Skip to main content

Thank you for visiting nature.com. 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.

  • Article
  • Published:

Fundamental limits on the suppression of molecular fluctuations

Abstract

Negative feedback is common in biological processes and can increase a system’s stability to internal and external perturbations. But at the molecular level, control loops always involve signalling steps with finite rates for random births and deaths of individual molecules. Here we show, by developing mathematical tools that merge control and information theory with physical chemistry, that seemingly mild constraints on these rates place severe limits on the ability to suppress molecular fluctuations. Specifically, the minimum standard deviation in abundances decreases with the quartic root of the number of signalling events, making it extremely expensive to increase accuracy. Our results are formulated in terms of experimental observables, and existing data show that cells use brute force when noise suppression is essential; for example, regulatory genes are transcribed tens of thousands of times per cell cycle. The theory challenges conventional beliefs about biochemical accuracy and presents an approach to the rigorous analysis of poorly characterized biological systems.

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

Access options

Buy this article

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

Figure 1: Schematic of optimal control networks and information loss.
Figure 2: Hard limits on standard deviations.
Figure 3: Plasmid replication control.

Similar content being viewed by others

References

  1. Ozbudak, E. M., Thattai, M., Kurtser, I., Grossman, A. D. & van Oudenaarden, A. Regulation of noise in the expression of a single gene. Nature Genet. 31, 69–73 (2002)

    Article  CAS  Google Scholar 

  2. Elowitz, M. B., Levine, A. J., Siggia, E. D. & Swain, P. S. Stochastic gene expression in a single cell. Science 297, 1183–1186 (2002)

    Article  ADS  CAS  Google Scholar 

  3. Newman, J. R. et al. Single-cell proteomic analysis of S. cerevisiae reveals the architecture of biological noise. Nature 441, 840–846 (2006)

    Article  ADS  CAS  Google Scholar 

  4. Golding, I., Paulsson, J., Zawilski, S. M. & Cox, E. C. Real-time kinetics of gene activity in individual bacteria. Cell 123, 1025–1036 (2005)

    Article  CAS  Google Scholar 

  5. Paulsson, J. & Ehrenberg, M. Noise in a minimal regulatory network: plasmid copy number control. Q. Rev. Biophys. 34, 1–59 (2001)

    Article  CAS  Google Scholar 

  6. Paulsson, J. Summing up the noise in gene networks. Nature 427, 415–418 (2004)

    Article  ADS  CAS  Google Scholar 

  7. Dublanche, Y., Michalodimitrakis, K., Kuemmerer, N., Foglierini, M. & Serrano, L. Noise in transcription negative feedback loops: simulation and experimental analysis. Mol. Syst. Biol. 2, 41 (2006)

    Article  Google Scholar 

  8. Barkai, N. & Shilo, B. Z. Variability and robustness in biomolecular systems. Mol. Cell 28, 755–760 (2007)

    Article  CAS  Google Scholar 

  9. Maxwell, J. On governors. Proc. R. Soc. Lond. 16, 270–283 (1867)

    MATH  Google Scholar 

  10. Cover, T. M. & Thomas, J. A. Elements of Information Theory 2nd edn (Wiley, 1991)

    Book  Google Scholar 

  11. Pedraza, J. M. & Paulsson, J. Effects of molecular memory and bursting on fluctuations in gene expression. Science 319, 339–343 (2008)

    Article  ADS  CAS  Google Scholar 

  12. Cai, L., Friedman, N. & Xie, X. S. Stochastic protein expression in individual cells at the single molecule level. Nature 440, 358–362 (2006)

    Article  ADS  CAS  Google Scholar 

  13. Tkacik, G., Callan, C. G., Jr & Bialek, W. Information flow and optimization in transcriptional regulation. Proc. Natl Acad. Sci. USA 105, 12265–12270 (2008)

    Article  ADS  CAS  Google Scholar 

  14. Savageau, M. A. Parameter sensitivity as a criterion for evaluating and comparing the performance of biochemical systems. Nature 229, 542–544 (1971)

    Article  ADS  CAS  Google Scholar 

  15. Keizer, J. Statistical Thermodynamics of Nonequilibrium Processes (Springer, 1987)

    Book  Google Scholar 

  16. Singh, A. & Hespanha, J. P. Optimal feedback strength for noise suppression in autoregulatory gene networks. Biophys. J. 96, 4013–4023 (2009)

    Article  ADS  CAS  Google Scholar 

  17. Korobkova, E. A., Emonet, T., Park, H. & Cluzel, P. Hidden stochastic nature of a single bacterial motor. Phys. Rev. Lett. 96, 058105 (2006)

