Design then mutate.

T development of a systematic design process for synthetic gene regulatory networks is an intriguing prospect that could improve both our understanding of regulatory motifs and our techniques for constructing novel applications. Such a design process would entail analysis tools capable of reliably predicting the in vivo behavior resulting from a given regulatory architecture. As with the process of designing an electrical circuit, the design tools would take the form of a set of equations that could be numerically simulated to predict the output of a given device. This type of ‘‘device genetics’’ would have an important influence on the development of therapeutic applications, as one can envision the design of complex genetic circuits for monitoring or controlling cellular processes. Although the pursuit of a systematic program for modeling genetic circuits is within the constraints of current biotechnology, the deduction of the governing dynamical processes that describe these regulatory networks is not straightforward. Many complications can confound a model description. For example, f luctuations in local concentrations or in the conformational properties of regulatory proteins are not easily reconciled in models that focus on phenomena at the regulatory level. Likewise, proteins can aggregate near the DNA or slide along it, and active processes, such as transport, are not easily incorporated. These contextdependent complications often result in a mismatch between the lump kinetic modeling parameters that are measured in vitro and those that are actually present in vivo. This mismatch can render difficult the forward design of useful genetic circuits. In this issue of PNAS, Yokobayashi et al. (1) address this difficulty by demonstrating how directed evolution can be used to tune a designed gene circuit to a desired behavior. Directed evolution harnesses mechanisms used during natural selection to generate and then identify evolutionary adaptations to novel environmental demands. It typically consists of the introduction of mutations via random mutagenesis or recombination, followed by the selection or screening for properties specified by the experimenter. Although this technique has been widely used to expand the library of enzymes for industrial and research purposes (2), its utility in the design process for gene regulatory networks has not been systematically investigated. In a series of experiments on an engineered gene network, Yokobayashi et al. show how directed evolution can be used to transform a nonfunctional genetic circuit into a library of ‘‘mutant’’ devices that are fully functional in the sense that their behavior is in accordance with the rules that govern logical gates. The starting point for their study was a three-gene network originally explored in ref. 3 by one of the authors of ref. 1 (Weiss). The essential interactions of this regulatory circuit are best understood from left to right in Fig. 1. The lacI gene is expressed from an unregulated promoter Placlq, and its product LacI represses the Plac promoter. Likewise, the Plac promoter controls the expression of the cI gene, and its product CI represses the PR promoter. The PR promoter controls the production of the enhanced yellow fluorescent protein (EYFP), which represents the ‘‘output’’ for the circuit, whereas the chemical inducer isopropyl -D-thiogalactopyranoside (IPTG), which binds to LacI tetramers and renders them unable to repress Plac, provides an external control over the network and thus represents the ‘‘input.’’ Guided by Fig. 1, heuristic reasoning would suggest the following two limiting input output behaviors for this circuit: (i) with no IPTG, LacI shuts off the production of CI so that EYFP is produced, whereas (ii) for large amounts of IPTG, LacI cannot shut off CI and EYFP production is repressed. Thus, as the IPTG concentration is increased, one should observe a transition between these extremes as the output of EYFP proceeds from the ‘‘on’’ to ‘‘off’’ state. Although this logic seems reasonable, the devil turns up in the details as the leaky nature of the Plac promoter leads to the repression of PR regardless of IPTG concentrations, and thus no EYFP output for any input (3). In the parlance of electrical engineering, the first two promoter gene pairs form an implies gate, whereas the last pair is an inverter, and the lack of functionality arises because of a signal mismatch between the gates. Yokobayashi et al. introduced random mutations to the nonfunctional device and successively screened the mutant circuits for those that obeyed the two limiting output behaviors for low and high IPTG inputs. They first used the process of error-prone PCR to introduce mutations targeting the cI gene. They then grew colonies in the absence of IPTG and observed that approximately half of the mutants were fluorescent, indicative of the on state for a functional device. They then selected these functional colonies, grew them in the presence of IPTG, and screened for those that were in the nonfluorescent off state ( 5–10% were observed). Then, because the output of these mutant circuits had responded properly to both limits of the input (with and without IPTG), they were deemed candidates for a functional device and selected for further testing. In this final test, which involved the measurement of fluorescence for each mutant circuit as the concentration of IPTG was increased, they observed circuit responses beginning in the on state then transitioning to the off state. The results demonstrated that a number of