Synchronization of Circadian Rhythms at Scale of Gene, Cell and Whole Organism



Three characteristic scales of a biological system are distinguished in the chapter: microscopic (gene’s size), mesoscopic (cell’s size) and macroscopic (organism’s size). For each case the approach to modeling of the circadian rhythms is discussed on the base of a time-delay model. The stochastic description has been used at the gene’s scale. The deterministic description within the spatially extended model has been suggested on the mesoscopic scale. Macroscopic effects have been analyzed within the discrete model describing the collective behaviour of large amount of cells. The effect of collective rhythms synchronization for each case has been studied. The problem of cross-linking of the results obtained at different scales is discussed.


Synchronization Circadian rhythms Time-delay Intrinsic noise Individual based models Reaction-diffusion systems 


  1. 1.
    Pittendrigh, C.S.: Temporal organization: reflections of a Darwinian clock-watcher. Annu. Rev. Physiol. 55, 16–54 (1993)CrossRefGoogle Scholar
  2. 2.
    Stepanova, S.I.: Biorhythmological aspects of adaptation. Nauka, Moscow (1986)Google Scholar
  3. 3.
    Lakin-Thomas, P.L., Brody, S.: Circadian rhythms in microorganisms: new complexities. Annu. Rev. Microbiol. 58, 489–519 (2004)CrossRefGoogle Scholar
  4. 4.
    Pikovsky, A., Rosenblum, M., Kurths, J.: Synchronization—a universal concept in nonlinear sciences. Cambridge University Press, Cambridge (2001)CrossRefMATHGoogle Scholar
  5. 5.
    Hasty, J., Collins, J.J.: Translating the noise. Nat. Genet. 31, 13–14 (2002)CrossRefGoogle Scholar
  6. 6.
    Bratsun, D.A.: Effect of subcritical excitation of oscillations in stochastic systems with time delay. Part I. Regulation of gene expression. Comput. Res. Model. 3, 421–438 (2011)Google Scholar
  7. 7.
    Ghaemmaghami, S., Won-Ki, H., Bower, K., Howson, R.W., Belle, A., Dephoure, N., O’Shea, E.K., Weissman, J.S.: Global analysis of protein expression in yeast. Nature 425, 737–741 (2003)CrossRefGoogle Scholar
  8. 8.
    Morozov, K.I., Pismen, L.M.: Cytoskeleton fluidization versus resolidification: prestress effect. Phys. Rev. E. 83, 051920–051928 (2011)CrossRefGoogle Scholar
  9. 9.
    Bratsun, D., Zakharov, A.: Modeling spatio-temporal dynamics of circadian rhythms in Neurospora crassa. Comput. Res. Model. 3, 191–213 (2011)Google Scholar
  10. 10.
    Bratsun, D.A., Zakharov, A.P.: Deterministic modeling spatio-temporal dynamics of delay-induced circadian oscillations in Neurospora crassa. In: Interdisciplinary Symposium on Complex Systems, Czech Technical University, Prague, 10–13 Sept 2013Google Scholar
  11. 11.
    Smolen, P., Baxter, D.A., Byrne, J.H.: Modeling circadian oscillations with interlocking positive and negative feedback loops. J. Neurosci. 21, 6644–6656 (2001)Google Scholar
  12. 12.
    Bratsun, D., Volfson, D., Hasty, J., Tsimring, L.S.: Delay-induced stochastic oscillations in gene regulation. Proc. Natl. Acad. Sci. U.S.A. 102, 14593–14598 (2005)CrossRefGoogle Scholar
  13. 13.
    Gillespie, D.T.: Exact stochastic simulation of coupled chemical reactions. J. Phys. Chem. 81, 2340–2361 (1977)CrossRefGoogle Scholar
  14. 14.
    Bratsun, D.A., Zakharov, A.P.: Adaptive numerical simulations of reaction-diffusion systems with history and time-delayed feedback. In: Interdisciplinary Symposium on Complex Systems, Czech Technical University, Prague, 10–13 Sept 2013Google Scholar
  15. 15.
    Salm, M., Pismen, L.M.: Chemical and mechanical signaling in epithelial spreading. Phys. Biol. 9, 026009–026023 (2012)CrossRefGoogle Scholar
  16. 16.
    Koseska, A., Ullner, E., Volkov, E., Kurths, J., Garcia-Ojalvo, J.: Cooperative differentiation through clustering in multicellular populations. J. Theor. Biol. 263, 189–202 (2010)CrossRefMathSciNetGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  1. 1.Theoretical Physics DepartmentPerm State Pedagogical UniversityPermRussia

Personalised recommendations