reconstructed genetic circuits are to understand how different aspects of circuit architecture contribute to function, to determine what functional tradeoffs are inherent in the design of the circuit, and to establish the sufficiency of particular circuit designs for given biological functions. More generally, they provide a complementary path to identifying both particular circuit interactions and general principles of gene circuit operation.
A reconstructive approach to genetic circuits may allow us to design circuits with unique properties and may provide insight into their underlying mechanisms. With a synthetic approach, it may be possible to construct a replica of a particular natural genetic circuit out of well-understood components and monitor its exact function in living cells. Using a synthetic approach, we could test the sufficiency of an arbitrary circuit made up of well-characterized components for generating a particular function. A major advantage to this approach is that we may be able to study the circuit mechanism without impairing cellular functions or inducing downstream consequences which are often drawbacks of traditional perturbation approaches. Finally, different circuit designs with similar functions can be directly compared to determine the precise properties each design grants a network as well as their relative advantages and disadvantages in particular cellular contexts. Ultimately, these studies may provide us with a deep enough understanding that we can design circuits that perform novel biological functions and we can exploit synthetic circuitry to reveal basic principles about natural circuit design.
Nonetheless, the synthetic approach faces many obstacles. For example, while we often know the components in a circuit, we frequently do not have in vivo information regarding kinetic parameters (affinities, binding and degradation rates, etc.). How can we infer these values if we cannot or have not measured them directly? Additionally, the intracellular environment is intrinsically “noisy,” and small copy numbers of molecular species limit the predictability of biochemical reactions. How can we interpret or predict circuit functions in the face of such noise? Can we devise synthetic circuits that suppress such noise to operate reliably, or take advantage of such noise to enable probabilistic cellular behaviors?
What are the major advantages and limitations of synthetic circuits as a means of understanding the principles of genetic circuit design?