PMCCPMCCPMCC

Search tips
Search criteria 

Advanced

 
Logo of wtpaEurope PMCEurope PMC Funders GroupSubmit a Manuscript
 
J Neurosci. Author manuscript; available in PMC Dec 27, 2012.
Published in final edited form as:
PMCID: PMC3390246
UKMSID: UKMS49004
Oxidative phosphorylation, not glycolysis, powers pre- and postsynaptic mechanisms underlying brain information processing
Catherine N. Hall, Miriam C. Klein-Flügge, Clare Howarth, and David Attwell
Department of Neuroscience, Physiology & Pharmacology University College London Gower Street, London, WC1E 6BT, UK
Correspondence to David Attwell, d.attwell/at/ucl.ac.uk Tel: (+44)-20-7679-7342
Neural activity has been suggested to initially trigger ATP production by glycolysis, rather than oxidative phosphorylation, for three reasons: glycolytic enzymes are associated with ion pumps; neurons may increase their energy supply by activating glycolysis in astrocytes to generate lactate; and activity increases glucose uptake more than O2 uptake. In rat hippocampal slices neuronal activity rapidly decreased the levels of extracellular O2 and intracellular NADH, even with lactate dehydrogenase blocked to prevent lactate generation, or with only 20% superfused O2 to mimic physiological O2 levels. Pharmacological analysis revealed an energy budget in which 11% of O2 use was on presynaptic action potentials, 17% was on presynaptic Ca2+ entry and transmitter release, 46% was on postsynaptic glutamate receptors and 26% was on postsynaptic action potentials, in approximate accord with theoretical brain energy budgets. Thus, the major mechanisms mediating brain information processing are all initially powered by oxidative phosphorylation, and an astrocyte-neuron lactate shuttle is not needed for this to occur.
Brain function depends critically on an adequate energy supply, in the form of oxygen and glucose provided in the blood, which is largely used on reversing the ion influxes underlying synaptic potentials and action potentials (Attwell & Laughlin, 2001). Averaged over time, brain ATP is almost entirely generated by the complete oxidation of glucose: glycolysis followed by oxidative phosphorylation results in a ratio of oxygen to glucose consumption of ~6:1 and oxidative phosphorylation provides ~87% (26 out of 30 molecules) of the ATP generated (Kety, 1957; Sokoloff, 1960). In the short term, however, when neuronal activity increases, ATP has been suggested to be initially produced by glycolysis, for three reasons.
First, both in brain and other tissues, glycolytic membrane-bound enzymes are directly associated with ion pumps such as the Na+/K+-ATPase (Knull, 1978; Paul et al., 1979; Mercer & Dunham, 1981; Lipton & Robacker, 1983; Dubinsky et al., 1998), H+-ATPase (Lu et al., 2001) and Ca2+-ATPase (Paul et al., 1989), suggesting that ion transport may be fuelled by ATP produced in a local compartment by glycolysis (Mercer & Dunham, 1981). Second, it has been proposed that neurons regulate their energy supply by turning on glycolysis in astrocytes. When active neurons release glutamate it is taken up into astrocytes, which are proposed to use glycolytically-derived ATP to power this uptake and the subsequent conversion of glutamate to glutamine, thus producing lactate which is exported to neurons as a substrate for mitochondrial oxidative phosphorylation (Pellerin & Magistretti, 1994; Magistretti et al., 1999). Third, because the increase in oxygen uptake during neural activity was found to be disproportionally small compared to the increase in blood flow and glucose uptake, it was suggested that glycolysis is the main energy-providing mechanism initially supporting neural activity (Fox et al., 1988). The fact that O2 uptake is small relative to the blood flow increase is the basis of BOLD functional imaging (Ogawa et al., 1993).
The notion that neuronal activity initially increases glycolytic ATP production, often assumed to be in astrocytes with subsequent transfer of lactate to neurons for oxidative phosphorylation, has become established in the literature (Hyder et al., 2006; Pellerin et al., 2007; Barros & Deitmer, 2009). However, this concept is based on techniques that have a relatively poor temporal resolution, and has been challenged by the demonstration that activity evokes a decrease in extracellular oxygen concentration (Malonek & Grinvald, 1996; Thompson et al., 2003) and a decrease in intracellular NADH (Kasischke et al., 2004; Brennan et al., 2006), both of which are consistent with at least some ATP being generated by oxidative phosphorylation.
