt.ac.cn.
Microbial Cell Factories
|June 19, 2022
Summary
Engineered E. coli produced 4.6 times more lycopene by optimizing the mevalonate pathway using ribosome binding site libraries. This metabolic engineering approach enhances lycopene production for industrial applications.
Area of Science:
- Metabolic Engineering
- Synthetic Biology
- Biotechnology
Background:
- Lycopene demand is rising in pharmaceutical and food sectors.
- Escherichia coli is engineered for lycopene production via heterologous pathways.
- Optimizing complex metabolic pathways in E. coli remains challenging.
Purpose of the Study:
- To enhance lycopene yield in E. coli by optimizing the mevalonate pathway.
- To improve inter-module balance in the lycopene synthetic pathway.
- To develop a robust lycopene production platform using metabolic engineering.
Main Methods:
- Introduced heterologous lycopene pathway into E. coli, divided into modules.
- Utilized ribosome binding site (RBS) libraries to fine-tune expression of MVA pathway genes (MVK, PMK, MVD, IDI).
- Employed high-throughput screening for lycopene color to select high-yield strains.
Main Results:
- Achieved a lycopene yield of 219.7 mg/g DCW, a 4.6-fold increase over the reference strain.
- Successfully balanced metabolic flux through strategic optimization of downstream MVA pathway enzymes.
- Developed a library of engineered E. coli strains for lycopene production.
Conclusions:
- Fine-tuning MVA pathway enzyme expression via RBS libraries effectively enhances lycopene metabolic flux.
- The developed strategy provides a valuable reference for synthesizing other terpenoids.
- High-yield lycopene production in E. coli was achieved through precise metabolic pathway optimization.
