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Generic Protocol for Optimization of Heterologous Protein Production Using Automated Microbioreactor Technology

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Published on: December 15, 2017

Modeling and optimization of a multi-product biosynthesis factory for multiple objectives.

Fook Choon Lee¹, Gade Pandu Rangaiah, Dong-Yup Lee

¹Department of Chemical & Biomolecular Engineering, National University of Singapore, 4 Engineering Drive 4, Singapore 117576, Singapore.

Metabolic Engineering

|January 7, 2010

Summary

This study optimized multi-product biosynthesis in Escherichia coli by developing an augmented metabolic model. Genetic algorithms were used to maximize serine and tryptophan production simultaneously, offering insights into metabolic pathway engineering.

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Area of Science:

Metabolic Engineering
Systems Biology
Biotechnology

Background:

Metabolic pathway optimization is crucial for efficient multi-product biosynthesis.
Understanding flux ratios and enzyme kinetics is key to enhancing microbial production.

Purpose of the Study:

To develop an augmented model for simultaneous optimization of serine and tryptophan flux ratios in Escherichia coli.
To identify optimal metabolic pathway manipulations for maximizing amino acid biosynthesis.

Main Methods:

Linked dynamic tryptophan operon, aromatic amino acid biosynthesis, and central carbon metabolism models.
Estimated six new kinetic parameters using experimental data and published literature.
Employed the elitist non-dominant sorting genetic algorithm (NSGA-II) with pattern recognition heuristics for multi-objective optimization.

Main Results:

Successfully maximized biosynthesis rates of serine and tryptophan simultaneously.
Obtained and elucidated Pareto-optimal enzyme activities for amino acid biosynthesis.
Identified potential improvements in metabolic pathway recipes through multi-objective optimization.

Conclusions:

The augmented model provides a robust framework for optimizing complex metabolic networks.
Genetic algorithms and multi-objective optimization strategies are effective for enhancing microbial biosynthesis.
The study highlights potential advancements in metabolic pathway engineering for industrial applications.