We demonstrate that oxidative phosphorylation is the main mechanism initially providing energy to power neuronal activity, that the main subcellular mechanisms underlying information processing, i.e. presynaptic action potentials, neurotransmitter release, postsynaptic currents and postsynaptic action potentials, all consume oxygen, and that an astrocyte-neuron lactate shuttle is not needed for oxidative phosphorylation to occur.
Brain slices
Coronal brain slices (300 μm thick) containing the hippocampus were prepared on a vibratome from P21 Sprague-Dawley rats (of either sex), killed by cervical dislocation in accordance with UK government regulations. Slices were incubated for 30 min at 37°C, and then for at least 30 min at room temperature in oxygenated (95% O2/5% CO2) artificial cerebrospinal fluid (aCSF) containing (mM): NaCl 124, KCl 2.5, NaHCO3 26, MgCl2 1, NaH2PO4 1, glucose 10, CaCl2 2 and kynurenic acid 1 (to block glutamate receptors).
Experimental solutions
Slices were perfused with bicarbonate-buffered aCSF, as described above, but without the kynurenic acid, at 35°C. In experiments employing 20% oxygen the perfusion solution was bicarbonate-buffered aCSF, gassed with 20 % O2, 5 % CO2 and 75 % N2.
Recording field potentials
Synaptic and action potential activity was evoked by stimulating the Schaffer collaterals in the stratum radiatum of area CA3 with a concentric bipolar tungsten electrode while monitoring the field potential in the stratum pyramidale in CA1, using a glass microelectrode filled with aCSF (see Fig. 1A). Field potentials were measured with a patch-clamp, as the current needed to hold the electrode at 0 mV. Consequently they have a current amplitude given by the voltage deflection occurring in the extracellular space divided by the resistance of the electrode (~2 MΩ), and are inverted in sign compared to voltage recordings. Each stimulus was 60 μs long, 50-90 V, and delivered at 0.33 Hz (to monitor the effects of drugs on different components of the field potential) or at 20 Hz (when evoking sufficient neuronal activity to detect changes in extracellular [O2]). Field potentials were analysed, as in Fig. 1B, to provide a measure of the presynaptic action potential volley (proportional to the number of fibres excited), the postsynaptic field potential (fEPSP, proportional to the product of the number of fibres excited and the EPSC evoked in each postsynaptic cell), and the postsynaptic action potential (population spike, determined by the number of postsynaptic cells that fire action potentials in response to the synaptic input).
Figure 1
Figure 1
Stimulus-evoked field potentials, and O2 and NADH changes
O2 electrode recordings
Extracellular O2 levels were measured using a glass Clark type oxygen microelectrode with a 10 μm tip (Unisense, Denmark) which was inserted ~100 μm into the slice, with its tip centre in the stratum radiatum 30 μm from the pyramidal cell layer (Fig. 1A). The electrode was calibrated at least once a week using distilled water at 35°C equilibrated with 0%, 20% and 100% oxygen. Oxygen electrode and field potential recordings were acquired using pClamp 10.1 (Molecular Devices, CA), which was also used to control the stimulation. The O2 concentration in the bulk solution entering the bath was 543±15 μM (n=3), i.e. lower than the ~1 mM in the solution bubbled with 95% O2/5% CO2 because of O2 loss through the plastic walls of the tube connecting the solution reservoir to the bath.
NADH imaging
Reduced NADH is fluorescent (Aubin, 1979), while its oxidized form NAD+ is not. Reduced NADH in area CA1 of the hippocampus (including the strata radiatum, pyramidale and oriens: Fig. 1A) was imaged by focusing just below the slice surface using bright-field microscopy with a 20x or 40x water immersion objective. NADH fluorescence was excited using a xenon arc lamp, with a 300-370 nm excitation filter, 420-490 nm emission filter and 410nm dichroic. Emitted light was imaged using a CoolSnapHQ2 CCD camera and ImagePro software (Media Cybernetics), with an exposure time of 2 s and a capture rate of 0.41 Hz. Images were analysed with ImageJ software.
Experimental protocol
For most experiments NADH images, field potential recordings and [O2] measurements were obtained simultaneously. The standard protocol (Fig. 2A) consisted of two phases: 30 sec of 0.33 Hz stimulation followed (after 30 sec with no stimulation) by 10 s of stimulation at 20 Hz to generate an easily detectable metabolic response in the tissue (no stimulation was applied after this). The frequency of 20 Hz is similar to the peak firing rate produced in CA3 cells in vivo for optimal stimuli (mean value 13 Hz, but extending up to 25 Hz: Leutgeb et al., 2007).
