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Multi-scale data-driven engineering for biosynthetic titer improvement.

Zhixing Cao¹, Jiaming Yu², Weishan Wang³

¹State Key Laboratory of Bioreactor Engineering, East China University of Science and Technology, Shanghai 200237, China; MOE Key Laboratory of Advanced Control and Optimization for Chemical Processes, East China University of Science and Technology, Shanghai 200237, China.

Current Opinion in Biotechnology

|June 3, 2020

Summary

Improving industrial biosynthesis titers is challenging. This review details advanced metabolic pathway rewiring and data-driven optimization for enhanced production efficiency.

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Area of Science:

Biotechnology and metabolic engineering.

Background:

Industrial biosynthesis involves complex interactions between genes, metabolites, and bioreactor conditions.
Identifying optimal microbial strains for high-titer production is a significant challenge.

Purpose of the Study:

To review state-of-the-art methods for improving biosynthesis titers across various scales.
To highlight advancements in metabolic pathway rewiring and data-driven process control.

Main Methods:

Summarizing current literature on biosynthesis titer improvement strategies.
Focusing on metabolic pathway engineering and process optimization techniques.

Main Results:

Metabolic pathway rewiring offers significant potential for enhancing product yields.
Data-driven process optimization and control enable more refined quantitative insights.

Conclusions:

Integrating multi-scale data and mathematical modeling is crucial for achieving higher biosynthesis titers.
Advanced strategies are essential for overcoming the complexities of industrial biosynthesis.