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      Norepinephrine stimulates glycogenolysis in astrocytes to fuel neurons with lactate

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          Abstract

          The mechanism of rapid energy supply to the brain, especially to accommodate the heightened metabolic activity of excited states, is not well-understood. We explored the role of glycogen as a fuel source for neuromodulation using the noradrenergic stimulation of glia in a computational model of the neural-glial-vasculature ensemble (NGV). The detection of norepinephrine (NE) by the astrocyte and the coupled cAMP signal are rapid and largely insensitive to the distance of the locus coeruleus projection release sites from the glia, implying a diminished impact for volume transmission in high affinity receptor transduction systems. Glucosyl-conjugated units liberated from glial glycogen by NE-elicited cAMP second messenger transduction winds sequentially through the glycolytic cascade, generating robust increases in NADH and ATP before pyruvate is finally transformed into lactate. This astrocytic lactate is rapidly exported by monocarboxylate transporters to the associated neuron, demonstrating that the astrocyte-to-neuron lactate shuttle activated by glycogenolysis is a likely fuel source for neuromodulation and enhanced neural activity. Altogether, the energy supply for both astrocytes and neurons can be supplied rapidly by glycogenolysis upon neuromodulatory stimulus.

          Author summary

          Although efficient compared to computers, the human brain utilizes energy at 10-fold the rate of other organs by mass. How the brain is supplied with sufficient on-demand energy to support its activity in the absence of neuronal storage capacity remains unknown. Neurons are not capable of meeting their own energy requirements, instead energy supply in the brain is managed by an oligocellular cartel composed of neurons, glia and the local vasculature (NGV), wherein glia can provide the ergogenic metabolite lactate to the neuron in a process called the astrocyte-to-neuron shuttle (ANLS). The only means of energy storage in the brain is glycogen, a polymerized form of glucose that is localized largely to astrocytes, but its exact role and conditions of use are not clear. In this computational model we show that neuromodulatory stimulation by norepinephrine induces astrocytes to recover glucosyl subunits from glycogen for use in a glycolytic process that favors the production of lactate. The ATP and NADH produced support metabolism in the astrocyte while the lactate is exported to feed the neuron. Thus, rapid energy demands by both neurons and glia in a stimulated brain can be met by glycogen mobilization.

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          Brain energy metabolism: focus on astrocyte-neuron metabolic cooperation.

          The energy requirements of the brain are very high, and tight regulatory mechanisms operate to ensure adequate spatial and temporal delivery of energy substrates in register with neuronal activity. Astrocytes-a type of glial cell-have emerged as active players in brain energy delivery, production, utilization, and storage. Our understanding of neuroenergetics is rapidly evolving from a "neurocentric" view to a more integrated picture involving an intense cooperativity between astrocytes and neurons. This review focuses on the cellular aspects of brain energy metabolism, with a particular emphasis on the metabolic interactions between neurons and astrocytes. Copyright © 2011 Elsevier Inc. All rights reserved.
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            Glutamate uptake into astrocytes stimulates aerobic glycolysis: a mechanism coupling neuronal activity to glucose utilization.

            Glutamate, released at a majority of excitatory synapses in the central nervous system, depolarizes neurons by acting at specific receptors. Its action is terminated by removal from the synaptic cleft mostly via Na(+)-dependent uptake systems located on both neurons and astrocytes. Here we report that glutamate, in addition to its receptor-mediated actions on neuronal excitability, stimulates glycolysis--i.e., glucose utilization and lactate production--in astrocytes. This metabolic action is mediated by activation of a Na(+)-dependent uptake system and not by interaction with receptors. The mechanism involves the Na+/K(+)-ATPase, which is activated by an increase in the intracellular concentration of Na+ cotransported with glutamate by the electrogenic uptake system. Thus, when glutamate is released from active synapses and taken up by astrocytes, the newly identified signaling pathway described here would provide a simple and direct mechanism to tightly couple neuronal activity to glucose utilization. In addition, glutamate-stimulated glycolysis is consistent with data obtained from functional brain imaging studies indicating local nonoxidative glucose utilization during physiological activation.
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              In Vivo Evidence for a Lactate Gradient from Astrocytes to Neurons.

