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.

  • Letter
  • Published:

Enhancement of cellular memory by reducing stochastic transitions

Abstract

On induction of cell differentiation, distinct cell phenotypes are encoded by complex genetic networks1,2,3. These networks can prevent the reversion of established phenotypes even in the presence of significant fluctuations. Here we explore the key parameters that determine the stability of cellular memory by using the yeast galactose-signalling network as a model system. This network contains multiple nested feedback loops. Of the two positive feedback loops, only the loop mediated by the cytoplasmic signal transducer Gal3p is able to generate two stable expression states with a persistent memory of previous galactose consumption states. The parallel loop mediated by the galactose transporter Gal2p only increases the expression difference between the two states. A negative feedback through the inhibitor Gal80p reduces the strength of the core positive feedback. Despite this, a constitutive increase in the Gal80p concentration tunes the system from having destabilized memory to having persistent memory. A model reveals that fluctuations are trapped more efficiently at higher Gal80p concentrations. Indeed, the rate at which single cells randomly switch back and forth between expression states was reduced. These observations provide a quantitative understanding of the stability and reversibility of cellular differentiation states.

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: The galactose signalling pathway.
Figure 2: History-dependent experiments reveal the regulatory interaction necessary for persistent memory.
Figure 3: Stability analysis of the GAL network.
Figure 4: Stochastic switching dynamics between two stable expression states (strain MA0188).

Similar content being viewed by others

References

  1. Freeman, M. Feedback control of intercellular signalling in development. Nature 408, 313–319 (2000)

    Article  ADS  CAS  PubMed  Google Scholar 

  2. Davidson, E. H. et al. A genomic regulatory network for development. Science 295, 1669–1678 (2002)

    Article  ADS  CAS  PubMed  Google Scholar 

  3. Xie, H., Ye, M., Feng, R. & Graf, T. Stepwise reprogramming of B cells into macrophages. Cell 117, 663–676 (2004)

    Article  CAS  PubMed  Google Scholar 

  4. Xiong, W. & Ferrell, J. E. Jr. A positive-feedback-based bistable ‘memory module’ that governs a cell fate decision. Nature 426, 460–465 (2003)

    Article  ADS  CAS  PubMed  Google Scholar 

  5. Shykind, B. M. et al. Gene switching and the stability of odorant receptor gene choice. Cell 117, 801–815 (2004)

    Article  CAS  PubMed  Google Scholar 

  6. Markevich, N. I., Hoek, J. B. & Kholodenko, B. N. Signalling switches and bistability arising from multisite phosphorylation in protein kinase cascades. J. Cell Biol. 164, 353–359 (2004)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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

    Article  ADS  CAS  PubMed  Google Scholar 

  8. Becskei, A., Seraphin, B. & Serrano, L. Positive feedback in eukaryotic gene networks: cell differentiation by graded to binary response conversion. EMBO J. 20, 2528–2535 (2001)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Atkinson, M. R., Savageau, M. A., Myers, J. T. & Ninfa, A. J. Development of genetic circuitry exhibiting toggle switch or oscillatory behavior in Escherichia coli. Cell 113, 597–607 (2003)

    Article  CAS  PubMed  Google Scholar 

  10. Isaacs, F. J., Hasty, J., Cantor, C. R. & Collins, J. J. Prediction and measurement of an autoregulatory genetic module. Proc. Natl Acad. Sci. USA 100, 7714–7719 (2003)

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  11. Angeli, D., Ferrell, J. E. Jr. & Sontag, E. D. Detection of multistability, bifurcations, and hysteresis in a large class of biological positive-feedback systems. Proc. Natl Acad. Sci. USA 101, 1822–1827 (2004)

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  12. Lai, K., Robertson, M. J. & Schaffer, D. V. The sonic hedgehog signaling system as a bistable genetic switch. Biophys. J. 86, 2748–2757 (2004)

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  13. Biggar, S. R. & Crabtree, G. R. Cell signaling can direct either binary or graded transcriptional responses. EMBO J. 20, 3167–3176 (2001)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Ideker, T. et al. Integrated genomic and proteomic analyses of a systematically perturbed metabolic network. Science 292, 929–934 (2001)

