Designing a hybrid in silico/in-cell controller robust to process-model mismatch associated with dynamically regulated enzyme overexpression

Abstract Discrepancy between model predictions and actual processes, known as process–model mismatch (PMM), remains a serious challenge in bioprocess optimization. Previously, we proposed the hybrid in silico/in-cell controller (HISICC) concept combining model-based optimization with cell-based feedback to address the PMM problem. Herein, this approach was advanced to regulate intracellular concentrations of rate-limiting enzymes. Advanced HISICC was demonstrated using an engineered Escherichia coli strain for fatty acid production (FA3). This strain harbors an in-cell feedback controller, which decelerates acetyl-CoA carboxylase (ACC) overexpression in response to sensing the concentration of malonyl-CoA formed by this enzyme. A mathematical model for FA3 was constructed and validated using experimental data. Simulations assuming various PMM revealed that the HISICC using FA3 effectively mitigates toxicity from excessive ACC by robustly adapting braking its overexpression, minimizing yield loss. This study confirmed HISICC as a viable strategy for enhancing bioprocess efficiency, especially in balancing the bottleneck enzyme levels.