              Investigating lactate dynamics in brain tissue is challenging, partly because in vivo data at cellular resolution are not available. We monitored lactate in cortical astrocytes and neurons of mice using the genetically encoded FRET sensor Laconic in combination with two-photon microscopy. An intravenous lactate injection rapidly increased the Laconic signal in both astrocytes and neurons, demonstrating high lactate permeability across tissue. The signal increase was significantly smaller in astrocytes, pointing to higher basal lactate levels in these cells, confirmed by a one-point calibration protocol. Trans-acceleration of the monocarboxylate transporter with pyruvate was able to reduce intracellular lactate in astrocytes but not in neurons. Collectively, these data provide in vivo evidence for a lactate gradient from astrocytes to neurons. This gradient is a prerequisite for a carrier-mediated lactate flux from astrocytes to neurons and thus supports the astrocyte-neuron lactate shuttle model, in which astrocyte-derived lactate acts as an energy substrate for neurons.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Formal analysisRole: InvestigationRole: MethodologyRole: Project administrationRole: SoftwareRole: Writing – original draftRole: Writing – review & editing
                Role: Formal analysisRole: SoftwareRole: SupervisionRole: Writing – review & editing
                Role: ConceptualizationRole: Formal analysisRole: InvestigationRole: Writing – review & editing
                Role: Writing – review & editing
                Role: ConceptualizationRole: Funding acquisitionRole: ResourcesRole: SupervisionRole: Writing – review & editing
                Role: ConceptualizationRole: Funding acquisitionRole: Project administrationRole: ResourcesRole: SupervisionRole: Writing – review & editing
                Role: ConceptualizationRole: Funding acquisitionRole: MethodologyRole: Project administrationRole: ResourcesRole: SupervisionRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS Comput Biol
                PLoS Comput. Biol
                plos
                ploscomp
                PLoS Computational Biology
                Public Library of Science (San Francisco, CA USA )
                1553-734X
                1553-7358
                30 August 2018
                August 2018
                : 14
                : 8
                : e1006392
                Affiliations
                [1 ] Blue Brain Project, École Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
                [2 ] Biological and Environmental Sciences and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal, Kingdom of Saudi Arabia
                Centre National de la Recherche Scientifique, FRANCE
                Author notes

                The authors have declared that no competing interests exist.

                Author information
                http://orcid.org/0000-0002-2270-1989
                http://orcid.org/0000-0003-4856-0835
                http://orcid.org/0000-0002-6263-1356
                Article
                PCOMPBIOL-D-18-00310
                10.1371/journal.pcbi.1006392
                6160207
                30161133
                55634e3c-99cd-4224-8647-e469f0950862
                © 2018 Coggan et al

                This 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.

                History
                : 23 February 2018
                : 24 July 2018
                Page count
                Figures: 6, Tables: 0, Pages: 22
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/501100001703, École Polytechnique Fédérale de Lausanne;
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100004052, King Abdullah University of Science and Technology;
                Award Recipient :
                Funded by: Prefargier Foundation
                Award Recipient :
                Funded by: Synapsy
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/100012496, nccr – on the move;
                Award Recipient :
                Supported by a CRG grant from King Abdullah University of Science and Technology "KAUST-EPFL Alliance for Neuro-inspired High-Performance Computing", as well as ETH Board funding to the Blue Brain Project. Support by the NCCR Synapsy and the Prefargier Foundation to PJM are also acknowledged. Calculations were performed on the EPFL Blue Brain IV BlueGene/Q hosted at the Swiss National Supercomputing Center (CSCS) in Lugano. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology and Life Sciences
                Biochemistry
                Glycobiology
                Glycogens
                Biology and Life Sciences
                Cell Biology
                Cellular Types
                Animal Cells
                Glial Cells
                Macroglial Cells
                Astrocytes
                Biology and Life Sciences
                Cell Biology
                Cellular Types
                Animal Cells
                Neurons
                Biology and Life Sciences
                Neuroscience
                Cellular Neuroscience
                Neurons
                Physical Sciences
                Chemistry
                Chemical Compounds
                Organic Compounds
                Carbohydrates
                Monosaccharides
                Glucose
                Physical Sciences
                Chemistry
                Organic Chemistry
                Organic Compounds
                Carbohydrates
                Monosaccharides
                Glucose
                Biology and Life Sciences
                Biochemistry
                Metabolism
                Carbohydrate Metabolism
                Glucose Metabolism
                Biology and Life Sciences
                Biochemistry
                Neurochemistry
                Neuromodulation
                Biology and Life Sciences
                Neuroscience
                Neurochemistry
                Neuromodulation
                Biology and life sciences
                Cell biology
                Signal transduction
                Cell signaling
                Signaling cascades
                cAMP signaling cascade
                Biology and Life Sciences
                Cell Biology
                Signal Transduction
                Cell Signaling
                Signaling Cascades
                Protein Kinase Signaling Cascade
                Custom metadata
                vor-update-to-uncorrected-proof
                2018-09-27
                All relevant data are within the paper and its Supporting Information files.

                Quantitative & Systems biology
                Quantitative & Systems biology

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