"Because biological systems exhibit functional complexity at multiple
scales, a big question has been whether effective design tools can be
created to increase the sizes and complexities of the microbial systems
we engineer to meet specific needs," says Jay Keasling, director of JBEI
and a world authority on synthetic biology and metabolic engineering.
"Our work establishes a foundation for developing CAD platforms to
engineer complex RNA-based control systems that can process cellular
information and program the expression of very large numbers of genes.
Perhaps even more importantly, we have provided a framework for studying
RNA functions and demonstrated the potential of using biochemical and
biophysical modeling to develop rigorous design-driven engineering
strategies for biology."
JBEI researchers have developed CAD-type tools for engineering RNA
components that hold enormous potential for microbial-based production
of advanced biofuels and other goods now derived from petrochemicals.
Keasling, who also holds appointments with the Lawrence Berkeley
National Laboratory (Berkeley Lab) and the University of California (UC)
Berkley, is the corresponding author of a paper in the journal Science
that describes this work. The paper is titled "Model-driven engineering
of RNA devices to quantitatively-program gene expression." Other
co-authors are James Carothers, Jonathan Goler and Darmawi Juminaga.
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," says
Carothers, a bioengineer and lead author of the Science paper
who is a member of Keasling's research groups with both JBEI and the
California Institute for Quantitative Biosciences. "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."
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-percent
correlation -- between predicted and measured gene expression levels.
"We needed to formulate models that would be sophisticated enough to
capture the details required for simulating system functions, but simple
enough to be framed in terms of measurable and tunable component
characteristics or design variables," Carothers says. "We think of
design variables as the parts of the system that can be predictably
modified, in the same way that a chemical engineer might tune the
operation of a chemical plant by turning knobs that control fluid flow
through valves. In our case, knob-turns are represented by specific
kinetic terms for RNA folding and ribozyme catalysis, and our models are
needed to tell us how a combination of these knob-turns will affect
overall system function."
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 clean, green and 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, we're 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," Carothers says.
While the RNA models and simulations developed at JBEI to date fall
short of being a full-fledged RNA CAD platform, Keasling, Carothers and
their coauthors are moving towards that goal.
"We are also actively trying to make our models and simulations more
accessible to researchers who may not want to become RNA control system
experts but would nonetheless like to use our approach and RNA devices
in their own work," Carothers says.
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.
"We recently initiated a research project to investigate how we can
use our approach to engineer RNA-based genetic control systems that will
increase the safety and efficacy of regenerative medicine therapies
that use cultured stem cells to treat diseases such as diabetes and
Parkinson's," Carothers says.
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).
From sciencedaily
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