A hybrid in silico/in-cell controller that handles process-model mismatches using intracellular biosensing

Area of Science:

• Biotechnology
• Synthetic Biology
• Metabolic Engineering

Background:

• Process-model mismatch (PMM) is a significant hurdle in optimizing bioprocesses.
• A hybrid in silico/in-cell controller (HISICC) was previously developed to integrate model-based optimization with cell-based feedback.
• Intracellular feedback mechanisms are crucial for robust bioprocess control.

Purpose of the Study:

• To extend the HISICC approach for regulating key enzyme levels via intracellular biosensing.
• To enhance bioprocess control by addressing limitations imposed by process-model mismatch.
• To improve yields in engineered microbial systems through advanced regulatory strategies.

Main Methods:

• Implementation of an extended HISICC in an engineered Escherichia coli strain (FA3) for fatty acid production.
• Genetic engineering of E. coli with a feedback controller for acetyl-CoA carboxylase (ACC) expression, responsive to malonyl-CoA levels.
• Modeling of the FA3 strain to enable HISICC optimization of an inducer input for enzyme expression.

Main Results:

• Simulations demonstrated that the HISICC effectively mitigated rapid ACC accumulation caused by PMMs, preventing cytotoxic levels.
• The HISICC approach led to improved fatty acid yields in the engineered E. coli.
• The study confirmed the utility of intracellular biosensing for managing PMMs in bioprocesses.

Conclusions:

• The extended HISICC offers a promising strategy for bioprocess optimization, particularly when dealing with process-model mismatch.
• Intracellular biosensing and feedback control are vital for precise regulation of enzyme expression and metabolic pathways.
• This approach has significant potential for improving the efficiency and yield of microbial cell factories.