Figure 2
Figure 2
Pharmacological analysis of O2 use on different subcellular mechanisms
This protocol was then repeated 3 times at an interval of 6 mins for each drug condition, and the field potential, O2 and NADH results from each triplicate were averaged. The first triplicate in each slice was drug free and was used as a control to which later triplicates were normalised. Since responses might change with time even under control conditions, to assess the effect of drugs we first assessed whether the response to a second control triplicate differed significantly from the first triplicate and, if it did, we compared the mean response in the second triplicate carried out in the presence of drug with the mean response in the second triplicate carried out in the absence of drug. For most experiments (including all from which the field potential was analysed), 1 μM TTX was added for the final stimulation triplicate. TTX abolishes all components of the field potential leaving only the stimulation artefact (Fig. 1B), which was subtracted from the previous recordings from the same slice to reveal the various field potential components.
Lactate measurements
To assess the effect of the lactate dehydrogenase inhibitor oxamate on hippocampal slice lactate levels, slices were incubated in 1 ml aCSF with and without 20 mM oxamate at 37°C for 5 mins (the earliest time at which measurements were taken after incubating slices with oxamate in the stimulation experiments). The slices were then removed and the bathing solution was assayed for lactate content using a commercially available colorimetric assay based on the reaction of lactate oxidase (Abcam, Cambridge, UK; some other lactate sensors are based on lactate dehydrogenase which would be inappropriate for experiments attempting to block this enzyme in the cells). This gave an absorbance proportional to lactate concentration over the range 0 to 10 mM, and the lactate concentration in the bathing aCSF was determined by comparison to known lactate concentrations. Oxamate (20 mM) did not affect the slope or intercept of the graph of absorbance as a function of concentration (slope increased by 3.6%, p=0.87; intercept increased by 1%, p=0.93) implying that oxamate did not inhibit the assay lactate oxidase.
Statistics
Statistical analysis was conducted using SPSS 16 (SPSS Inc.) or the StatTools resources at http://department.obg.cuhk.edu.hk/researchsupport/statmenu.asp. Unless stated otherwise, Student’s 2-tailed t-tests were used. Where multiple comparisons are presented, p values were corrected using a procedure equivalent to the Holm-Bonferroni method (for N comparisons, the most significant p value is multiplied by N, the 2nd most significant by N-1, the 3rd most significant by N-2, etc.; corrected p values are significant if they are less than 0.05). Data are presented as mean ± s.e.m.
Experimental approach
In this paper we use hippocampal slices to assess how energy is provided in response to stimulated activity by combining oxygen electrode recording, NADH imaging and modelling of how O2 concentration changes relate to O2 consumption. The slice preparation is crucial for these experiments for three reasons. First, unlike for cultured cells, the spatial relationship of neurons and astrocytes is preserved. Second, it allows pharmacological agents to be applied at a defined concentration. Third, and most importantly, unlike in intact brain, oxygen is supplied to the slice by diffusion from the perfusing solution, so that changes in the oxygen concentration in the slice reflect only changes in the rate of oxygen use and do not require complex modelling to interpret (see Gjedde, 2005). This is critically different from the in vivo brain, where the amount of oxygen supplied by the blood is often altered by the same experimental manipulations that alter oxygen use, confounding the interpretation of experiments. For example, glutamate receptor antagonists and inhibition of lactate production, as used below, will decrease blood flow (Akgören et al., 1994; Li & Iadecola, 1994; Brazitikos et al., 1993; Gordon et al, 2008), reducing oxygen supply (Offenhauser et al., 2005) and confounding the quantification of any effect on oxygen consumption.
Neuronal activity lowers extracellular O2 and intracellular NADH levels
Figure 1A and B show the experimental arrangement and typical field potentials recorded when stimulating the Schaffer collaterals at 0.33 Hz, including a small and brief presynaptic action potential volley, the field EPSP (a downward deflection when measured as a current, lasting about 15 msec), and the population spike (a brief upward deflection reflecting the occurrence of postsynaptic action potentials).
