Genetic circuit building blocks for cellular computation, communications, and signal processing

  • Authors:

  • Ron Weiss;Subhayu Basu;Sara Hooshangi;Abigail Kalmbach;David Karig;Rishabh Mehreja;Ilka Netravali

  • Affiliations:

  • Electrical Engineering Department, Princeton University, Engineering Quad, B312, Princeton, NJ 08540, USA&semi/ Author for correspondence, e-mail: rweiss@princeton.edu;Electrical Engineering Department, Princeton University, Engineering Quad, B312, Princeton, NJ 08540, USA;Electrical Engineering Department, Princeton University, Engineering Quad, B312, Princeton, NJ 08540, USA;Electrical Engineering Department, Princeton University, Engineering Quad, B312, Princeton, NJ 08540, USA;Electrical Engineering Department, Princeton University, Engineering Quad, B312, Princeton, NJ 08540, USA;Electrical Engineering Department, Princeton University, Engineering Quad, B312, Princeton, NJ 08540, USA;Electrical Engineering Department, Princeton University, Engineering Quad, B312, Princeton, NJ 08540, USA

  • Venue:
  • Natural Computing: an international journal
  • Year:
  • 2003

Quantified Score

Hi-index 0.00

Visualization

Abstract

In this paper, we review an emerging engineering discipline to programcell behaviors by embedding synthetic gene networks that performcomputation, communications, and signal processing. To accomplishthis goal, we begin with a genetic component library and a biocircuitdesign methodology for assembling these components into compoundcircuits. The main challenge in biocircuit design lies in selectingwell-matched genetic components that when coupled, reliably producethe desired behavior. We use simulation tools to guide circuitdesign, a process that consists of selecting the appropriatecomponents and genetically modifying existing components until thedesired behavior is achieved. In addition to such rational design, wealso employ directed evolution to optimize genetic circuitbehavior. Building on Nature's fundamental principle of evolution,this unique process directs cells to mutate their own DNA until theyfind gene network configurations that exhibit the desired systemcharacteristics. The integration of all the above capabilities infuture synthetic gene networks will enable cells to performsophisticated digital and analog computation, both asindividual entities and as part of larger cell communities. Thisengineering discipline and its associated tools will advance thecapabilities of genetic engineering, and allow us to harness cells fora myriad of applications not previously achievable.