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Evolution of Resource and Energy Management in Biologically Realistic Gene Regulatory Network Models

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Evolutionary Systems Biology

Part of the book series: Advances in Experimental Medicine and Biology ((volume 751))

Abstract

We describe the use of computational models of evolution of artificial gene regulatory networks to understand the topologies of biological gene regulatory networks. We summarize results from three complementary approaches that explicitly represent biological processes of transcription, translation, metabolism and gene regulation: a fine-grained model that allows detailed molecular interactions, a coarse-grained model that allows rapid evolution of many generations, and a fixed-architecture model that allows for comparison of different hypotheses. In the first two cases, we are able to evolve networks towards the biological fitness objectives of survival and reproduction. A theme that emerges is that the control of cell energy and resources is a major driver of gene network topology and function. This is demonstrated in the fine-grained model with the emergence of biologically realistic mRNA and protein turnover rates that optimize energy usage and cell division time, and the evolution of basic repressor activities; in the fixed architecture model with a negative self-regulating gene evolving major efficiencies in mRNA usage; and in the coarse-grained model by the need for the inclusion of basal gene expression to obtain biologically plausible networks and the emergence of global regulators keeping all cellular systems under negative control. In summary, we demonstrate the value of biologically realistic computer evolution techniques, and the importance of energy and resource management in driving the topology and function of gene regulatory networks.

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Author information

Authors and Affiliations

  1. School of Biosciences, University of Nottingham, Leicestershire, LE12 5RD, UK

    Dov J. Stekel

  2. Warwick Systems Biology Centre, University of Warwick, Coventry, CV4 7AL, UK

    Dafyd J. Jenkins

Authors
  1. Dov J. Stekel
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  2. Dafyd J. Jenkins
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Correspondence to Dov J. Stekel .

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Editors and Affiliations

  1. University of Exeter, Prince of Wales Road, Exeter, EX4 4SB, Devon, United Kingdom

    Orkun S. Soyer

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© 2012 Springer Science+Business Media, LLC

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Stekel, D.J., Jenkins, D.J. (2012). Evolution of Resource and Energy Management in Biologically Realistic Gene Regulatory Network Models. In: Soyer, O. (eds) Evolutionary Systems Biology. Advances in Experimental Medicine and Biology, vol 751. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-3567-9_14

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