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Constraint-Based Modeling of Metabolic Interactions in and Between Astrocytes and Neurons

  • Tunahan ÇakırEmail author
Chapter
Part of the Springer Series in Computational Neuroscience book series (NEUROSCI)

Abstract

Through its metabolic network, a cell distributes the available carbon flux into several pathways. The pathway activity information for a cell is crucial to deduce underlying molecular mechanisms and to monitor the effect of perturbations such as diseases. The constraint-based modeling approach to organism- and tissue-specific metabolic networks has therefore become a popular focus in the computational system’s biology field. The approach uses reaction stoichiometries and the reversibility information for the reactions as well as few literature-based flux measurements to calculate flux distributions through all covered pathways in a metabolic network. Therefore, the effect of phenomena such as hypoxia, hyperglycemia, and neurodegenerative diseases on brain metabolism can be computationally documented to enlighten molecular mechanisms and to design new hypotheses. This chapter covers the basics of constraint-based modeling via a toy metabolic network example and gives an overview of the application of the approach to couple neuronal and astrocytic metabolisms. It further utilizes a recently developed genome-scale metabolic network of the brain to calculate fluxes for the resting state and for hypoxia in and between astrocytes and neurons. Finally, the chapter shortly discusses the use of transcriptome data to obtain condition-specific flux distributions.

Keywords

Metabolic network Flux balance analysis Neuron–astrocyte coupling Brain metabolism 

Notes

Acknowledgements

This work was supported by TUBITAK, The Scientific and Technological Research Council of Turkey, through a career grant (Project Code: 110M464), by Gebze Technical University Research Project (Project Code: BAP 2011-A-27), and by The Turkish Academy of Sciences—Outstanding Young Scientists Award Program (TUBA-GEBIP).

Conflict of Interest

The author declares no conflict of interest.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Department of BioengineeringGebze Technical UniversityKocaeliTurkey

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