Skip to main content

Thank you for visiting You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Construction of a genetic toggle switch in Escherichia coli


It has been proposed1 that gene-regulatory circuits with virtually any desired property can be constructed from networks of simple regulatory elements. These properties, which include multistability and oscillations, have been found in specialized gene circuits such as the bacteriophage λ switch2 and the Cyanobacteria circadian oscillator3. However, these behaviours have not been demonstrated in networks of non-specialized regulatory components. Here we present the construction of a genetic toggle switch—a synthetic, bistable gene-regulatory network—in Escherichia coli and provide a simple theory that predicts the conditions necessary for bistability. The toggle is constructed from any two repressible promoters arranged in a mutually inhibitory network. It is flipped between stable states using transient chemical or thermal induction and exhibits a nearly ideal switching threshold. As a practical device, the toggle switch forms a synthetic, addressable cellular memory unit and has implications for biotechnology, biocomputing and gene therapy.

This is a preview of subscription content, access via your institution

Relevant articles

Open Access articles citing this article.

Access options

Rent or buy this article

Prices vary by article type



Prices may be subject to local taxes which are calculated during checkout

Figure 1: Toggle switch design.
Figure 2: Geometric structure of the toggle equations.
Figure 3: The toggle switch plasmid.
Figure 4: Demonstration of bistability.
Figure 5: Toggle switch induction threshold.
Figure 6: TAK117 switching time.


  1. Modod, J. & Jacob, F. General conclusions: teleonomic mechanisms in cellular metabolism, growth and differentiation. Cold Spring Harb. Symp. Quant. Biol. 26, 389–401 (1961).

    Article  Google Scholar 

  2. Ptashne, M. A Genetic Switch: Phage λ and Higher Organisms (Cell, Cambridge, Massachusetts, 1992).

    Google Scholar 

  3. Ishiura, M. et al. Expression of a gene cluster kaiABC as a circadian feedback process in cyanobacteria. Science 281, 1519–1523 (1998).

    Article  ADS  CAS  PubMed  Google Scholar 

  4. Schellenberger, W., Eschrich, K. & Hofmann, E. Self-organization of a glycolytic reconstituted enzyme system: alternate stable stationary states, hysteretic transitions and stabilization of the energy charge. Adv. Enzyme Regul. 19, 257–284 (1980).

    Article  CAS  PubMed  Google Scholar 

  5. Glass, L. & Kauffman, S. A. The logical analysis of continuous, non-linear biochemical control networks. J. Theor. Biol. 39, 103–129 (1973).

    Article  CAS  PubMed  Google Scholar 

  6. Glass, L. Classification of biological networks by their qualitative dynamics. J. Theor. Biol. 54, 85–107 (1975).

    Article  CAS  PubMed  Google Scholar 

  7. Glass, L. Combinatorial and topological methods in nonlinear chemical kinetics. J. Chem. Phys. 63, 1325–1335 (1975).

    Article  ADS  CAS  Google Scholar 

  8. Kauffman, S. The large scale structure and dynamics of gene control circuits: an ensemble approach. J. Theor. Biol. 44, 167– 190 (1974).

    Article  CAS  PubMed  Google Scholar 

  9. Thomas, R. Logical analysis of systems comprising feedback loops. J. Theor. Biol. 73, 631–656 ( 1978).

    Article  CAS  PubMed  Google Scholar 

  10. Thomas, R. Regulatory networks seen as asynchronous automata: a logical description. J. Theor. Biol. 153, 1– 23 (1991).

    Article  Google Scholar 

  11. Tchuraev, R. N. A new method for the analysis of the dynamics of the molecular genetic control systems. I. Description of the method of generalized threshold models. J. Theor. Biol. 151, 71–87 (1991).

    Article  CAS  PubMed  Google Scholar 

  12. Arkin, A. & Ross, J. Computational functions in biochemical reaction networks. Biophys. J. 67, 560– 578 (1994).

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  13. Bhalla, U. S. & Iyengar, R. Emergent properties of networks of biological signaling pathways. Science 283, 381–387 (1999).

    Article  ADS  CAS  PubMed  Google Scholar 

  14. Yagilo, G. & Yagil, E. On the relation between effector concentration and the rate of induced enzyme synthesis. Biophys. J. 11, 11–27 (1971).

    Article  ADS  Google Scholar 

  15. Shea, M. A. & Ackers, G. K. The OR control system of bacteriophage Lambda: a physical-chemical model for gene regulation. J. Mol. Biol. 181, 211–230 (1985).

    Article  CAS  PubMed  Google Scholar 

  16. Smith, T. F., Sadler, J. R. & Goad, W. Statistical–mechanical modeling of a regulatory protein: the Lactose repressor. Math. Biosci. 36, 61–86 (1977).

    Article  CAS  Google Scholar 

  17. Arkin, A., Ross, J. & McAdams, H. H. Stochastic kinetic analysis of developmental pathway bifurcation in phage λ-infected Escherichia coli cells. Genetics 149, 1633–1648 (1998).

    CAS  PubMed  PubMed Central  Google Scholar 

  18. McAdams, H. H. & Arkin, A. Stochastic mechanisms in gene expression. Proc. Natl Acad. Sci. USA 94, 814–819 (1997).

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  19. McAdams, H. H. & Arkin, A. Stimulation of prokaryotic genetic circuits. Annu. Rev. Biophys. Biomol. Struct. 27, 199–224 (1998).

    Article  CAS  PubMed  Google Scholar 

  20. Lutz, R. & Bujard, H. Independent and tight regulation of transcriptional units in Escherichia coli via the LacR/O, the TetR/O and AraC/I1-I2 regulatory elements. Nucleic Acids Res. 25, 1203–1210 (1997).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Cormack, B. P., Valdivia, R. H. & Falkow, S. FACS-optimized mutants of the green fluorescent protein (GFP). Gene 173, 33–38 (1996).

    Article  CAS  PubMed  Google Scholar 

  22. Ausubel, F. M. et al. Current Protocols in Molecular Biology (Wiley, New York, 1987).

    Google Scholar 

  23. Sambrook, J., Fritsch, E. F. & Maniatis, T. Molecular Cloning: A Laboratory Manual (Cold Spring Harbor Laboratory Press, Plainview, New York, 1989).

    Google Scholar 

  24. Edelstein-Keshet, L. Mathematical Models in Biology (McGraw-Hill, New York, 1988).

    MATH  Google Scholar 

  25. Kaplan, D. & Glass, L. Understanding Nonlinear Dynamics (Springer, New York, 1995).

    Book  Google Scholar 

  26. Yagil, E. & Yagil, G. On the relation between effector concentration and the rate of induced enzyme synthesis. Biophys. J. 11, 11–27 (1971).

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  27. Rubinow, S. I. Introduction to Mathematical Biology (Wiley, New York, 1975).

    MATH  Google Scholar 

Download references


We thank M. Bitensky and T. Yoshida for providing access to their flow cytometer; Y. Yu for his suggestions on plasmid construction; C. Sabanayagam for his technical advice; and C. Chow for his mathematical advice. This work was supported by the Office of Naval Research and the College of Engineering at Boston University.

Author information

Authors and Affiliations


Corresponding author

Correspondence to James J. Collins.

Additional information

Center for Advanced Biotechnology, Boston University, 44 Cummington Street, Boston, Massachusetts 02215, USA

Supplementary information

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Gardner, T., Cantor, C. & Collins, J. Construction of a genetic toggle switch in Escherichia coli. Nature 403, 339–342 (2000).

Download citation

  • Received:

  • Accepted:

  • Issue Date:

  • DOI:

This article is cited by


By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.


Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing