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Current and future modalities of dynamic control in metabolic engineering
Makoto A Lalwani1, Evan M Zhao1, José L Avalos2
1Department of Chemical and Biological Engineering, Hoyt Laboratory, Princeton University, 25 William Street, Princeton, NJ 08544, USA.
Current Opinion in Biotechnology
|March 26, 2018
Summary
Metabolic engineering uses dynamic control to balance cell health and product generation. Integrating biosensors with computer control offers future potential for optimizing valuable compound production.
Area of Science:
- Metabolic engineering and synthetic biology
- Biotechnology and bioprocess engineering
Background:
- Cellular production of valuable compounds faces a conflict between host organism health and product yield.
- Current dynamic control strategies include two-phase fermentations and pathway autoregulation.
- These methods aim to optimize product formation while maintaining cellular viability.
Purpose of the Study:
- To review recent advancements in dynamic control strategies for metabolic engineering.
- To explore the integration of biosensors and computer-assisted feedback control for enhanced metabolic engineering.
- To highlight the potential of advanced dynamic control for maximizing cellular production.
Main Methods:
- Literature review of dynamic control applications in metabolic engineering.
- Analysis of open-loop and closed-loop control modalities.
- Exploration of biosensor and feedback control system integration.
Main Results:
- Dynamic control strategies, including decoupling growth and production, are crucial for metabolic engineering.
- Open-loop and closed-loop control offer advanced methods for optimizing the production phase.
- Biosensor and computer-assisted feedback control represent a promising frontier.
Conclusions:
- Dynamic control is essential for overcoming the trade-off between cellular health and product formation in metabolic engineering.
- Advanced control modalities, particularly those involving real-time monitoring and feedback, hold significant promise for future applications.
- Integrating biosensors with computer control can lead to more efficient and robust cellular production systems.
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