On advancing the oxygen electrode from the bulk perfusion solution to a position ~100 μm below the surface of the slice the O2 level decreased from the bulk solution value of 543 μM (see Experimental Procedures) to a mean value of 212±17 μM in 86 slices. A 10 sec train of stimulation at 20 Hz produced a decrease of O2 level of 118±8 μM in 86 slices (specimen trace in Fig. 1C). At the same time there was a 1.4±0.2% initial decrease in NADH fluorescence (averaged over the CA1 region), followed by a 2.4±0.3% increase above the original level (in 26 slices, specimen trace in Fig. 1D). In the stratum oriens, the resting NADH fluorescence was a little lower than in the strata pyramidale or radiatum (Fig. 1E), but neither the initial decrease of NADH level evoked by stimulation (Fig. 1F), nor the overshoot of [NADH] after stimulation (Fig. 1G) differed significantly between the three layers.
The decrease of [O2] implies that the rate of ATP production by oxidative phosphorylation has been increased. This may be due to ATP consumption leading to a rise in the [ADP]/[ATP]ratio (Chance & Williams, 1955), due to a rise of mitochondrial [Ca2+] activating the F0F1-ATPase (Territo et al., 2000; but see Gellerich et al., 2010), or due to a rise of extramitochondrial [Ca2+]i activating the mitochondrial aspartate-glutamate exchanger aralar (Contreras & Satrústegui, 2009; Gellerich et al., 2009) which raises [NADH] in mitochondria and thus supports H+ pumping out across the mitochondrial membrane. We will show below that the majority of the ATP produced in response to neuronal activity is by oxidative phosphorylation. The fall of NADH level is expected if neuronal activity increases oxidative phosphorylation to a rate which consumes NADH faster than it can be provided by the tricarboxylic acid (TCA) cycle and glycolysis (Fig. 1H). The subsequent overshoot in [NADH] to a value higher than the original level may reflect a late activation of glycolysis in astrocytes or neurons (Kasischke et al., 2004) as is sometimes assumed, but could alternatively be due to increased NADH production by the TCA cycle (Brennan et al., 2006) occuring when a rise of mitochondrial [Ca2+]i activates mitochondrial dehydrogenases ((Duchen, 1992); see Gellerich et al. (2010) and Gunter et al. (2004) for reviews and Mathiesen et al. (2011) for an opposing view).
O2 use on different subcellular mechanisms
The main energy-demanding processes mediating information processing, i.e. presynaptic action potentials, transmitter release, postsynaptic currents and postsynaptic action potentials (Attwell & Laughlin, 2001), occur in different subcellular compartments, and thus may differ in their dependence on ATP generation by glycolysis and oxidative phosphorylation. To assess this, we applied drugs to block, successively, postsynaptic currents and postsynaptic action potentials (10 μM NBQX and 50 μM D-AP5), presynaptic transmitter release and downstream postsynaptic events (250 μM Cd2+), and finally all action potentials and synaptic events (1 μM TTX).
To assess the effects of the drugs used, we analysed the extracellular field potentials. As expected, postsynaptic currents and postsynaptic action potentials were selectively abolished by NBQX+AP5, with no significant effect on the presynaptic action potential (Figs. 2A-D), Cd2+ also abolished postsynaptic events but spared the presynaptic action potential, while TTX abolished all electrical activity (Fig. 1B). We also tried using muscimol (20 μM) to activate GABAA receptors and thus prevent the postsynaptic cells from firing action potentials (Caesar et al., 2003), in an attempt to define the O2 use on postsynaptic action potentials. However, as observed by Jang et al. (2005), high levels of muscimol reduced the field EPSP by ~40% (data not shown), suggesting that presynaptic GABAA receptors reduce transmitter release, which would have confounded our allocation of O2 consumption to different subcellular mechanisms.
Blocking postsynaptic currents, and the postsynaptic action potentials they produce, with NBQX+AP5 reduced the 20 Hz stimulation evoked decrease of O2 level by 63% (p=2.7×10−9, compared to the preceding responses in the absence of drugs). The response in NBQX+AP5 was significantly smaller than the O2 response to a second set of stimulation in the absence of any drug (p=6×10−4, Fig. 2E), while applying the stimulation twice with no drug application had no significant effect on the O2 decrease (p=0.73, Con in Fig. 2E). Applying Cd2+, to additionally block presynaptic processes controlling transmitter release downstream of Ca2+ entry, as well as all processes (in addition to postsynaptic currents) activated by transmitter release (such as uptake and metabolic processing of transmitter, and activation of metabotropic glutamate receptors (mGluRs)), reduced the O2 decrease by a further 19% (Fig. 2E), while TTX abolished the O2 decrease. A similar series of reductions of the NADH fluorescence decrease (Fig. 2F) and overshoot (Fig. 2G) was seen when these drugs were applied. The NADH changes seen on drug application were not significantly different across the layers of the hippocampus (repeated measures ANOVA, p=0.42), so for this and subsequent experiments NADH data were averaged across the whole CA1 region.
