Skip to main content
Log in

Hybrid Modeling of Noise Reduction by a Negatively Autoregulated System

  • Original Article
  • Published:
Bulletin of Mathematical Biology Aims and scope Submit manuscript

Abstract

We analyze the reduction of intrinsic noise caused by transition of a promoter between its active and inactive state in a negatively regulated genetic network, i.e., transcription of the gene is inhibited by its own gene product. To measure the noise attenuation, we compare its behavior to an inducible gene for which activation and deactivation of the gene take place at constant rates.

As a model, we choose a hybrid approach in which some of the reaction channels are modeled as discrete events, and other reactions are modeled as continuous processes. Such a model is appropriate for investigations of noise caused by low reactant numbers. By focusing on intrinsic noise originating from the switching behavior of the regulatory system of a particular gene, we model only the transition between two different promoter states as a discrete event.

We show that the stationary distributions of the unregulated and the autoregulated system are given as a solution of two coupled ordinary differential equations. Also, beside the distribution densities, the first two central moments are derived in closed analytical forms. We give conditions on the parameters when one or the other system shows lower fluctuations.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  • Becskei, A., Serrano, L., 2000. Engineering stability in gene networks by autoregulation. Nature 405, 590–93.

    Article  Google Scholar 

  • Becskei, A., Séraphin, B., Serrano, L., 2001. Positive feedback in eukaryotic gene networks: cell differentiation by graded to binary response conversion. EMBO J. 20, 2528–5.

    Article  Google Scholar 

  • Belle, A., Tanay, A., Bitincka, L., Shamir, R., O’Shea, E.K., 2006. Quantification of protein half-lives in the budding yeast proteome. Proc. Natl. Acad. Sci. USA 103, 13004–3009.

    Article  Google Scholar 

  • Davis, M.H.A., 1984. Piecewise-deterministic Markov processes: A general class of non-diffusion stochastic models. J. R. Stat. Soc. B 46, 353–88.

    MATH  Google Scholar 

  • Elowitz, M.B., Levine, A.J., Siggia, E.D., Swain, P.S., 2002. Stochastic gene expression in a single cell. Science 297, 1183–186.

    Article  Google Scholar 

  • Godstein, S., 1951. On diffusion by discontinuous movements and on the telegraph equation. Q. J. Mech. Appl. Math. 4, 129–56.

    Article  Google Scholar 

  • Hadeler, K.P., 1998. Reaction transport equations in biological modeling. Math. Comput. Model. 31, 75–1.

    Article  Google Scholar 

  • Hardin, P.E., Hall, J.C., Rosbash, M., 1990. Feedback of the Drosophila period gene product on circadian cycling of its messenger RNA levels. Nature 343, 536–40.

    Article  Google Scholar 

  • Hirata, H., Yoshiura, S., Ohtsuka, T., Bessho, Y., Harada, T., Yoshikawa, K., Kageyama, R., 2002. Oscillatory expression of the bHLH factor Hes1 regulated by a negative feedback loop. Science 298, 840–43.

    Article  Google Scholar 

  • Ferrell, J.E. Jr., Machleder, E.M., 1998. The biochemical basis of an all-or-none cell fate switch in xenopus oocytes. Science 280, 895–98.

    Article  Google Scholar 

  • Kac, M., 1974. A stochastic model related to the telegrapher’s equation. Rocky Mt. J. Math. 4, 497–09. Reprinted.

    Article  MATH  Google Scholar 

  • Kepler, T.B., Elstondagger, T.C., 2001. Stochasticity in transcriptional regulation: Origins, consequences, and mathematical representations. Biophys. J. 81, 3116–136.

    Article  Google Scholar 

  • Kwon, H., Park, S., Lee, S., Lee, D.-K., Yang, C.-H., 2001. Determination of binding constant of transcription factor AP-1 and DNA. Eur. J. Biochem. 268, 565–72.

    Article  Google Scholar 

  • McAdams, H.H., Arkin, A., 1997. Stochastic mechanisms in gene expression. Proc. Natl. Acad. Sci. USA 94, 814–19.

    Article  Google Scholar 

  • Müller, J., Kuttler, C., Hense, B.A., Zeiser, S., Liebscher, V., 2008. Transcription, intercellular variability and correlated random walk. Math. Biosci. 216, 30–9.

    Article  MATH  MathSciNet  Google Scholar 

  • Peccoud, J., Ycart, B., 1995. Markovian modelling of gene products synthesis. Theor. Popul. Biol. 48, 222–34.

    Article  MATH  Google Scholar 

  • Raj, A., Peskin, C.S., Tranchina, D., Vargas, D.Y., Tyagi, S., 2006. Stochastic mRNA synthesis in mammalian cells. PLoS Biol. 4, 1707–719.

    Article  Google Scholar 

  • Savageau, M.A., 1974. Comparison of classical and autogenous systems of regulation in inducible operons. Nature 252, 546–49.

    Article  Google Scholar 

  • Schulman, D.B., Setzera, D.R., 2002. Identification and characterization of transcription factor IIIA from Schizosaccharomyces pombe. Nucleic Acids Res. 30, 2772–781.

    Article  Google Scholar 

  • Slater, L.J., 1966. Generalized Hypergeometric Functions. Cambridge University Press, Cambridge.

    MATH  Google Scholar 

  • Smits, W.K., Eschevins, C.C., Susanna, K.A., Bron, S., Kuipers, O.P., Hamoen, L.W., 2005. Stripping Bacillus: ComK auto-stimulation is responsible for the bistable response in competence development. Mol. Microbiol. 56, 604–4.

    Article  Google Scholar 

  • Sørensen, M.A., Pedersen, S., 1991. Absolute in vivo translation rates of individual codons in Escherichia coli. The two glutamic acid codons GAA and GAG are translated with a threefold difference in rate. J. Mol. Biol. 222, 265–80.

    Article  Google Scholar 

  • Tyson, J.J., Othmer, H.G., 1978. The dynamics of feedback control circuits in biochemical pathways. Prog. Theor. Biol. 5, 1–2.

    Google Scholar 

  • van Kampen, N.G., 1992. Stochastic Processes in Physics and Chemistry. North-Holland–Elsevier, Amsterdam.

    Google Scholar 

  • Wolf, D.M., Eeckman, F.H., 1998. On the relationship between genomic regulatory element organization and gene regulatory dynamics. J. Theor. Biol. 195, 167–86.

    Article  Google Scholar 

  • Zeiser, S., Franz, U., Wittich, O., Liebscher, V., 2008. Simulation of genetic networks modelled by piecewise deterministic Markov processes. IET Syst. Biol. 2, 113–35.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Stefan Zeiser.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Zeiser, S., Franz, U., Müller, J. et al. Hybrid Modeling of Noise Reduction by a Negatively Autoregulated System. Bull. Math. Biol. 71, 1006–1024 (2009). https://doi.org/10.1007/s11538-008-9391-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11538-008-9391-5

Keywords

Navigation