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Logo of nihpaAbout Author manuscriptsSubmit a manuscriptNIH Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
J Neurochem. Author manuscript; available in PMC May 8, 2009.
Published in final edited form as:
PMCID: PMC2679179
NIHMSID: NIHMS106281

The in vivo neuron-to-astrocyte lactate shuttle in human brain

evidence from modeling of measured lactate levels during visual stimulation

Abstract

Functional magnetic resonance spectroscopy (fMRS) allows the non-invasive measurement of metabolite concentrations in the human brain, including changes induced by variations in neurotransmission activity. However, the limited spatial and temporal resolution of fMRS does not allow specific measurements of metabolites in different cell types. Thus, the analysis of fMRS data in the context of compartmentalized metabolism requires the formulation and application of mathematical models. In the present study we utilized the mathematical model introduced by Simpson et al. (JCBFM 27: 1766-1791, 2007) to gain insights into compartmentalized metabolism in vivo from the fMRS data obtained in humans at ultra high magnetic field by Mangia et al. (JCBFM 27: 1055-1063, 2007). This model simulates brain glucose and lactate levels in a theoretical cortical slice. Using experimentally determined concentrations and catalytic activities for the respective transporter proteins, we calculate inflow and export of glucose and lactate in endothelium, astrocytes and neurons. We then vary neuronal and astrocytic glucose and lactate utilization capacities until close correspondence is observed between in vivo and simulated glucose and lactate levels. The results of the simulations indicate that, when literature values of glucose transport capacity are utilized, the fMRS data are consistent with export of lactate by neurons and import of lactate by astrocytes, a mechanism that can be referred to as a neuron-to-astrocyte lactate shuttle (NALS). A shuttle of lactate from astrocytes to neurons (ANLS) could be simulated, but this required the astrocytic glucose transport capacity to be increased by 12-fold, and required that neurons not respond to activation with increased glycolysis, two conditions that are not supported by current literature.

Keywords: energy metabolism, neuronal activation, glucose transport and utilization, lactate, human brain

Introduction

The mammalian brain depends upon a continuous supply of circulating glucose to support its energetic demands primarily by oxidative metabolism, both at rest and during activation. In recent years, the field of brain energy metabolism has been consumed with questions regarding the precise fuel for neuronal metabolism during times of activation or neurotransmission, i.e. glucose or lactate, and the extent to which blood-borne glucose is metabolized through glycolysis to lactate by astrocytes to fuel neuronal metabolism (Dienel and Cruz 2004, Pellerin et al. 2007). Astrocytes are known to play a pivotal role during neurotransmission, as they are actively involved in neurotransmitter recycling, in the clearance of extracellular potassium ions, and in the propagation of Ca+ ‘waves’ (for review, refer to Hertz et al. 2007). The additional role of astrocytes as the source of energetic fuel for neurons was originally proposed by Pellerin and Magistretti (1994) who suggested that activation of neurons with the release of the neurotransmitter glutamate stimulated glycolysis in nearby astrocytes, and the lactate so produced was then released by astrocytes to fuel neuronal metabolism. This hypothesis was termed the astrocyte-neuron lactate shuttle hypothesis (ANLSH). The model does not exclude a direct neuronal glucose uptake, however it suggests that lactate produced by astrocytic glycolysis is the main metabolic fuel of (glutamatergic) neurons during neurotransmission.

