Biomechanics of Cells and Tissues pp 103-130 | Cite as
Modelling the Influence of Cell Signaling on the Dynamics of Gene Regulatory Networks
Abstract
Boolean models have proven to be effective in capturing some features of the dynamical behavior of the gene regulatory network of isolated cells. Cells are however constantly exposed to several signals that affect the regulation of their genes and are therefore not isolated. Moreover, cells in multi-cellular organisms and, to some extent, also in colonies of unicellular ones modify their gene expression profiles in a coordinated fashion. Many of these processes are controlled by cell–cell communication mechanisms. It appears therefore important to understand how the interplay among gene regulatory networks, by means of the signaling network, may alter their dynamical properties. In order to explore the issue, a model based on interconnected identical Boolean networks has been proposed, which has allowed to investigate the influence that cell-signaling may have on the expression patterns of individual cells, with particular regard on their variety and homeostasis. The main results described in this chapter show that both the diversity of emergent behaviors and the diffusion of perturbations may not depend linearly on the fraction of genes involved in the signaling network. On the contrary, when cells exchange a moderate quantity of signals with neighbors, the variety of their activation patterns is maximized, together with the number of genes that can be damaged as a consequence of a minor alteration of the system.
References
- 1.Aldana M, Coppersmith S, Kadanoff LP (2003) Boolean dynamics with random couplings. In: Marsden JE, Sreenivasan KR, Kaplan E (eds) Perspectives and problems in nonlinear science. Springer Applied Mathematical Sciences Series, Springer, New York, pp 23–90CrossRefGoogle Scholar
- 2.Berks M, Traynor D, Carrin I, Insall RH, Kay RK (1991) Diffusible signal molecules controlling cell differentiation and patterning in dictyostelium. Development 113(Supplement 1):131–139Google Scholar
- 3.Bull L, Alonso-Sanz R (2008) On coupling random boolean networks. In: Adamatzky A, Alonso-Sanz R, Lawniczak A, Juarez Martinez G, Morita K, Worsch T (eds) Automata-2008: theory and applications of cellular Automata. Luniver Press, Frome, pp 292–305.Google Scholar
- 4.Damiani C, Kauffman SA, Serra R, Villani M, Colacci A (2010) Information transfer among coupled random boolean networks. In: Bandini S, Umeo H, Manzoni S, Vizzari G (eds) Cellular automata, 9th international conference on cellular automata for research and industry, (ACRI 2010, Ascoli Piceno, Italy, September 21–24). Lecture Notes in Computer Science. vol 6350/2010. Springer, Berlin, pp 1–11.Google Scholar
- 5.Damiani C, Serra R, Villani M, Kauffman SA, Colacci A (2011) Cell-cell interaction and diversity of emergent behaviours. IET systems biology 5(2):137–144CrossRefGoogle Scholar
- 6.Damiani C (2011) Dynamics of interacting genetic networks. Ph.d thesis within the school of graduate studies “multiscale modelling, computational simulations and characterization for material and life sciences”, Modena and Reggio Emilia University, Reggio Emilia.Google Scholar
- 7.Derrida B, Pomeau Y (1986) Random networks of automata: a simple annealed approximation. Europhys Lett 1 1(2):45–49.Google Scholar
- 8.David G, Fu H, Gu X, Richard O, Steve R, Vladislav V, Kurth MJ, Downes CS, Dubitzky W (2006) Computational methodologies for modelling, analysis and simulation of signalling networks. Briefings Bioinform 7(4):339–353CrossRefGoogle Scholar
- 9.Glazier JA, Graner F (1993) Simulation of the differential adhesion driven rearrangement of biological cells. Phys Rev E 47(3):2128–2154CrossRefGoogle Scholar
- 10.Goodwin BC, Cohen MH (1969) A phase-shift model for the spatial and temporal organization of developing systems. J Theor Biol 25(1):49–107CrossRefGoogle Scholar
- 11.Goodwin BC, Kauffman SA (1990) Spatial harmonics and pattern specification in early drosophila development. Part i. bifurcation sequences and gene expression. J Theor Biol 144(3):303–319CrossRefGoogle Scholar
- 12.Hogeweg P (2000) Evolving mechanisms of morphogenesis: on the interplay between differential adhesion and cell differentiation. J Theor Biol 203(4):317–333CrossRefGoogle Scholar
- 13.Jackson ER, Johnson D, Nash WG (1986) Gene networks in development. J Theor Biol 119(4):379–396CrossRefGoogle Scholar
- 14.Janowski S, Kormeier B, Tpel T, Hippe K, HofestŁdt R, Willassen N, Rafael F, Sebastian R, Daniela B, Peik H, Ming C (2010) Modeling of cell-to-cell communication processes with petri nets using the example of quorum sensing. Silico Biol 10(1–2):27–48Google Scholar
- 15.Kaneko K, Yomo T (1997) Isologous diversification: a theory of cell differentiation. Bull Math Biol 59(1):139–196MATHCrossRefGoogle Scholar
