Team:William and Mary/Description
Motivation
Genetic circuits exist in great abundance in nature as complex metabolic pathways which interact
in various ways to perform vital cellular processes. Synthetic biologists aim to not only understand
naturally occurring circuit networks, but also to modify them or to conceptualize and build entirely
new circuits.
The inherent versatility of synthetic genetic circuitry has lead to a vast array of diverse applications
in countless fields. However, the field remains fundamentally limited by the magnitude and specificity of
behavioral control over genetic circuits and circuit networks. These limitations can be boiled down to two
essential problems: inherent constraints to behavior based on the nature of a circuit’s constituent genes,
and the inefficiency of the “design-build-test” cycle which is relied upon for the construction of effective
circuit models.
The fundamental constraints of integral circuit components limit the ability to design and construct
genetic circuits of arbitrary and highly specific behavior. When constructing a circuit with some intended
behavior, design is limited by the available input-specific regulators to gene expression and their
characteristic regulatory behavior. In order to achieve more precise behavioral control, the ability to
tune expression levels of regulatory elements to some desired level is vital. This limitation highlights
the need for genetic devices that can modify the behavior of arbitrary genetic circuits; implementing these
devices would enable precise behavioral control invariant to the constraints of the constituent genes that
make up the circuit in question [1].
The other foundational limitation of genetic circuit construction addresses the inefficiency and
unpredictability of the design and construction process itself. The progression from synthesizing parts
into a circuit on a plasmid, to transformation and testing in vivo, is a lengthy and expensive process
which furthermore is largely variable in terms of actual functionality of the final product [2].This often
leads to a series of trial-and-error testing cycles whose products maintain a persistent level of uncertainty
with regard to precise, predictable behavior. Although it is possible to achieve functional genetic circuits
in this capacity, greater problems arise regarding the tunability of the product. The success of any genetic
circuit relies on the ability to precisely tune a response to a range of input concentrations; it would therefore
be desirable to obtain a reliable method for tuning circuit response, ideally without the need to rewire the
internal workings of the circuit. This method would allow control over output expression to be implemented in
a more rapid and predictable manner [3].
Description
