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    Multi-timescale Modeling of Activity-Dependent Metabolic Coupling in the Neuron-Glia-Vasculature Ensemble

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    journal.pcbi.1004036.pdf
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    Type
    Article
    Authors
    Jolivet, Renaud
    Coggan, Jay S.
    Allaman, Igor
    Magistretti, Pierre J. cc
    KAUST Department
    Biological and Environmental Sciences and Engineering (BESE) Division
    Bioscience Program
    Date
    2015-02-26
    Permanent link to this record
    http://hdl.handle.net/10754/346681
    
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    Abstract
    Glucose is the main energy substrate in the adult brain under normal conditions. Accumulating evidence, however, indicates that lactate produced in astrocytes (a type of glial cell) can also fuel neuronal activity. The quantitative aspects of this so-called astrocyte-neuron lactate shuttle (ANLS) are still debated. To address this question, we developed a detailed biophysical model of the brain’s metabolic interactions. Our model integrates three modeling approaches, the Buxton-Wang model of vascular dynamics, the Hodgkin-Huxley formulation of neuronal membrane excitability and a biophysical model of metabolic pathways. This approach provides a template for large-scale simulations of the neuron-glia-vasculature (NGV) ensemble, and for the first time integrates the respective timescales at which energy metabolism and neuronal excitability occur. The model is constrained by relative neuronal and astrocytic oxygen and glucose utilization, by the concentration of metabolites at rest and by the temporal dynamics of NADH upon activation. These constraints produced four observations. First, a transfer of lactate from astrocytes to neurons emerged in response to activity. Second, constrained by activity-dependent NADH transients, neuronal oxidative metabolism increased first upon activation with a subsequent delayed astrocytic glycolysis increase. Third, the model correctly predicted the dynamics of extracellular lactate and oxygen as observed in vivo in rats. Fourth, the model correctly predicted the temporal dynamics of tissue lactate, of tissue glucose and oxygen consumption, and of the BOLD signal as reported in human studies. These findings not only support the ANLS hypothesis but also provide a quantitative mathematical description of the metabolic activation in neurons and glial cells, as well as of the macroscopic measurements obtained during brain imaging.
    Citation
    Multi-timescale Modeling of Activity-Dependent Metabolic Coupling in the Neuron-Glia-Vasculature Ensemble 2015, 11 (2):e1004036 PLOS Computational Biology
    Publisher
    Public Library of Science (PLoS)
    Journal
    PLOS Computational Biology
    DOI
    10.1371/journal.pcbi.1004036
    PubMed ID
    25719367
    PubMed Central ID
    PMC4342167
    Additional Links
    http://dx.plos.org/10.1371/journal.pcbi.1004036
    ae974a485f413a2113503eed53cd6c53
    10.1371/journal.pcbi.1004036
    Scopus Count
    Collections
    Articles; Biological and Environmental Science and Engineering (BESE) Division; Bioscience Program

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