Glucose sparing by glycogenolysis (GSG) determines the relationship between brain metabolism and neurotransmission

Abstract

Over the last two decades, it has been established that glucose metabolic fluxes in neurons and astrocytes are proportional to the rates of the glutamate/GABA-glutamine neurotransmitter cycles in close to 1:1 stoichiometries across a wide range of functional energy demands. However, there is presently no mechanistic explanation for these relationships. We present here a theoretical meta-analysis that tests whether the brain's unique compartmentation of glycogen metabolism in the astrocyte and the requirement for neuronal glucose homeostasis lead to the observed stoichiometries. We found that blood-brain barrier glucose transport can be limiting during activation and that the energy demand could only be met if glycogenolysis supports neuronal glucose metabolism by replacing the glucose consumed by astrocytes, a mechanism we call Glucose Sparing by Glycogenolysis (GSG). The predictions of the GSG model are in excellent agreement with a wide range of experimental results from rats, mice, tree shrews, and humans, which were previously unexplained. Glycogenolysis and glucose sparing dictate the energy available to support neuronal activity, thus playing a fundamental role in brain function in health and disease.

Keywords: Astrocytes; energy metabolism; glucose; glycogen; lactate; neurochemistry.

Conflict of interest statement

Declaration of conflicting interests: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Figures

Figure 1.

Schematics of the major metabolic pathways of the GSG model. (a) shows a schematic of the fluxes of neuronal and astrocytic glucose metabolism for Glu-/GABA/-Gln cycle rates at or below the resting awake (RA) state, identified by VNTcycle-RA . Under the RA condition the net rate of glycogenolysis ( VGnet ) is equal to 0. The pseudo-MAS (PMAS) is a mechanism that couples glycolytic production of NADH in neuronal cytoplasm with NADH shuttling to and oxidation in mitochondria during the conversion of astrocyte-derived glutamine into neurotransmitter glutamate (see SI Section 6 and Fig. SI-3 for details); both the MAS and PMAS involve oxidation-reduction and transamination reactions. The dotted lines from Lac to the plasma membranes of astrocytes and neurons represent lactate release that corresponds to a small fraction (about 5%) of the glucose metabolized from the cells and from brain at or below the RA state. (b) shows the incremental fluxes of glucose and glycogen, as well as ATP synthesis, due to an increase in VNTcycle above RA state ( ΔVNTcycle>0 ). The flux values and predicted stoichiometries are derived in SI Sections 2-5. The majority of pyruvate from glycogenolysis leaves the astrocyte as lactate with a small fraction being oxidized as part of the glutamate and GABA oxidation and resynthesis pathways. Major pathways of ATP synthesis ( ΔVATP ) coupled to the rates of glucose and glycogen metabolism are indicated in green. Major pathways of ATP consumption are indicated in red, the largest being assigned to the neuronal and astrocytic Na+,K+-ATPase (see SI Section 5). For the derivation of the coefficients for ATP synthesis rates see SI Section 2, Eqs. SI-25 and SI-26. For derivation of the coefficients for astrocytic and neuronal ATP consumption by the Na+, K+-ATPase, see SI Section 5 and Eq. SI-64. The solid lines from Lac to the plasma membranes of astrocytes and neurons represent release of larger amounts of lactate from the activated cells and from brain. Abbreviations: Glc-6-P, glucose-6-phosphate; HK, hexokinase; Pyr, pyruvate; Lac, lactate; Mito, mitochondria; Glu, glutamate; GABA, γ-aminobutyric acid; Gln, glutamine; MAS, malate-aspartate shuttle; CMR, cerebral metabolic rate; V denotes rates for different pathways identified by subscripts and are defined in the ‘Theory and Calculations' within the main text.

Figure 2.

Predicted relationships between neuronal and astrocyte glucose and glycogen metabolism and energetics. The predicted slopes from the GSG model (blue lines) and ANLS model (brown lines) are plotted together with the experimental data and their least squares best fit (dotted lines represent 95% confidence intervals, CI95%; see Results and SI Section 7 and Table SI-2 for values and references). The units of ΔVGnet are μmol g−1min−1 (expressed in glucose units). (a,b) ΔVGnet versus ΔCMRglc tests the degree of glucose sparing during activation, without (a) or with (b) data acquired during seizure and ischemia. (c,d) ΔVGnet versus ΔVNTcycle tests whether there is a linear relationship during activation, without (c) or with (d) data acquired during seizure, consistent with direct coupling between glycogenolytic ATP production and neuronal activity. (e,f) ΔVATP-Gnet versus ΔVATP-ox-N tests the predicted relationship between incremental ATP synthesis from nonoxidative glycogenolysis versus neuronal glucose oxidation. The best linear solutions to the experimental data without (e) and with (f) seizure data give slopes in agreement with the GSG model (blue line) (prediction 0.20; e, slope = 0.205 ± 0.008, 95% CI 0.184-0.227; f, slope = 0.178, 95% CI 0.14–0.22). In contrast, if glycogenolysis is coupled to neuronal oxidation of astrocytic lactate by the ANLS mechanism (which would experimentally also have been measured as glucose oxidation), then a slope of 0.067 is predicted, which is 3-fold lower than the experimental data (bottom curve). Also shown (top curve) is the value of ΔVATP-A calculated from the GSG model, which includes glycogen oxidation ( ΔVATP-tot-Gnet ) equation (19) (e, slope = 0.409; f, slope = 0.381).