Since the introduction of the ANLSH, a considerable amount of experimental and theoretical work has been put forth by different laboratories to validate or refute this working hypothesis, although a consensus still has not been reached, as reviewed in several papers (Mangia et al. 2003, Pellerin et al. 2007, Chih and Roberts Jr 2003, Dienel and Cruz 2004, Simpson et al. 2007, Fillenz 2005, Mangia et al. 2008). Much of the original work that led to the ANLSH derived from in vitro experiments, and establishing the metabolic role of lactate during neuronal activation in vivo is challenged by the difficulties in obtaining the necessary experimental evidence. In this context, Magnetic Resonance Spectroscopy (MRS) is a powerful tool for non-invasive investigation of brain metabolism, due to its ability to detect temporal changes in metabolite concentrations during neuronal activation. The reliable quantification of such changes during studies of functional MRS (fMRS) is still a demanding task (Mangia et al. 2008), and studies such as these have often produced inconsistent results (for review, see Mangia et al. 2006). However, ultra-high magnetic field systems can help in obtaining robust and accurate time-courses of metabolite changes. The concentrations of 17 brain metabolites were recently measured with unprecedented sensitivity and temporal resolution at 7 T in the human primary visual cortex during paradigms of visual stimulation (Mangia et al. 2006, Mangia et al. 2007a, Mangia et al. 2007b). Few metabolites were found to undergo changes in steady-state concentration in response to increased neuronal activity during prolonged visual stimulation (Mangia et al. 2007a). In agreement with previous findings (Frahm et al. 1996), glucose concentration ([Glc]) was found to undergo a gradual reduction during activation. In contrast to [Glc], lactate concentration ([Lac]) increased during the first minute of visual activation by ~0.2 μmol/g, reached a new-steady state, and returned to baseline at the end of the stimulus.

Despite the increased reliability of metabolite quantification attainable at ultra-high fields, the temporal and spatial resolution of fMRS does not provide direct evidence to prove or disprove hypotheses involving metabolic compartmentalization among different cell types, because the measured signal is averaged from a relatively large volume of cortex. Specifically, fMRS cannot provide direct information about the amounts of lactate and glucose used by neurons and astrocytes during activation, and the interpretation of changes of lactate concentration in vivo is anything but straightforward. Therefore, the analysis of tissue [Lac] changes in the context of compartmentalized metabolism requires the formulation of mathematical models. Aubert and Costalat developed a mathematical model of neuroglial coupling that predicts the time-courses of observable variables (as the total [Lac]) under the assumptions of the ANLSH (Aubert and Costalat 2002, Aubert and Costalat 2005, Aubert et al. 2005, Aubert et al. 2007). This approach was then utilized to demonstrate that the ANLSH is valid at least during the first period of prolonged stimulations (up to 30 s), and after the end of the stimulus (Aubert and Costalat 2005). Recently, another model has been suggested for brain metabolism, which includes the kinetic properties and distribution of glucose (GLUTs) and monocarboxylate (MCTs) transporter proteins in neurons, astrocytes, and endothelial cells (Simpson et al. 2007). This model also takes into account that glucose transported across the blood brain barrier into the basal lamina is free to diffuse into the interstitium. Based on the analysis of the extra-cellular [Lac] time-course measured in the rat brain during electrical stimulation (Hu and Wilson 1997), Simpson et al. concluded that neurons, and not astrocytes, are the main producers and consumers of lactate during activation (Simpson et al. 2007). Neuronal rather than astrocytic glycolysis was previously suggested based on human data obtained with positron emission tomography (Gjedde and Marrett 2001). In addition, several studies aimed at assessing glycolytic or oxidative activity in synaptosomes prepared from adult brain support the notion that neuronal glycolysis increases markedly during activation (Erecinska et al. 1991, Kauppinen and Nicholls 1986, Kauppinen et al. 1989).

The purpose of the present study was to utilize the model of Simpson et al. (2007) to analyze the experimental data obtained in humans with high field fMRS (Mangia et al. 2007a). Specifically, two scenarios were considered: 1) our core model, where both astrocytes and neurons increase glycolysis in response to increased neuronal activity, and neuronal glucose transport capacity is greater than that of the astrocytes, and 2) a variation on the model of Simpson et al. (2007) which mimics the ANLS condition, which required that astrocytic glucose transport capacity increase12-fold and that neurons do not respond to activation with increased glycolysis.

