Functional complexity that emerges from component interactions is a universal feature of physical systems. As a consequence, in most engineering disciplines, tools for simulating and designing global functions from local component behaviors are essential for constructing complex devices and systems. Biological systems exhibit functional complexity across multiple scales, from RNA, DNA, and protein subunit interactions to those among genes, pathways, circuits, and cells. Creating biological design tools applicable to each of these scales will be crucial for increasing the sizes and complexities of the synthetic biological systems engineered for therapeutic applications or for drugs, fuels, and materials production.

In nature, RNA structures process cellular information and regulate genetic expression at the levels of transcription, translation, and RNA degradation. Synthetic aptamers, ribozymes (rbzs), and aptazymes (aptzs) assembled into static or dynamic ligand-responsive regulators can control gene expression in bacteria, yeast, and mammalian cells. Given this functional potential, creating methods to rapidly assemble RNA-regulated devices with predictable activities should allow engineering of programmable pathway and circuit controllers and higher-order information-processing mechanisms.

We developed design-driven approaches for engineering static, rbz-regulated expression devices (rREDs) and dynamic, ligand-controlled, aptz-regulated expression devices (aREDs) with quantitatively predictable functions.

—Carothers et al.

Synthetic biology is an emerging scientific field in which novel biological devices, such as molecules, genetic circuits or cells, are designed and constructed, or existing biological systems, such as microbes, are re-designed and engineered. A major goal is to produce valuable chemical products from simple, inexpensive and renewable starting materials in a sustainable manner. As with other engineering disciplines, CAD tools for simulating and designing global functions based upon local component behaviors are essential for constructing complex biological devices and systems. However, until this work, CAD-type models and simulation tools for biology have been very limited.

Identifying the relevant design parameters and defining the domains over which expected component behaviors are exerted have been key steps in the development of CAD tools for other engineering disciplines. We’ve applied generalizable engineering strategies for managing functional complexity to develop CAD-type simulation and modeling tools for designing RNA-based genetic control systems. Ultimately we’d like to develop CAD platforms for synthetic biology that rival the tools found in more established engineering disciplines, and we see this work as an important technical and conceptual step in that direction.

—James Carothers

Keasling, Carothers and their co-authors focused their design-driven approach on RNA sequences that can fold into complicated three-dimensional shapes, called ribozymes and aptazymes. Like proteins, ribozymes and aptazymes can bind metabolites, catalyze reactions and act to control gene expression in bacteria, yeast and mammalian cells. Using mechanistic models of biochemical function and kinetic biophysical simulations of RNA folding, ribozyme and aptazyme devices with quantitatively predictable functions were assembled from components that were characterized in vitro, in vivo and in silico. The models and design strategy were then verified by constructing 28 genetic expression devices for the Escherichia coli bacterium. When tested, these devices showed excellent agreement—94% correlation—between predicted and measured gene expression levels.

Our work establishes a foundation for developing computer-aided design platforms to engineer complex RNA-based control systems that can process cellular information and program the expression of very large numbers of genes, enabling both increased understanding of fundamental biological processes and applications to meet demands for new therapies, renewable fuels, and chemicals.

—Carothers et al.

JBEI researchers are now using their RNA CAD-type models and simulations as well as the ribozyme and aptazyme devices they constructed to help them engineer metabolic pathways that will increase microbial fuel production. JBEI is one of three DOE Bioenergy Research Centers established by DOE’s Office of Science to advance the technology for the commercial production of renewable biofuels. A key to JBEI’s success will be the engineering of microbes that can digest lignocellulosic biomass and synthesize from the sugars transportation fuels that can replace gasoline, diesel and jet fuels in today’s engines.

In addition to advanced biofuels, the team is also looking into engineering microbes to produce chemicals from renewable feedstocks that are difficult to produce cheaply and in high yield using traditional organic chemistry technology.

While the work at JBEI focused on E. coli and the microbial production of advanced biofuels, the authors of the Science paper believe that their concepts could also be used for programming function into mammalian systems and cells.

This research was supported in part by grants from the DOE Office of Science through JBEI, and the National Science Foundation through the Synthetic Biology Engineering Research Center (SynBERC).

Resources

• James M. Carothers, Jonathan A. Goler, Darmawi Juminaga, and Jay D. Keasling (2011) Model-Driven Engineering of RNA Devices to Quantitatively Program Gene Expression. Science 334 (6063), 1716-1719 doi: 10.1126/science.1212209