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Systems Biology of Metabolic and Signaling Networks pp 19–35Cite as

Complex Systems Biology of Networks: The Riddle and the Challenge

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Part of the book series: Springer Series in Biophysics ((BIOPHYSICS,volume 16))

Abstract

There is no direct relationship between metabolite, mRNA, protein, and gene; the expression of a gene is not necessarily correlated with the abundance of the corresponding protein product, and the activity of a protein may depend on posttranslational modifications, e.g., phosphorylation, redox-modulation/modification, and acetylation. It is believed that the diverse nature and outcomes of networks composed of genes, transcripts, proteins, and metabolites remain an obstacle for tracing the flux from genes to proteins in order to be able to capture or explain developmental programs or the underlying mechanisms of a disease. A different approach is needed to address this problem, and accordingly an alternative view based on the dynamic integration of three different kinds of networks, mass–energy, information, and signaling, is proposed and developed in this chapter. From this perspective, the spatio-temporal expression of mass–energy transformation and information-carrying networks is modulated by signaling networks associated with fundamental cellular processes such as cell division, differentiation, and autophagy. The dynamic network of reaction fluxes (i.e., the fluxome) represents the ultimate integrative outcome of the whole process. This approach—which accounts for the basic biological fact that cells and organisms make themselves—can only be realized by networks connected by overall cyclic topologies. Thereby, the output of mass–energy/information networks, composed of proteins, transcriptional factors, metabolites, is at the same time input for signaling networks which output activates or represses those same networks that produced them.

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Acknowledgments

This work was performed with the financial support of R01-HL091923 from NIH.

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Authors and Affiliations

  1. Division of Cardiology, Johns Hopkins University, Baltimore, MD, 21205, USA

    Miguel A. Aon

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  1. Miguel A. Aon
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Correspondence to Miguel A. Aon .

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Editors and Affiliations

  1. School of Medicine, Johns Hopkins University, Baltimore, Maryland, USA

    Miguel A. Aon

  2. Laboratory of Fundamental and Applied Bi, Inserm U1055 and University Joseph Fourier, Grenoble, Grenoble cedex 9, France

    Valdur Saks

  3. Laboratory of Fundamental and Applied Bi, Inserm U1055 and University Joseph Fourier, Grenoble, Grenoble cedex 9, France

    Uwe Schlattner

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Aon, M.A. (2014). Complex Systems Biology of Networks: The Riddle and the Challenge. In: Aon, M., Saks, V., Schlattner, U. (eds) Systems Biology of Metabolic and Signaling Networks. Springer Series in Biophysics, vol 16. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38505-6_2

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