Designing RNA-Based Genetic Control Systems for Efficient Production from Engineered Metabolic Pathways

Engineered metabolic pathways can
be augmented with dynamic regulatory
controllers to increase production titers by minimizing toxicity and
helping cells maintain homeostasis. We investigated the potential
for dynamic RNA-based genetic control systems to increase production
through simulation analysis of an engineered p-aminostyrene
(p-AS) pathway in E. coli. To map
the entire design space, we formulated 729 unique mechanistic models
corresponding to all of the possible control topologies and mechanistic
implementations in the system under study. Two thousand sampled simulations
were performed for each of the 729 system designs to relate the potential
effects of dynamic control to increases in p-AS production
(total of 3 × 106 simulations). Our analysis indicates
that dynamic control strategies employing aptazyme-regulated expression
devices (aREDs) can yield >10-fold improvements over static control.
We uncovered generalizable trends in successful control architectures
and found that highly performing RNA-based control systems are experimentally
tractable. Analyzing the metabolic control state space to predict
optimal genetic control strategies promises to enhance the design
of metabolic pathways.