    Article  ADS  Google Scholar 

  18. Doan, T., Mendez, A., Detwiler, P. B., Chen, J. & Rieke, F. Multiple phosphorylation sites confer reproducibility of the rod’s single-photon responses. Science 313, 530–533 (2006)

    Article  ADS  CAS  Google Scholar 

  19. Martins, N. C., Dahleh, M. A. & Doyle, J. C. Fundamental limitations of disturbance attenuation in the presence of side information. IEEE Trans. Automat. Contr. 52, 56–66 (2007)

    Article  MathSciNet  Google Scholar 

  20. Martins, N. C. & Dahleh, M. A. Feedback control in the presence of noisy channels: “bode-like” fundamental limitations of performance. IEEE Trans. Automat. Contr. 53, 1604–1615 (2008)

    Article  MathSciNet  Google Scholar 

  21. El-Samad, H., Kurata, H., Doyle, J. C., Gross, C. A. & Khammash, M. Surviving heat shock: control strategies for robustness and performance. Proc. Natl Acad. Sci. USA 102, 2736–2741 (2005)

    Article  ADS  CAS  Google Scholar 

  22. Yi, T. M., Huang, Y., Simon, M. I. & Doyle, J. Robust perfect adaptation in bacterial chemotaxis through integral feedback control. Proc. Natl Acad. Sci. USA 97, 4649–4653 (2000)

    Article  ADS  CAS  Google Scholar 

  23. Bialek, W. & Setayeshgar, S. Cooperativity, sensitivity, and noise in biochemical signaling. Phys. Rev. Lett. 100, 258101 (2008)

    Article  ADS  Google Scholar 

  24. Gregor, T., Tank, D. W., Wieschaus, E. F. & Bialek, W. Probing the limits to positional information. Cell 130, 153–164 (2007)

    Article  CAS  Google Scholar 

  25. Walczak, A. M., Mugler, A. & Wiggins, C. H. A stochastic spectral analysis of transcriptional regulatory cascades. Proc. Natl Acad. Sci. USA 106, 6529–6534 (2009)

    Article  ADS  CAS  Google Scholar 

  26. Bialek, W. & Setayeshgar, S. Physical limits to biochemical signaling. Proc. Natl Acad. Sci. USA 102, 10040–10045 (2005)

    Article  ADS  CAS  Google Scholar 

  27. Tomizawa, J. Control of ColE1 plasmid replication: binding of RNA I to RNA II and inhibition of primer formation. Cell 47, 89–97 (1986)

    Article  CAS  Google Scholar 

  28. Das, N. et al. Multiple homeostatic mechanisms in the control of P1 plasmid replication. Proc. Natl Acad. Sci. USA 102, 2856–2861 (2005)

    Article  ADS  CAS  Google Scholar 

  29. Shannon, C. E. A mathematical theory of communication. Bell Syst. Tech. J. 27, 379–423, 623–656 (1948)

    Article  MathSciNet  Google Scholar 

  30. Gorbunov, A. K. & Pinsker, M. S. Nonanticipatory and prognostic epsilon entropies and message generation rates. Probl. Inf. Transm. 9, 184–191 (1973)

    Google Scholar 

  31. Kabanov, Y. The capacity of a channel of the Poisson type. Theory Probab. Appl. 23, 143–147 (1978)

    Article  Google Scholar 

  32. Davis, M. H. A. Capacity and cut-off rate for Poisson type channels. IEEE Trans. Inf. Theory 26, 710–715 (1980)

    Article  Google Scholar 

Download references

Acknowledgements

This research was supported by the BBSRC under grant BB/C008073/1, by the National Science Foundation grants DMS-074876-0 and CAREER 0720056, and by grants GM081563-02 and GM068763-06 from the National Institutes of Health.

Author information

Authors and Affiliations

Authors

Contributions

I.L., G.V. and J.P. contributed equally, and all conceived the study, derived the equations and wrote the paper.

Corresponding authors

Correspondence to Glenn Vinnicombe or Johan Paulsson.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Supplementary information

Supplementary Information

This file contains Supplementary Information comprising: 1 Introduction; 2 Preliminaries; 3 The informationcapacity of molecular channels; 4 The bounds; 5 Serial and parallel cascades; 6 Tradeoffs; Supplementary Appendices A, B and C and additional references. (PDF 529 kb)

PowerPoint slides

Rights and permissions

Reprints and permissions

About this article

Cite this article

Lestas, I., Vinnicombe, G. & Paulsson, J. Fundamental limits on the suppression of molecular fluctuations. Nature 467, 174–178 (2010). https://doi.org/10.1038/nature09333

Download citation

  • Received:

  • Accepted:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nature09333

This article is cited by

Comments

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.

Search

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