Abstract
Circadian rhythm, cell division and metabolic oscillations are rhythmic cellular behaviors that must be both robust but also to respond to changes in their environment. In this work, we study emergent behavior of coupled biochemical oscillators, modeled as repressilators. While more traditional approaches to oscillators synchronization often use phase oscillators, our approach uses switching systems that may be more appropriate for cellular networks dynamics governed by biochemical switches. We show that while one-directional coupling maintains stable oscillation of individual repressilators, there are well-characterized parameter regimes of mutually coupled repressilators, where oscillations stop. In other parameter regimes, joint oscillations continue. Our results may have implications for the understanding of condition-dependent coupling and un-coupling of regulatory networks.
Similar content being viewed by others
References
Albert R, Collins JJ, Glass L (2013) Introduction to focus issue: quantitative approaches to genetic networks. Chaos 23(2):025001
Almeida S, Chaves M, Delaunay F (2020) Control of synchronization ratios in clock/cell cycle coupling by growth factors and glucocorticoids. R Soc Open Sci 7:192054
Almeida S, Chaves M, Delaunay F (2020) Transcription-based circadian mechanism controls the duration of molecular clock states in response to signaling inputs. J Theor Biol 484:110015
Alon U (2007) Network motifs: theory and experimental approaches. Nat Rev Genet 8:450–461
Atay O, Doncic A, Skotheim JM (2016) Switch-like transitions can modularize complex biological networks. Cell Syst 3(2):121–132
Bieler J, Cannavo R, Gustafson K, Gobet C, Gatfield D, Naef F (2014) Robust synchronization of coupled circadian and cell cycle oscillators in single mammalian cells. Mol Syst Biol 10(7):739
Boccaletti S, Pisarchik AN, del Genio CI (2018) Synchronization: from coupled systems to complex networks. Cambridge University Press, Cambridge
Burckard O, Teboul M, Delaunay F, Chaves M (2022) Cycle dynamics and synchronization in a coupled network of peripheral circadian clocks. Interface Focus 20210087
Collins JJ, Stewart IN (1992) Symmetry-breaking bifurcation: a possible mechanism for 2:1 frequency-locking in animal locomotion. J Math Biol 30(8):827–838
Collins JJ, Stewart IN (1993) Coupled nonlinear oscillators and the symmetries of animal gaits. J Nonlinear Sci 3:349–392
Cummins B, Gedeon T, Harker S, Mischaikow K (2017) Database of dynamic signatures generated by regulatory networks (DSGRN). In: Feret J, Koeppl H (eds) Computational methods in systems biology, 2017, chapter 19. Springer, Berlin, pp 300–308
Cummins B, Gedeon T, Harker S, Mischaikow K (2018) DSGRN: examining the dynamics of families of logical models. Front Physiol 9
Cummins B, Gedeon T, Harker S, Mischaikow K (2018) Model rejection and parameter reduction via time series. SIAM J Appl Dyn Syst 17(2):1589–1616
Cummins B, Gedeon T, Harker S, Mischaikow K, Mok K (2016) Combinatorial representation of parameter space for switching systems. SIAM J Appl Dyn Syst 15(4):2176–2212
de Jong H, Gouze JL, Hernandez C, Page M, Sari T, Geiselmann J (2004) Qualitative simulation of genetic regulatory networks using piecewise-linear models. Bull Math Biol 66(2):301–40
Edwards R (2001) Chaos in neural and gene networks with hard switching. Differ Equ Dyn Syst 9:187–220
Epstein IR, Pojman JA (1998) An introduction to nonlinear chemical dynamics: oscillations, waves, patterns, and chaos. University Press, Oxford
Ermentrout B, Kopell N (1990) Oscillator death in systems of coupled neural oscillators. SIAM J Appl Math 50(1):125–146
Feillet C, van der Horst GT, Levi F, Ran DA, Delaunay F (2015) Coupling between the circadian clock and cell cycle oscillators: implication for healthy cells and malignant growth. Front Neurol 6(96)