These data indicate that oxidative phosphorylation is used to generate at least some of the ATP used to power presynaptic action potentials, presynaptic processes controlling transmitter release, and postsynaptic currents and action potentials.
Separating postsynaptic O2 use on glutamate-gated currents and action potentials
Calculations presented below show that the 63% reduction of the [O2] decrease produced by NBQX+AP5 implies that 72% of the O2 is used postsynaptically. However, this does not distinguish O2 use on postsynaptic glutamate receptor currents and on postsynaptic action potentials. To determine whether both or just one of these processes is powered by ATP from oxidative phosphorylation, we applied glutamate (500 μM) to activate AMPA/KA, NMDA and metabotropic glutamate receptors and thus to generate action potentials (the glutamate level reached deep in the slice will be in the low micromolar range because of uptake: Amato et al., 1994). The experiments were carried out in the presence of 250 μM Cd2+ to prevent the evoked action potentials from releasing more neurotransmitter. Repeated application of glutamate (in Cd2+) evoked an [O2] decrease that was not significantly different on the second application (p=0.93, Cd2+ bar in Fig. 2I), while if TTX was present during the second glutamate application (to block glutamate-evoked action potentials but not Na+ entry through glutamate-gated channels) the O2 decrease was reduced by 29% (p=0.013, n=7, Fig. 2H, 2I), reflecting the suppression of O2 use on reversing the ion movements associated with action potentials.
The dependence of action potential firing rate on mean glutamate-gated current, and hence the relative magnitudes of the ion influxes through glutamate-gated channels and through voltage-gated Na+ channels, may differ when action potentials are evoked by superfusing glutamate (as here) and by activating the Schaffer collateral input (as in Fig. 2E). In addition, superfusion of glutamate may activate extrasynaptic and astrocyte receptors that are not activated by synaptic glutamate release. However, the data in Fig. 2H & I demonstrate that activation of glutamate receptors, and the action potentials this produces, both evoke O2 use on ATP production by oxidative phosphorylation.
Oxidative phosphorylation is evoked by neuronal activity at physiological O2 levels
The experiments described above employed, as is customary, 95% oxygen (~1 mM) in the superfusion solution, which leads to an oxygen level in the brain slices of ~150-400 μM (at different depths in the slice: see Fig. 6A & B below), which is much higher than the in vivo value of 20-60 μM (Dings et al., 1998; Offenhauser et al., 2005). The fraction of ATP which is produced by oxidative phosphorylation might be reduced by the lower in vivo value, which can be mimicked by superfusing brain slices with solution equilibrated with 20% oxygen (Hall & Attwell, 2008), giving an oxygen level of 2-130 μM at different depths in the slice (data not shown). We therefore investigated the changes of O2 level and NADH fluorescence produced by neuronal activity in slices superfused with solution containing 20% O2.
Figure 6
Figure 6
Modelling the O2 consumption of the slice
Switching from 95% to 20% O2 in the superfusion solution did not significantly affect the amplitude of the presynaptic action potential (p=0.24), though the postsynaptic fEPSP (38% decrease, p=1.3×10−4) and the postsynaptic population spike (15% decrease, p=0.014; Fig. 3A) were significantly reduced. This reduction in postsynaptic responses may reflect a rise in the adenosine concentration in the slice in the lower O2 solution (Gordon et al., 2008) which acts on presynaptic receptors to reduce glutamate release. As was shown in Fig. 2B-D for 95% O2, NBQX+AP5 abolished the fEPSP and population spike, with no effect on the presynaptic action potential, while TTX abolished all evoked electrical activity (n=5-6 slices, data not shown).