Methods

Experimental data

The human data utilized in these simulations have been previously published (Mangia et al. 2007a). Briefly, the study group consisted of 12 healthy volunteers, age 19-26 years, and each subject was studied twice during different visual stimulation paradigms; measurements were performed on a 7T/90cm horizontal bore magnet (Mangia et al. 2007a). 1H NMR spectra were analyzed during rest and stimulation periods for each paradigm, and time courses of 17 different metabolites were determined. Values for lactate and glucose concentrations during one of the functional paradigms were used in the simulations presented in this study.

Software

Simulations were carried out by 4th order Runge Kutta Numerical Integration using the software package Berkeley Madonna version 8.3.22. Details of the steady-state transport equations and differential equations used for modeling are fully accessible in Simpson et al. (2007), and can be downloaded from the website: http://glutxi.umassmed.edu/bbb/model.htm.

The model

Brain glucose and lactate uptake and utilization were simulated using the model of Simpson et al. (2007). Using experimentally determined transporter concentrations and kinetic parameters, the model calculates inflow and export of glucose and lactate in endothelium, astrocytes and neurons. The model varies the neuronal and astrocytic utilization of glucose and lactate until close correspondence is observed between in vivo and simulated glucose and lactate levels (Simpson et al. 2007). For both transporter (GLUT and MCT) isoforms, kinetic behavior (e.g. catalytic turnover and substrate affinity), expression level, and cellular expression are firmly based on experimentally determined values for neurons, astrocytes, endothelial cells, and erythrocytes. In addition, the model takes into account that small molecule self-diffusion within the basal lamina and interstitium allows for experimentally determined limits on diffusion such as tortuosity (Hrabetova and Nicholson 2004) and for demonstrations of unrestricted diffusion between the basal lamina and interstitium (Brightman and Reese 1969). Metabolite flow between compartments is bidirectional and, when carrier (GLUT or MCT)-mediated transport is involved, the appropriate transport equations are employed (Simpson et al. 2007, Stein 1986). Electroneutral proton-lactate co-transport is unaffected by altered membrane potential but is influenced by altered extra- or intracellular pH (Stein 1986). Since the effects over physiologic pH ranges are very small (Broer et al. 1998, Simpson et al. 2007), we ignore the effects of pH changes and therefore assume that net lactate transport proceeds in the direction of its concentration gradient. The compartmental sequence of glucose flow from blood to brain proceeds in the direction of capillary lumen to microvascular endothelial cell, to basal lamina, to astrocytic endfoot or to interstitium and is illustrated in Fig 4 of Simpson et al. (2007). Astrocytic glucose is exported either to the interstitium or back to the basal lamina. Interstitial glucose may be imported by neurons and astrocytes or may diffuse back to the basal lamina. Intracellular glucose may be metabolized to pyruvate/lactate which is then oxidized to CO2 or is exported to the interstitium whence it is imported by astrocytes or neurons, or diffuses to the basal lamina and exits the brain to the blood.

As described previously (Simpson et al. 2007), the following experimental observations are inherent components of the model and are critical to the successful modeling of the available data: 1) The catalytic activity (kcat) of GLUT3 protein is 7-fold greater than that for GLUT1, thereby explaining why neuronal glucose transport capacity is much greater than that of astrocytes (Maher et al. 1996); 2) Small molecules (≤ 40 kDa) are free to diffuse throughout and between the interstitium and basal lamina (Brightman and Reese 1969); 3) To be consistent with an oxygen to glucose index of 5.5 (an established number for the ratio between oxygen and glucose consumption rates in the human brain, Shulman et al. 2001), we assign 1/12 of the glucose entering both neurons and astrocytes to non-oxidative processes; 4) The virtual brain slice has a volume of 68 fL; 5) Neuronal, astrocytic, interstitial, basal lamina, and endothelial compartments are 49.5%, 29%, 18%, 1.5%, and 2% of total slice volume respectively (Hertz 2008). Our calculations do not account for the concentrations of pyruvate, which are approximately 10% of the lactate levels and in steady state with lactate (Siesjö 1978).