- 16.Kauffman SA (1969) Metabolic stability and epigenesis in randomly constructed genetic nets. J Theor Biol 22(3):437–467CrossRefGoogle Scholar
- 17.Kauffman SA (1971) Gene regulation networks: a theory of their global structure and behaviour. Top Dev Biol 6:145–182CrossRefGoogle Scholar
- 18.Kauffman SA (1974) The large scale structure and dynamics of gene control circuits: an ensemble approach. J Theor Biol 44(1):167–190MathSciNetCrossRefGoogle Scholar
- 19.Kauffman SA (1993) The origins of order. Oxford University Press, New YorkGoogle Scholar
- 20.Kauffman SA (1995) At home in the universe. Oxford University Press, New YorkGoogle Scholar
- 21.Kauffman SA (2000) Investigations. Oxford University Press, New YorkGoogle Scholar
- 22.Kauffman SA (2004) A proposal for using the ensemble approach to understand genetic regulatory networks. J Theor Biol 230(4):581–590MathSciNetCrossRefGoogle Scholar
- 23.Kauffman SA, Shymko RM, Trabert K (1978) Control of sequential compartment formation in Drosophila. Science 199(4326):259–270CrossRefGoogle Scholar
- 24.Kauffman SA (1984) Emergent properties in random complex automata. Phys D Nonlinear Phenom 10(1–2):145–156MathSciNetCrossRefGoogle Scholar
- 25.Kauffman SA (1991) Emergent properties in random complex automata. Physica D Nonlinear Phenom 265(2):78–74MathSciNetGoogle Scholar
- 26.Kupiec JJ (1997) A darwinian theory for the origin of cellular differentiation. Mol Gen Genet 255(2):201–8CrossRefGoogle Scholar
- 27.Lane D (2006) Hierarchy, complexity, society. In: Courgeau D, Franck R, Pumain D (eds) Hierarchy in natural and social sciences, Methodos Series vol 3. Springer, Netherlands, pp 81–119CrossRefGoogle Scholar
- 28.Langton C (1990) Computation at the edge of chaos: phase transitions and emergent computation. Phys D Nonlinear Phenom 42(1–3):12–37MathSciNetCrossRefGoogle Scholar
- 29.Lodish H, Berk A, Kaiser CA, Krieger M, Scott MP, Bretscher A, Ploegh H, Matsudaira P (2008) Molecular Cell Biology (6th edn). W. H, Freeman, New York. ISBN 9781429203142Google Scholar
- 30.Meinhardt H (1978) Space-dependent cell determination under the control of a morphogen gradient. J Theor Biol 74(2):307–321CrossRefGoogle Scholar
- 31.Meinhardt H (1982) Models of biological pattern formation. Academic Press, LondonGoogle Scholar
- 32.von Neumann J (1966) Theory of self-reproducing automata. University of Illinois Press, USAGoogle Scholar
- 33.Wiesenfeld K, Bak P, Tang C (1988) Self-organized criticality. Phys Rev A 38(1):364–374MathSciNetMATHCrossRefGoogle Scholar
- 34.Packard NH (1988) Adaptation toward the edge of chaos. In: Kelso JAS, Mandell AJ, Shlesinger MF (eds) Dynamic patterns in complex systems. World Scientific, Singapore, pp 293–301Google Scholar
- 35.Ramo P, Kesseli J, Yli-Harja O (2006) Perturbation avalanches and criticality in gene regulatory networks. J Theor Biol 242(1):164–170MathSciNetCrossRefGoogle Scholar
- 36.Rohlf T, Bornholdt S (2009) Morphogenesis by coupled regulatory networks: reliable control of positional information and proportion regulation. J Theor Biol 261(2):176–193CrossRefGoogle Scholar
- 37.Salazar-Ciudad I, Garcia-Fernández J, Solé R (2000) Gene networks capable of pattern formation: from induction to reaction-diffusion. J Theor Biol 205(4):587–603CrossRefGoogle Scholar
- 38.Salazar-Ciudad I, Jernvall J, Newman SA (2003) Mechanisms of pattern formation in development and evolution. Development 130(10):2027–2037CrossRefGoogle Scholar
- 39.Sander K (1996) Pattern formation in insect embryogenesis: the evolution of concepts and mechanisms. Int J Insect Morphol Embryol 25(4):349–367MathSciNetCrossRefGoogle Scholar
- 40.Serra R, Villani M, Damiani C, Graudenzi A, Colacci A (2008) The diffusion of perturbations in a model of coupled random boolean networks. In: Umeo H, Morishiga S, Nishinari K, Komatsuzaki T, Banidini S (eds) Cellular Automata (proceedings of 8th international conference on cellular auotomata ACRI 2008, Yokohama, September 2008), ISBN 0302-9743, Lecture Notes in Computer Science vol 5191/2008. Springer, Berlin, pp 315-322.Google Scholar
- 41.Serra R, Villani M, Graudenzi A, Kauffman SA (2007) Why a simple model of genetic regulatory networks describes the distribution of avalanches in gene expression data. J Theor Biol 246(3):449–460MathSciNetCrossRefGoogle Scholar
- 42.Shmulevich I, Kauffman SA, Aldana M (2005) Eukaryotic cells are dynamically ordered or critical but not chaotic. PNAS 102(38):13439–13444CrossRefGoogle Scholar
- 43.Turing AM (1952) The chemical basis of morphogenesis. Philos Trans Roy Soc London Ser B 237(641):3772CrossRefGoogle Scholar
- 44.von Dassow G, Meir E, Munro EM, Odell GM (2000) The segment polarity network is a robust developmental module. Nature 406(6792):188–192. 07 2000/07/13/print.Google Scholar
- 45.Wolpert L (1989) Positional information revisited. Development 107(Supplement):3–12Google Scholar