Figure 3
Figure 3
Oxidative phosphorylation powers neuronal activity at physiological [O2]
In 20% O2 the resting O2 level before stimulation was 115±25 μM (n=18), i.e. only 54% of the value measured with 95% O2 in the superfusion solution. Thus, there is less O2 available to be consumed during periods of increased energy demand, and stimulation of the Schaffer collaterals could not lower the [O2] by the same amount as occurs in 95% O2 solution (~120 μM, Fig. 1). Accordingly, the initial decrease in [O2] was only 22±3% of that seen in 95% O2 solution, but the time course of the dip was significantly prolonged (Fig. 3B, D; it recovered to baseline in ~5 mins), consistent with ion pumping being powered by oxidative phosphorylation for a longer period after neuronal activity in 20% O2. Similarly, the initial decrease and late overshoot of NADH fluorescence averaged over the CA1 area were also reduced in 20% O2 solution (Fig. 3C). Switching from 95% to 20% O2 solution increased the resting NADH fluorescence by 5±2% (p=0.018; n=15). The time courses of the [O2] and [NADH] changes are compared in Fig. 3D. At both superfused O2 levels, the overshoot of the NADH concentration overlaps with much of the period of increased O2 use.
In the presence of NBQX+AP5, to block postsynaptic currents and action potentials, the O2 decrease was reduced to 32% of the value obtained in the absence of drugs, not significantly different to the reduction to 37% produced by NBQX+AP5 in 95% O2 solution (Fig. 3E, 3F, statistics are given in the legend). Thus, the fraction of O2 consumption that is on postsynaptic activity is approximately independent of O2 level.
Effect of blocking lactate dehydrogenase
The astrocyte-neuron lactate shuttle hypothesis proposes that astrocytes carry out glycolysis and use lactate dehydrogenase (LDH) to convert the end product of glycolysis, pyruvate, into lactate, which is transferred to neurons where neuronal LDH converts it back to pyruvate to fuel neuronal oxidative phosphorylation (Fig. 1H). To test this hypothesis, we blocked LDH in astrocytes and neurons using 20 mM oxamate (the IC50 for block is 0.6-4.4 mM: Wu et al., 2007). After 5 mins, oxamate significantly reduced lactate levels in the bathing aCSF by 66±7% (p=4.3×10−4) (Fig. 4A), consistent with LDH being inhibited. According to the astrocyte-neuron lactate shuttle idea, this ought to reduce or abolish the O2 decrease evoked by neuronal activity.
Figure 4
Figure 4
Blocking LDH does not affect the [O2] and [NADH] decreases
Blocking LDH also allows us to put limits on the relative importance of ATP production by oxidative phosphorylation and glycolysis. With inter-conversion of pyruvate and lactate blocked, if glycolytic ATP production were dominant, neuronal activity would produce a rise of NADH level, not a fall. Inspection of Fig. 1H shows that, with LDH blocked, glycolysis generates one NADH molecule per ATP produced, glycolysis followed by pyruvate entering the TCA cycle generates 2.5 NADH per ATP produced, while oxidative phosphorylation consumes 10/26 or 0.38 NADH molecules per ATP produced. It follows that a rise of [NADH] is expected if, averaged over all the astrocytes and neurons imaged, the rate of production of ATP by glycolysis is greater than 38% of the rate of ATP production by oxidative phosphorylation (or if the rate of ATP production by glycolysis followed by the TCA cycle is greater than 38%/2.5 = 15% of that produced by oxidative phosphorylation). Thus, if neuronal activity evokes a fall of NADH fluorescence, it implies that oxidative phosphorylation generates more than 100%-38% = 62% of the ATP powering the increase of neuronal activity (assuming that NADH generated in the cytoplasm rapidly equilibrates with mitochondrial NADH, the fluorescence of which may be enhanced by binding to proteins such as complex 1 (Blinova et al., 2008)).
In the presence of oxamate the resting level of [O2] and NADH fluorescence were unchanged (reduced by 1±6%, p=0.83, N=11 and by 2±2%, p=0.32, N=13, respectively). Furthermore, although oxamate reduced and slowed the field EPSC and population spike (see below), neuronal activity still evoked a decrease of [O2] and of NADH fluorescence (Fig. 4C, D), and the amplitudes of these decreases were not significantly different from when oxamate was absent (p=0.67 and 0.53 respectively, Fig. 4E-F). However oxamate significantly increased the late overshoot of NADH fluorescence (p=0.003, Fig. 4G). This is expected because, when glycolysis is activated with a delay after stimulation (Kasischke et al., 2004) and produces pyruvate, block of the conversion of pyruvate to lactate results in less consumption of NADH (see Fig. 1H), and allows more pyruvate to enter the NADH-generating TCA cycle (which is being activated: Brennan et al., 2006).
