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Dynamic, autonomous gene expression system for self-adaptation and self-regulation in microbial production.
Sang Myeong Bae1, Minki Chung1, Joo Yeon Lee1
1School of Integrative Engineering, Chung-Ang University, 84 Heukseok-ro, Dongjak-gu, Seoul 06974, Republic of Korea.
Biotechnology Advances
|April 6, 2026
Summary
Autonomous genetic regulation enables microbes to adapt in real-time to dynamic fermentation conditions. These self-adaptive systems balance cellular growth and chemical production, overcoming limitations of static engineering strategies for robust microbial cell factories.
Area of Science:
- Synthetic biology and metabolic engineering
- Biotechnology and bioprocessing
- Control theory in biological systems
Background:
- Static metabolic engineering strategies struggle with dynamic fermentation environments, creating growth-production trade-offs.
- Engineered microbes face limitations in productivity and stability due to conflicting demands between metabolic flux and cellular fitness.
- External environmental controls are labor-intensive and difficult to scale for managing microbial production.
Purpose of the Study:
- To review recent advances in autonomous genetic regulation for microbial cell factories.
- To explore single-cell and population-level dynamic control strategies.
- To discuss design principles and future perspectives for intelligent microbial production systems.
Main Methods:
- Summarizing progress in autonomous single-cell regulation (metabolite- and cell burden-responsive systems).
- Reviewing population-level strategies (quorum-sensing- and pH-responsive systems).
- Highlighting feedback and feedforward control architectures for stability and adaptation.
Main Results:
- Autonomous genetic circuits integrate sensing, feedback, and control modules for real-time adaptation.
- Dynamic circuits maintain cellular homeostasis while optimizing metabolic flux.
- Strategies enable microbes to respond to intracellular and environmental cues, improving performance.
Conclusions:
- Autonomous regulation is key to overcoming limitations of static engineering in microbial production.
- Next-generation cell factories require integration of systems biology, synthetic biology, and control theory.
- Intelligent microbial systems can autonomously optimize performance in fluctuating bioprocessing conditions.
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