    Article  ADS  CAS  PubMed  Google Scholar 

  15. Suzuki-Fujimoto, T. et al. Analysis of the galactose signal transduction pathway in Saccharomyces cerevisiae: interaction between Gal3p and Gal80p. Mol. Cell. Biol. 16, 2504–2508 (1996)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Timson, D. J., Ross, H. C. & Reece, R. J. Gal3p and Gal1p interact with the transcriptional repressor Gal80p to form a complex of 1:1 stoichiometry. Biochem. J. 363, 515–520 (2002)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Peng, G. & Hopper, J. E. Gene activation by interaction of an inhibitor with a cytoplasmic signaling protein. Proc. Natl Acad. Sci. USA 99, 8548–8553 (2002)

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  18. Mizutani, A. & Tanaka, M. Regions of GAL4 critical for binding to a promoter in vivo revealed by a visual DNA-binding analysis. EMBO J. 22, 2178–2187 (2003)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Johnston, M., Flick, J. S. & Pexton, T. Multiple mechanisms provide rapid and stringent glucose repression of GAL gene expression in Saccharomyces cerevisiae. Mol. Cell. Biol. 14, 3834–3841 (1994)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Wieczorke, R. et al. Concurrent knock-out of at least 20 transporter genes is required to block uptake of hexoses in Saccharomyces cerevisiae. FEBS Lett. 464, 123–128 (1999)

    Article  CAS  PubMed  Google Scholar 

  21. Ozbudak, E. M., Thattai, M., Lim, H. N., Shraiman, B. I. & van Oudenaarden, A. Multistability in the lactose utilization network of Escherichia coli. Nature 427, 737–740 (2004)

    Article  ADS  CAS  PubMed  Google Scholar 

  22. Bhat, P. J. & Hopper, J. E. The mechanism of inducer formation in gal3 mutants of the yeast galactose system is independent of normal galactose metabolism and mitochondrial respiratory function. Genetics 128, 233–239 (1991)

    CAS  PubMed  PubMed Central  Google Scholar 

  23. Rohde, J. R., Trinh, J. & Sadowski, I. Multiple signals regulate GAL transciption in yeast. Mol. Cell. Biol. 20, 3880–3886 (2000)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Blake, W. J., Kærn, M., Cantor, C. R. & Collins, J. J. Noise in eukaryotic gene expression. Nature 422, 633–637 (2003)

    Article  ADS  CAS  PubMed  Google Scholar 

  25. Raser, J. M. & O'Shea, E. K. Control of stochasticity in eukaryotic gene expression. Science 304, 1811–1814 (2004)

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  26. Hasty, J., Pradines, J., Dolnik, M. & Collins, J. J. Noise-based switches and amplifiers for gene expression. Proc. Natl Acad. Sci. USA 97, 2075–2080 (2000)

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  27. Bialek, W. Stability and noise in biochemical switches. Adv. Neural Info. Process. 13, 103–109 (2001)

    Google Scholar 

  28. Kepler, T. B. & Elston, T. C. Stochasticity in transcriptional regulation: origins, consequences, and mathematical representations. Biophys. J. 81, 3116–3136 (2001)

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  29. Kramers, H. A. Brownian motion in a field of force and the diffusion model of chemical reactions. Physica 7, 284–304 (1940)

    Article  ADS  MathSciNet  CAS  Google Scholar 

  30. Sillje, H. H. et al. Effects of different carbon fluxes on G1 phase duration, cyclin expression, and reserve carbohydrate metabolism in Saccharomyces cerevisiae. J. Bacteriol. 179, 6560–6565 (1997)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

We thank M. Thattai for stimulating discussions and helpful suggestions on measuring the escape rates; J. Pedraza, M. Kardar, O. Ozcan and S. Cabi for useful discussions; B. Kaufmann for help with image analysis; and B. Pando for comments on the manuscript. M.A. acknowledges support by an MIT Presidential Fellowship endowed by Praecis Pharmaceuticals, Inc. A.B. is a Long Term Fellow of the Human Frontiers Science Program. This work was supported by a NSF-CAREER and a NIH grant.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Alexander van Oudenaarden.

Ethics declarations

Competing interests

The authors declare that they have no competing financial interests.

Supplementary information

Supplementary Notes

This file contains information on the following: modelling the galactose signalling pathway; determining experimental escape rates; and the doxycycline inducible PTET system. It also contains additional references, Supplementary Figures S1-S7, Supplementary Table 1 (yeast strains used in this study) and Supplementary Table 2 (galactose depletion experiments). (PDF 889 kb)

Rights and permissions

Reprints and permissions

About this article

Cite this article

Acar, M., Becskei, A. & van Oudenaarden, A. Enhancement of cellular memory by reducing stochastic transitions. Nature 435, 228–232 (2005). https://doi.org/10.1038/nature03524

Download citation

  • Received:

  • Accepted:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nature03524

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