Rates of glucose and oxygen metabolism which are considered to test the predictability of the model are based on observed utilization rates in vivo, ~0.3 μmol/g/min (Heiss et al. 1984) and ~1.6 μmol/g/min, respectively (Siesjö 1978). It should be noted that the glycolytic values observed in vitro are usually higher than those observed in vivo, which likely reflects the hypoxic nature of tissue culture.

While experimental values for the activity and distribution of glucose and lactate transporters are accessible from an extensive number of studies on rat brain, the same does not apply for the human brain. However, the differences in metabolism between the rat and the human brain are available from the current literature and were taken into account in the present work. Oxygen consumption by human brain (1.6 μmol/g/min) is approximately one-half of that of rat brain (McKenna et al. 2006); glucose utilization by human brain (0.23 - 0.3 μmol/g/min) is 33% of that of rat brain (Clark and Sokoloff 1999); and glucose uptake by human brain (0.4 μmol/g/min) is 27 - 40% of uptake by rat brain (Hasselbalch et al. 1998). Based on these numbers, human glucose transport capacities in the current model have been adjusted to 40% of values used in simulations of the rat brain (Simpson et al. 2007). There is no available information for the comparison of rates of lactate transport between human and rat brain; in the present work we assume that the transport of lactate in the human brain is similar to that of rat brain. Human arterial serum glucose (5.5 mM) is slightly less than rat serum glucose (6 mM).

Glucose utilization and lactate oxidation are described by simple Michaelis-Menten kinetics, characterized by affinity constants Km (0.045 mM and 2 mM, respectively) and (maximum) capacities. Whereas the affinity constants are assumed a priori, the capacities are adjusted a posteriori until close correspondence between in vivo and simulated glucose and lactate levels is obtained. The model does not include increases in cerebral blood flow occurring during increased neuronal activity, since these should not significantly change either glucose or lactate influx or efflux from the tissue (see Simpson et al. 2007 for discussion).

Results and Discussion

Before simulating activation of the human visual cortex, the predictive value of the model was evaluated by examining how well the simulated serum [Glc] dependence of steady-state brain glucose levels compares with the steady-state human brain glucose data of Gruetter et al (1998). According to the ratio-metric approach of Gruetter et al (1998) in which Michaelis-Menten equations describe irreversible cerebral glucose utilization and reversible glucose transport across the blood brain barrier, the maximum glucose transport to glucose utilization ratio (Tmax:CMRglc) is 2.7. Our simulations mimic the experimental data of Gruetter et al (1998) (data not shown), suggesting that the model reproduces human brain glucose transport and utilization.

The simulations show that, under basal conditions, the capacity of the simulated brain slice to utilize glucose (sum of basal glycolytic capacities of neurons and astrocytes shown in Table 1) is 0.302 × 10-15 mmol/s for the core model, and 0.324 × 10-15 mmol/s for the ANLS simulation. By considering that the volume of our simulated slice is 68 fL, and basal [Glc] = 1.4 mM, these numbers convert to CMRglc of 0.26 μmol/g/min and 0.28 μmol/g/min, respectively, which are in good agreement with the value of ~0.3 μmol/g/min reported for the human brain (Siesjö 1978). The capacity of the simulated brain slice to oxidize lactate (sum of basal lactate oxidation capacities of neurons and astrocytes shown in table 1) is 1.79 × 10-15 mmol/s for the core model, and 1.94 × 10-15 mmol/s for the ANLS simulation. At basal astrocytic and neuronal [Lac] ≈ 1 mM, these rates convert to lactate utilization rates of 0.52 μmol/g/min and 0.56 μmol/g/min, respectively, which translate to O2 consumption rate of 1.60 μmol/g/min and 1.68 μmol/g/min. These numbers are in close agreement with the value of ~1.6 μmol/g/min reported for the human brain (Siesjö 1978).

