Two-stage dynamic deregulation of metabolism improves process robustness & scalability in engineered E. coli

Area of Science:

• Metabolic Engineering
• Synthetic Biology
• Biotechnology

Background:

• Bioprocesses often face challenges with robustness and scalability.
• Traditional optimization methods are time-consuming and costly.
• Dynamic control strategies offer potential solutions for improving bioprocess performance.

Purpose of the Study:

• To investigate the impact of two-stage dynamic control on bioprocess robustness.
• To explore the use of CRISPR interference and controlled proteolysis for enzyme level modulation.
• To demonstrate improved scalability and reduced optimization requirements in industrial chemical synthesis.

Main Methods:

• Implementing two-stage dynamic control during the stationary phase of bioprocesses.
• Utilizing CRISPR interference and controlled proteolysis to reduce key metabolic enzyme levels.
• Analyzing alterations in metabolite pools and metabolic network deregulation.

Main Results:

• Dynamic control significantly improved bioprocess robustness by deregulating central metabolism.
• Reduced enzyme levels led to altered metabolite pools and a less environmentally sensitive metabolic network.
• Validated process robustness and scalability for alanine, citramalate, and xylitol production.

Conclusions:

• Two-stage dynamic control is an effective strategy for enhancing bioprocess robustness and scalability.
• Metabolic deregulation through enzyme level modulation is key to improved process performance.
• Predictive, high-throughput approaches are crucial for advancing metabolic engineering and synthetic biology.