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

Handle URI:
http://hdl.handle.net/10754/346681
Title:
Multi-timescale Modeling of Activity-Dependent Metabolic Coupling in the Neuron-Glia-Vasculature Ensemble
Authors:
Jolivet, Renaud; Coggan, Jay S.; Allaman, Igor; Magistretti, Pierre J. ( 0000-0002-6678-320X )
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.
KAUST Department:
Biological and Environmental Sciences and Engineering (BESE) Division
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
Issue Date:
26-Feb-2015
DOI:
10.1371/journal.pcbi.1004036
PubMed ID:
25719367
PubMed Central ID:
PMC4342167
Type:
Article
ISSN:
1553-7358
Additional Links:
http://dx.plos.org/10.1371/journal.pcbi.1004036
Appears in Collections:
Articles; Biological and Environmental Sciences and Engineering (BESE) Division

Full metadata record

DC FieldValue Language
dc.contributor.authorJolivet, Renauden
dc.contributor.authorCoggan, Jay S.en
dc.contributor.authorAllaman, Igoren
dc.contributor.authorMagistretti, Pierre J.en
dc.date.accessioned2015-03-16T05:24:19Zen
dc.date.available2015-03-16T05:24:19Zen
dc.date.issued2015-02-26en
dc.identifier.citationMulti-timescale Modeling of Activity-Dependent Metabolic Coupling in the Neuron-Glia-Vasculature Ensemble 2015, 11 (2):e1004036 PLOS Computational Biologyen
dc.identifier.issn1553-7358en
dc.identifier.pmid25719367en
dc.identifier.doi10.1371/journal.pcbi.1004036en
dc.identifier.urihttp://hdl.handle.net/10754/346681en
dc.description.abstractGlucose 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.en
dc.publisherPublic Library of Science (PLoS)en
dc.relation.urlhttp://dx.plos.org/10.1371/journal.pcbi.1004036en
dc.rightsThis is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.en
dc.titleMulti-timescale Modeling of Activity-Dependent Metabolic Coupling in the Neuron-Glia-Vasculature Ensembleen
dc.typeArticleen
dc.contributor.departmentBiological and Environmental Sciences and Engineering (BESE) Divisionen
dc.identifier.journalPLOS Computational Biologyen
dc.identifier.pmcidPMC4342167en
dc.eprint.versionPublisher's Version/PDFen
dc.contributor.institutionDepartment of Neuroscience, Physiology & Pharmacology, University College Londonen
dc.contributor.institutionBrain Mind Institute, École Polytechnique Fédérale de Lausanne (EPFL)en
dc.contributor.institutionNeuroLinx Research Institute, La Jollaen
dc.contributor.affiliationKing Abdullah University of Science and Technology (KAUST)en
kaust.authorMagistretti, Pierre J.en
All Items in KAUST are protected by copyright, with all rights reserved, unless otherwise indicated.