Figure 3.

Predicted effect of blocking glycogenolysis on the rates of oxidative and nonoxidative glucose consumption in awake and anesthetized rats. Plots of ΔCMRglc versus ΔCMRglc-ox (both expressed in glucose units) for studies in which the rate of brain signaling was enhanced by sensory stimulation and seizure (black symbols) and studies in which glycogenolysis ΔVGnet is blocked either pharmacologically (blue triangles) or by the experimental conditions (blue circle). See Table SI-2 for values and references.

Figure 4.

Calculated VATP-A versus ΔVATP-N from experimental rat data and predicted slope from the GSG model. VATP-A versus ΔVATP-N calculated from 13C MRS studies of rat cerebral cortex metabolism at different levels of electrical activity ranging from near isoelectricity (deep pentobarbital anesthesia) to the resting awake state (see equation (23), SI Section 3, and Tables SI-3, SI-4, and SI-5). The best fit line (black) to the slope of the experimental data is in good agreement with the prediction of the GSG model (blue).

Figure 5.

Plots of meta-analysis data for CMRglc-ox-N versus VNTcycle . Plots of (a) CMRglc-ox-N versus VNTcycle , (b) CMRglc-ox-N-Glu versus VNTcycle-Glu , (c) CMRglc-ox-GABA versus VNTcycle-GABA and (d) CMRglc-ox-N-(Glu+GABA) versus VNTcycle -(Glu+GABA) . Best fit slopes and CI95% are shown by solid and dashed black lines, respectively. See Tables SI-3, SI-4, and SI-5 for values and references. All oxidation rates are expressed in glucose units. The best fit lines and statistics were calculated from rat cerebral cortex data only (black dots). In panel a, data from mouse (blue), tree shrew (green) and human (orange) (Table SI-9) are plotted along with the rat data.

Figure 6.

ΔVLac and ΔCMRglc-nonox+ΔVGnet versus ΔCMRglc-ox-N during sensory stimulation in human and rat cerebral cortex. (a) The measured slope of the initial rate of lactate production in human brain from four studies versus the average increase in ΔCMRglc-ox-N (expressed in glucose units) (Table SI-8) was 2.65 ± 0.26, which is not significantly different (P=0.69) from the prediction of the glucose sparing model of 2.76 (blue line). For comparison, the slope predicted should there be no glycogen metabolism (inactive glycogenolysis) is Y = 1.0 (green line), supporting the presence of highly active glycogenolysis. (b) Plot of ΔCMRglc-nonox+ΔVGnet (non oxidative) versus ΔCMRglc-ox (expressed in glucose units) including measurements from studies of activated rat cortex (Table SI-2) and human data (orange filled circles). The best fit slope determined from the rat data was 3.14 ± 0.32 (R2=0.628), which is in agreement with the GSG model and the human lactate results, and well above the prediction if there were no astrocytic nonoxidative glycogenolysis (green line, Y = 1.0).

Figure 7.

Measured increase in CMRglc in rat and human cerebral cortex during sensory stimulation and predicted increase in CMRglc in the absence of glucose sparing. (a) Comparison of CMRglc measured using FDG-PET in human visual cortex during photic stimulation (blue) versus the value of CMRglc predicted should there be no glucose sparing by glycogenolysis (orange). All values are normalized to the resting awake state ( CMRglc-RA ). The dashed horizontal lines are the calculated maximum glucose transport rates ( VGT-max ) under normoglycemic (5.0 mM, VGT-max-norm ) and physiological hypoglycemic (3.5 mM, VGT-max-hypo ) plasma glucose concentrations. The values used and references are tabulated in Table SI-6. (b) The same plot using data from regional measurements of rat cerebral cortex during sensory stimulation (Table SI-2 for values and references). For the rat physiological fed and fasting plasma glucose levels are 7.0 mM and 5.0 mM, respectively. The two bars for the reference Dienel et al. 2007 indicate separate measurementsin the somatosensory and parietal cortex. The two bars for the reference Collins et al. 1987 indicate rates obtained under two visual stimulation frequencies.