The circuits themselves are a large part of the prediction problem. “Current circuits are not particularly robust,” notes Collins, as cellular conditions can impact their output and values, especially in larger circuit designs.
But in July 2012, Weiss along with several MIT colleagues described a set of computational tools to guide (but not predict) large-scale circuit design in an article in PLoS Computational Biology. This study examined the use of computational tools to determine the impact of combinations of functional modules on optimal system performance in large circuits. In essence, Weiss and his colleagues programs don't predict circuit output — instead they provide information on the possible impacts components can exert on the circuit.
“Computational analysis here is a parameter; modify a component and it has a large impact on the circuit,” explains Weiss. Perform such analysis repeatedly, and you begin to optimize your circuit design. In this case a modular network for artificial tissue homeostasis was optimized and in the process the researchers discovered that features previous associated with robust circuits (noise attenuation for example) actually were detrimental for this network — a result and observation that Weiss's team owes in no small part to their computational analyses.Engineering for the masses?
For the moment, engineering genetic circuits is still the province of synthetic biologists. Although a growing number of components and modules are available to try from repositories such as The Standard Registry of Biological Parts (partsregistry.org), stringing these together into a working circuit is not as straightforward as one might hope at the moment.
“Getting parts into cells works well now,” says Collins. But he is quick to add that designing circuits that function in the way one would like in a given cell remains the big challenge at the moment.
And while electrical engineers can quickly model and test their systems and designs prior to implementation, it is clear that synthetic biologists do not have this luxury at the moment — a further roadblock for the would-be novice circuit builder.
“Progress is not at that level, therefore experimental characterization of components in isolation must be done,” says Collins. Still, from Weiss's computational strategies for identifying critical components to actually testing component experimentally prior to building a circuit, approaches aimed at understanding and defining circuit design principles seem to be in vogue now. Collins recently reported on what he calls a “gene circuit breadboard” in the journal Nature Methods; a series of vectors to enable rapid construction, and post-assembly tuning, of basic synthetic gene networks (also see sidebar: “Getting it all together”).
In the end, circuit designers are making tremendous progress in understanding how to construct synthetic circuits. The question now is when will design give way to applications? Only the synthetic oscillator in the cell will tell.