Table 1
Simulation Parameters

Figure 1 illustrates the response of visual cortex glucose and lactate levels to stimulation. The lines drawn through the points represent the results of our simulations. In Figure 1A we simulated these results by using the core model employed by Simpson et al (2007). The key features of this model include: 1) neuronal glucose transport is more rapid than astrocytic glucose transport; 2) both neurons and astrocytes respond to activation with enhanced glycolysis although the neuron produces the most robust response. The metabolic responses which were necessary in order to successfully model the experimental findings are shown in Figure 2A. The initial rapid increase in brain lactate levels contrasts with the gradual decrease in brain glucose levels. The rapid phase was modeled by the introduction of transiently increased neuronal and astrocytic glucose utilization and a commensurate transient reduction in neuronal and astrocytic lactate utilization. Thereafter the slow transients in brain glucose and lactate required a small but sustained increase in neuronal and astrocytic glycolytic flux plus commensurate gradual increases in neuronal and astrocytic oxidative flux. During post-activation recovery, glucose transport into the brain is not sufficiently rapid to permit rapid recovery of brain glucose levels. Thus, reduced rates of neuronal and astrocytic glycolysis are necessary to simulate post-activation glucose recovery. Consequently, reduced neuronal and astrocytic lactate oxidation are required to prevent undershoot of lactate levels.

Figure 1
Simulations of changes in glucose and lactate concentrations from the human visual cortex during visual stimulation
Figure 2
Adjustments in neuronal and astrocytic glycolytic capacities and lactate oxidation capacities required to simulate the data of Figure 1

In Figure 1B, we simulated the experimental results by using a different set of assumptions that mimic the ANLS condition, as described previously by Simpson et al (2007). The key features of the model in this case include: 1) astrocytic glucose transport is increased approximately 12-fold to equal neuronal glucose transport; 2) only astrocytes respond to activation with enhanced glycolysis. The metabolic responses which were necessary to successfully model the experimental findings are shown in Figure 2B. Once again, the rapid early lactate transient requires a transient increase in astrocytic glycolysis plus commensurate transient reductions in astrocytic and neuronal lactate utilization. The rather slow transients in brain glucose and lactate require a sustained elevation in astrocytic glycolytic flux and commensurate small increases in neuronal and astrocytic oxidative flux. Post activation, rapid recovery of lactate and glucose levels requires transiently reduced astrocytic glycolysis plus transiently reduced neuronal and astrocytic lactate oxidation.

Net lactate flows from neuron to interstitium and from interstitium to astrocyte are shown in Figure 3. With the core model of Simpson et al (2007), lactate flows from the neuron to the interstitium and from the interstitium to the astrocyte under basal and stimulated conditions (Figure 3A). Thus the neuron is always a lactate exporter while the astrocyte is a net lactate importer. More detailed analysis reveals that under basal conditions, simulated steady-state neuronal, astrocytic, and interstitial lactate levels are 0.996, 0.925, and 0.967 mM respectively. This means that rates of unidirectional lactate uptake and exit in neurons (6.56 and 6.64 × 10-15 mmol/s, respectively) are almost balanced as are rates of unidirectional lactate uptake and exit in astrocytes (2.12 and 2.04 × 10-15 mmol/s, respectively) However, since [Lac]neuron > [Lac]interstitium > [Lac]astrocyte, the net flow of lactate, which approaches 0.8 × 10-16 mmol/s), is from neuron to interstitium to astrocyte. Simulating the ANLS condition in which astrocytic glucose transport capacity is artificially increased 12-fold, and in which neurons do not respond to activation with increased glycolysis, the net flow of lactate proceeds from the astrocytes to interstitium and from interstitium to neuron, both during basal conditions and activation (Figure 3B). Simulated steady-state neuronal, astrocytic, and interstitial lactate levels in the basal, ANLS slice are 0.897, 1.096 and 0.978 mM, respectively. This means that, as for the core model, rates of unidirectional lactate uptake and exit in neurons (6.25 and 6.02 × 10-15 mmol/s respectively) are almost balanced as are rates of unidirectional lactate uptake and exit in astrocytes (2.18 and 2.39 × 10-15 mmol/s respectively). However, since [Lac]astrocyte > [Lac]interstitium > [Lac]neuron, the net flow of lactate (which approaches 2.2 × 10-16 mmol/s) is from astrocyte to interstitium to neuron.

