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

The discrepancy between model predictions and actual processes, known as process-model mismatch (PMM), remains a substantial challenge in bioprocess optimization. We previously introduced a hybrid in silico/in-cell controller (HISICC) that combines model-based optimization with cell-based feedback to address this problem. Here, we extended this approach to regulate a key enzyme level using intracellular biosensing.

A hybrid in silico/in-cell controller for microbial bioprocesses with process-model mismatch.

Bioprocess optimization using mathematical models is prevalent, yet the discrepancy between model predictions and actual processes, known as process-model mismatch (PMM), remains a significant challenge. This study proposes a novel hybrid control system called the hybrid in silico/in-cell controller (HISICC) to address PMM by combining model-based optimization (in silico feedforward controller) with feedback controllers utilizing synthetic genetic circuits integrated into cells (in-cell feedback controller). We demonstrated the efficacy of HISICC using two engineered Escherichia coli strains, TA1415 and TA2445, previously developed for isopropanol (IPA) production.