EVOLUTIONARY DESIGN OF GENETIC CIRCUITS AND CELL-CELL COMMUNICATIONS

Yohei Yokobayashi, Cynthia H. Collins, Jared R. Leadbetter, Frances H. Arnold () and Ron Weiss ()
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Yohei Yokobayashi: Division of Chemistry and Chemical Engineering, California Institute of Technology, 1200 E. California Blvd, Pasadena, CA 91125, USA
Cynthia H. Collins: Biochemistry and Molecular Biophysics, California Institute of Technology, 1200 E. California Blvd, Pasadena, CA 91125, USA
Jared R. Leadbetter: Division of Engineering and Applied Science, California Institute of Technology, 1200 E. California Blvd, Pasadena, CA 91125, USA
Frances H. Arnold: Division of Chemistry and Chemical Engineering, California Institute of Technology, 1200 E. California Blvd, Pasadena, CA 91125, USA
Ron Weiss: Department of Electrical Engineering, Princeton University, B-312, E-Quad, Princeton, NJ 08544, USA

Advances in Complex Systems (ACS), 2003, vol. 06, issue 01, pages 37-45

Abstract: Synthetic genetic circuits are artificial networks of transcriptional control elements inserted into living cells in order to 'program' cellular behavior. We can extend this application to programming population behavior by incorporating cell-cell communications capabilities. By designing and building such networks, cellular circuit engineers expect to gain insight into how natural genetic networks function with remarkable robustness, stability, and adaptability to changing environments. Programmed cells also have promising applications in biotechnology and medicine. A major challenge that biological circuit engineers face is the difficulty of predicting circuit performance at the design stage, with the consequence that actual construction requires significant experimental effort, even for very simple circuits. To address this fundamental obstacle we propose the use of laboratory evolution methods to create new circuit components and optimize circuit performance inside living cells.

Keywords: Genetic circuit; directed evolution; quorum sensing; cell-cell communications; genetic regulatory networks (search for similar items in EconPapers)
Date: 2003
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