title: Strategy revealing phenotypic differences among synthetic oscillator designs.
abstract: Considerable progress has been made in identifying and characterizing the component parts of genetic oscillators, which play central roles in all organisms. Nonlinear interaction among components is sufficiently complex that mathematical models are required to elucidate their elusive integrated behavior. Although natural and synthetic oscillators exhibit common architectures, there are numerous differences that are poorly understood. Utilizing synthetic biology to uncover basic principles of simpler circuits is a way to advance understanding of natural circadian clocks and rhythms. Following this strategy, we address the following questions: What are the implications of different architectures and molecular modes of transcriptional control for the phenotypic repertoire of genetic oscillators? Are there designs that are more realizable or robust? We compare synthetic oscillators involving one of three architectures and various combinations of the two modes of transcriptional control using a methodology that provides three innovations: a rigorous definition of phenotype, a procedure for deconstructing complex systems into qualitatively distinct phenotypes, and a graphical representation for illuminating the relationship between genotype, environment, and the qualitatively distinct phenotypes of a system. These methods provide a global perspective on the behavioral repertoire, facilitate comparisons of alternatives, and assist the rational design of synthetic gene circuitry. In particular, the results of their application here reveal distinctive phenotypes for several designs that have been studied experimentally as well as a best design among the alternatives that has yet to be constructed and tested.
authors.affiliation: Department of Biomedical Engineering and ‡Microbiology Graduate Group, University of California , Davis, California 95616, United States.
authors.forename: Jason G
authors.initials: JG
authors.lastname: Lomnitz
authors.forename: Michael A
authors.initials: MA
authors.lastname: Savageau
mesh_terms: D000465:Algorithms; D004926:Escherichia coli / Q000378:metabolism; D025461:Feedback, Physiological; D007700:Kinetics; D008962:Models, Theoretical; D010641:Phenotype; D012333:RNA, Messenger / Q000378:metabolism; D012097:Repressor Proteins / Q000235:genetics; D014158:Transcription, Genetic
chemical_list: D012333:RNA, Messenger; D012097:Repressor Proteins
keywords: circuit architecture; dynamic phenotypes; mathematically controlled comparison; mode of transcription control; system design space