Figure 3
Contributions to interstitial lactate concentration before and after neuronal stimulation

Overall, these results indicate that, when neuronal and astrocytic glucose transport capacities are based on values reported in literature (core model), the increase in [Lac] observed in the human visual cortex during prolonged visual stimuli is consistent with import of lactate by astrocytes and export of lactate by neurons, a mechanism that can be referred to as the neuron-to-astrocyte lactate shuttle (NALS). In order to force the astrocyte to become a lactate exporter during stimulation (ANLS), the glucose transport capacity by astrocytes must be arbitrarily increased by 12-fold, and neurons must not respond to activation with increased glycolysis. Neither of these conditions is supported by current literature.

A recent study of cerebellar metabolism in the anesthetized rat supported the notion that astrocytic glutamate uptake (and therefore astrocytic glycolysis, as postulated by the ANLSH) cannot be the sole mechanism responsible for the increase of extracellular lactate levels during increased postsynaptic activity (Caesar et al. 2008). In fact, under normal neuronal activation, glucose consumption, oxygen consumption, and extracellular lactate levels were found to increase. In addition, application of 6-Cyano-7-nitroquinoxaline-2,3-dione (CNQX), a drug that does not alter glutamate uptake into astrocytes but blocks the AMPA receptors, abolished all evoked increases in postsynaptic activity, blood flow, glucose consumption, oxygen consumption, as well as concomitant increases in lactate.

The present results are in agreement with previous conclusions obtained by simulating animal data (Simpson et al. 2007). In addition, consistent with the present findings, a neuronal, rather than astrocytic, release of lactate in the extracellular space was shown to occur after the first 30 s of stimulation by the mathematical model implemented by Aubert and Costalat (2005) when the sodium neuronal influx was supposed to be 3-fold higher than in astrocytes.

While these simulations indicate a net flow of lactate from neurons to astrocytes, they do not exclude a local shuttle of lactate from astrocytes to neurons. Lactate can indeed be efficiently oxidized by neurons, and can be utilized as a preferential fuel in specific conditions, including early brain development (Dombrowski et al. 1989, Thurston and Hauhart 1989, Vannucci and Vannucci 2000). Several studies have shown that lactate has an important role during the recovery of synaptic activity following hypoxia (Schurr et al. 1997a, Schurr et al. 1997b) or traumatic brain injury (Chen et al. 2000), which lead to abnormal levels (up to 10 mM) of tissue lactate concentration [Lac].

We conclude that, based on the metabolic model introduced by Simpson et al. (2007), the evolution of [Lac] and [Glc] observed in humans by 1H MRS during prolonged visual stimulation (Mangia et al. 2007a) are consistent with a lactate shuttle from neurons to astrocytes (NALS). These results are in agreement with previous findings, however they do not rule out the possibility that lactate derived from astrocytic glycolysis can be utilized by neurons as a metabolic fuel in other metabolic conditions.

Acknowledgments

Supporting grants and Institutes: NIH P41RR08079; P30 NS057091; the W. M. Keck Foundation and the MIND Institute (S. Mangia); NIH DK 44888, DK 36081 (A. Carruthers); and DK075130 (I.A. Simpson), AHA 0575055N (S.J. Vannucci).

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