Feillet Céline, Krusche Peter, Tamanini Filippo, Janssens Roel C, Downey Mike J, Martin Patrick, Teboul Michèle, Saito Shoko, Lévi Francis A, Bretschneider Till, van der Horst Gijsbertus T J, Delaunay Franck, Rand David A (2014) Phase locking and multiple oscillating attractors for the coupled mammalian clock and cell cycle. Proc Natl Acad Sci USA 111(27):9828–9833
Forger D, Peskin C (2003) A detailed predictive model of the mammalian circadian clock. Proc Natl Acad Sci USA 100(25):14806–148112003
Gedeon T (1998) Cyclic Feedback Systems, volume 637 of Memoirs of AMS. American Mathematical Soc, Providence
Gedeon T (2000) Multi-parameter exploration of dynamics of regulatory networks. Biosystems 190:104113
Gedeon T, Cummins B, Harker S, Mischaikow K (2018) Identifying robust hysteresis in networks. PLoS Comput Biol 14(4):e1006121
Glass L, Kauffman S (1972) Co-operative components, spatial localization and oscillatory cellular dynamics. J Theor Biol 34(2):219–37
Goldbetter A, Yan J (2021) Multi-synchonization and other patterns of multi-rhythmicity in oscillatory dynamical systems. Interface Focus 12:20210089
Harker S. dsgrn software
Hastings S, Tyson J, Webster D (1977) Existence of periodic solutions for negative feedback cellular control systems. J Differ Equ 25:39–64
Ironi L, Panzeri L, Plahte E, Simoncini V (2011) Dynamics of actively regulated gene networks. Physica D 240(8):779–794
Kuramoto Y (1984) Chemical oscillations, waves and turbulence. Springer, Berlin
Pikovsky A, Rosenblum MG, Kurths J (2001) Synchronization: a universal concept in nonlinear sciences. Cambridge University Press, Cambridge
Smith LM, Motta FC, Chopra G, Moch JK, Nerem RR, Cummins B, Roche KE, Kelliher CM, Leman AR, Harer J, Gedeon T, Waters NC, Haase SB (2020) An intrinsic oscillator drives the blood stage cycle of the malaria parasite. Science 368:754–759
Snoussi H, Thomas R (1993) Qualitative dynamics of piecewise-linear differential equations: a discrete mapping approach. Bull Math Biol 55(5):973–991
Sontag E (2002) Asymptotic amplitudes and Cauchy gains: a small-gain principle and an application to inhibitory biological feedback. Syst Control Lett 47:167–179
Stewart Ian, Golubitsky Martin, Pivato Marcus (2003) Symmetry groupoids and patterns of synchrony in coupled cell networks. SIAM J Appl Dyn Syst 2(4):609–646
Strogatz S (2012) Sync: how order emerges from chaos in the universe, nature and daily life. Hyperion, New York
Strogatz Steven H, Mirollo Renato E (1991) Stability of incoherence in a population of coupled oscillators. J Stat Phys 63(3):613–635
Tyson JJ, Othmer HG (1978) The dynamics of feedback control circuits in biochemical pathways. Prog Theor Biol 5:1–62
Winfree AT (1980) The geometry of biological time. Springer, New York
Yan J, Goldbeter A (2019) Robust synchronization of the cell cycle and the circadian clock through bidirectional coupling. J R Soc Interface 16:20190376
Acknowledgements
We acknowledge the Indigenous nations and peoples who are the traditional owners and caretakers of the land on which this work was undertaken at the Montana State University.
Funding
This research was partially supported by NSF Grant DMS-1839299 and NIH Grant 5R01GM126555-01.
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interest
The authors have no competing interests to declare that are relevant to the content of this article.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
This paper is dedicated to Eduardo Sontag on the occasion of his 70th birthday.
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Gedeon, T., Cummins, B. Oscillator death in coupled biochemical oscillators. Math. Control Signals Syst. 35, 781–801 (2023). https://doi.org/10.1007/s00498-023-00348-3
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00498-023-00348-3