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Fluctuation-Driven Adaptation and Symbiosis in Cellular Dynamics

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Bio-Inspired Models of Network, Information, and Computing Systems (BIONETICS 2010)

Abstract

Biological systems can generally adapt environmental chan- ges and to create symbiotic relationship with other species, by changing their intra-cellular states flexibly. However, the mechanisms for such flexible adaptation and creation of symbiotic relationship remain unclear. In this study, by using simple computer models of cells, we show that for cells whose gene expression fluctuate stochastically, the adaptive cellular state is inevitably selected by noise, even without sophisticated mechanisms. Furthermore, by the fluctuation-induced adaptation mechanism, we show that symbiotic relationships naturally appear in systems of interacting cells. This mechanism can provide clues to understand flexible adaptation and creation of symbiotic relationship. Applications of this mechanism for designing artificial systems are also discussed.

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References

  1. Jacob, F., Monod, J.: Genetic regulatory mechanisms in the synthesis of proteins. J. Mol. Biol. 3, 318–356 (1961)

    Article  Google Scholar 

  2. Kashiwagi, A., Urabe, I., Kaneko, K., Yomo, T.: Adaptive response of a gene network to environmental changes by fitness-induced attractor selection. PLoS One 1 e49 (2006)

    Google Scholar 

  3. Furusawa, C., Kaneko, K.: A Generic Mechanism for Adaptive Growth Rate Regulation. PLoS Comp. Biol. 4(1), e3 (2008)

    Google Scholar 

  4. Elowitz, M.B., Levine, A.J., Siggia, E.D., Swain, P.S.: A Generic Mechanism for Adaptive Growth Rate Regulation. Science 297, 1183–1186 (2002)

    Article  Google Scholar 

  5. Kaern, M., Elston, T.C., Blake, W.J., Collins, J.J.: Stochasticity in gene expression: from theories to phenotypes. Nature Rev. Genet. 8, 451–464

    Google Scholar 

  6. Pedraza, J.M., Van Oudenaarden, A.: Nosise propagation in gene networks. Science 307, 1965–1969

    Google Scholar 

  7. Marr, A.G.: Growth rate of Escherichia coli. Microbio. Rev. 55(2), 316–333

    Google Scholar 

  8. Currie, C.R.: A community of ants, fungi, and bacteria: a multilateral approach to studying symbiosis. Annu. Rev. Microbiol. 55, 357–380 (2001)

    Article  Google Scholar 

  9. Minami, Y., Koizumi, Y., Arakawa, S., Murata, M.: Adaptability of Virtual Network Topology Control based on Attractor Selection. In: Proceedings of 2009 International Symposium on Nonlinear Theory and its Applications, NOLTA 2009 (2009)

    Google Scholar 

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© 2012 ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering

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Furusawa, C., Ijichi, K., Shimizu, H. (2012). Fluctuation-Driven Adaptation and Symbiosis in Cellular Dynamics. In: Suzuki, J., Nakano, T. (eds) Bio-Inspired Models of Network, Information, and Computing Systems. BIONETICS 2010. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 87. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32615-8_25

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  • DOI: https://doi.org/10.1007/978-3-642-32615-8_25

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-32614-1

  • Online ISBN: 978-3-642-32615-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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