Although oxamate is widely used as an inhibitor of LDH, it also inhibits pyruvate decarboxylase (an enzyme expressed in astrocytes and neurons, which converts pyruvate to oxaloacetate to top up the TCA cycle with molecules) and, when pyruvate levels are low, pyruvate uptake into mitochondria (Martin-Requero et al., 1986a, b). Furthermore it can produce a small inhibition of aspartate aminotransferase (Rei, 1979), a component of the malate-aspartate shuttle which transfers cytoplasmic NADH into mitochondria. These effects are unlikely to be significant in our preparation, since inhibition of pyruvate uptake, the TCA cycle or NADH uptake in mitochondria would decrease oxidative phosphorylation, yet in our experiments the activity-evoked [O2] decrease was unaffected by oxamate.
The fact that neuronal activity still evokes a fall of both [O2] and [NADH] with LDH blocked implies that the majority of the ATP (at least 62%, see above) that powers the stimulation-evoked neuronal activity is produced by oxidative phosphorylation. Furthermore, the lack of a change in the decrease of [O2] evoked by neuronal activity when LDH is blocked rules out a transfer of lactate from astrocytes to neurons as a substrate for oxidative phosphorylation to power neuronal activity, at least in the short term.
Effects of oxamate on field potentials
Despite its lack of effect on the [O2] and [NADH] decreases, oxamate roughly halved the amplitude of the field EPSP and the population spike (Fig. 5A-D). This is a greater reduction of the population spike than was previously reported by Schurr & Payne (2007). These data might suggest a decrease in charge entry generating the field EPSP and the postsynaptic action potentials, implying a decreased energy requirement in oxamate, which should be reflected in lower oxygen use (contrary to the experimental observations in Fig. 4C, E). However, oxamate also increased the duration of the population spike by a factor of ~1.6 (p=6.2×10−5, Fig. 5A, E; modelling of the superimposed waveforms of the fEPSP and population spike showed that this was too large to result simply from the decrease of the underlying fEPSP) and increased the decay time of the fEPSP by a factor of ~1.5 (although this did not reach statistical significance, p=0.1, Fig. 5E). This suggests that, for reasons unknown, oxamate decreased and prolonged the EPSC, leading to less synchronization of spike timing in different neurons. As a result, although the fEPSP and population spike are decreased and prolonged, the overall O2 use does not change significantly.
Figure 5
Figure 5
Effects of oxamate on field potentials
Why oxamate alters the EPSC is unclear, but it does not appear to reflect a decrease of energy supply produced by a lack of substrate for oxidative phosphorylation, as applying pyruvate (1 mM) with oxamate did not prevent the changes in the fEPSP and population spike induced by oxamate (increased insignificantly by 3.0±8.0%, p=0.71, and 7±15%, p=0.71, respectively, n=8, compared to oxamate alone). Oxygen usage was also unaffected by pyruvate supplementation (increased by 10±7%, p=0.19, n=9, compared to oxamate alone). This suggests that either oxamate or the decrease in lactate concentration have a direct effect on the EPSC. Determining the mechanism of this effect is outside the scope of this study, but there may be contributions from a lactate-mediated decrease in prostaglandin uptake and rise of extracellular prostaglandin concentration (Chan et al., 2002; Gordon et al., 2008) which decreases EPSC amplitude but does not affect decay time (Koch et al., 2010) or from a promotion by lactate of hydroxyl radical formation (Ali et al., 2000) causing a peroxide-mediated increase of KATP channel activity (Avshalumov et al., 2005).
