title: Designing RNA-based genetic control systems for efficient production from engineered metabolic pathways.
abstract: 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 × 10(6) 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.
authors.affiliation: Departments of Chemical Engineering and Bioengineering, Molecular Engineering & Sciences Institute, and Center for Synthetic Biology, University of Washington , Seattle, Washington 98195, United States.
authors.forename: Jason T
authors.initials: JT
authors.lastname: Stevens
authors.forename: James M
authors.initials: JM
authors.lastname: Carothers
mesh_terms: D000594:Amino Acid Oxidoreductases / Q000378:metabolism; D004926:Escherichia coli / Q000378:metabolism*; D060847:Metabolic Engineering; D012313:RNA / Q000737:chemistry / Q000378:metabolism*; D020058:Styrene / Q000737:chemistry / Q000378:metabolism
chemical_list: D020058:Styrene; D012313:RNA; D000594:Amino Acid Oxidoreductases
keywords: RNA device; dynamic control; metabolic engineering; simulation; synthetic biology