Modelling the relationship between the [O2] decrease and O2 use
To use the effect of the drugs in Fig. 2 to quantify the O2 used on different subcellular mechanisms, we need to understand how the measured [O2] decrease relates to the increase of O2 use evoked by neuronal activity. To establish this, we first estimated the resting O2 usage in the slice, as in Hall & Attwell (2008). The O2 electrode was advanced through the slice to determine the profile of [O2] across the unstimulated slice. The results were not significantly different in the stratum pyramidale and stratum radiatum (repeated measures ANOVA, p=0.26, N=6; Fig. 6A) and so were averaged (Fig. 6B). Next, these data were fitted with steady state solutions (obtained using the pdepe function in Matlab) of the diffusion equation
equation M1
(1)
where x is distance into the slice, c is the concentration of O2, D is its diffusion coefficient in brain at 37oC (1.54×10−9 m2/sec, Ganfield et al., 1970), Km = 1 μM is the EC50 for O2 activating oxidative phosphorylation (Cooper, 2003) and Vmax is the maximum rate of oxidative phosphorylation at saturating [O2]. The boundary condition at the bottom of the slice (x=300 μm, resting on the bath chamber) was assumed to be that δc/δx=0. By fixing the value of [O2] at the slice surface at its measured value (387±47 μM in 12 slices), and varying the value of Vmax, it was found that the data were best fitted with Vmax = 0.7 mM/min (Fig. 6B), about half the value found previously for acute cerebellar slices but similar to the value found for cultured cerebellar slices (Hall & Attwell, 2008). Having established this value of Vmax, we next estimated the thickness of the unstirred layer outside the slice, to allow us to compute changes of [O2] when Vmax was raised by neuronal activity. This was done by solving equation (1) both within the slice (with Vmax=0.7 mM/min) and outside the slice (with Vmax =0, D set to the free solution value of 2.74×10−9 m2/sec (at 35° C: van Stroe & Janssen, 1993), and with the [O2] in the bulk solution set to 543 μM, see Experimental Procedures), and varying the unstirred layer thickness until the [O2] value measured at the surface of the slice (387 μM) was reproduced. The unstirred layer was thereby estimated to be 70 μm thick. In addition, from the profile of [O2] across the slice, it was possible to estimate how deep in the slice the O2 electrode was positioned at the start of the experiments (estimated as 92 μm deep, similar to the intended depth of 100 μm).
With these parameters estimated, we next simulated how the [O2] profile across the slice was altered by Schaffer collateral stimulation. To mimic the effect of Na+ entry stimulating ATP consumption by the Na+/K+-ATPase, and hence increasing O2 use, we solved equation (1) within the slice for a step increase of Vmax (throughout the slice) from the 0.7 mM/min value derived above to a new higher value for 10 sec, followed by an exponential decay back to 0.7 mM/min. In the unstirred layer outside the slice, equation (1) was solved with Vmax=0. The initial values of [O2] across the slice were those calculated with Vmax set to 0.7 mM/min and an unstirred layer thickness of 70 μm, as above. To reproduce the peak [O2] decrease seen in 95% O2 in Fig. 3B (at a distance 92 μm into the slice), it was necessary to increase Vmax within the slice to 1.5 mM/min (i.e. an approximate doubling of the Vmax), while to reproduce the decay time course of the O2 transient, the time constant of decay of the Vmax increase after stimulation had to be set to 24 sec (a rate constant of 2.5 min−1: Fig. 6C). The resulting profile of [O2] through the slice at the peak of the response is shown in Fig 6D. Although neuronal activity may not really produce an immediate and constant increase in the Vmax for O2 use throughout the stimulation period, this assumed time course for the increase in Vmax during activity, and the subsequent exponential decrease, reproduced reasonably well the measured time course of the [O2] transient at a distance 92 μm into the slice. The calculated Vmax of 1.5 mM/min is similar to the CMRO2 measured in vivo in anaesthetized rats (Ichord et al., 2001; Zhu et al., 2007) and about 1/3 of the value calculated from glucose usage in unanaesthetized rats (Sokoloff et al., 1977), implying that the neuronal activity that we are evoking is similar to that normally studied in anaesthetized animals, but below the maximum level occurring in resting animals in vivo. This is probably not due to our use of P21 (rather than adult) rats, because the cerebral metabolic rate for oxygen is not significantly different at these two ages (Dahlquist & Persson, 1976). Presumably, therefore, we are not stimulating sufficient axons to generate activity matching that occurring in vivo.
With the response in control solution reasonably well reproduced, we then investigated the effect on the predicted [O2] transient of reducing the increase of Vmax, to mimic the effect of reducing the activity-evoked increase of O2 use with glutamate receptor blockers or Cd2+. The aim was to assess how the amplitude of the [O2] transient was related to the change of Vmax that generated it. For this analysis we assumed that there was no change in the time constant with which the Vmax decreased after activity. The resulting relationship between the amplitude of the [O2] decrease evoked by activity and the underlying increase of Vmax was roughly linear, but with a decrease in slope at larger values of Vmax (Fig. 6E). The non-linearity in this relationship results from the fact that, in the depth of the slice, the predicted [O2] becomes comparable to the Km for O2 use by mitochondria (Fig. 6D), rendering equation (1) non-linear (unlike for c>>Km when eqn. (1) becomes D.δ2c/δx2 - δc/δt = Vmax so that changes of c are proportional to changes of Vmax). When we calculated the increased O2 usage at the position of the O2 electrode as (cf. eqn. 1)
equation M2
and integrated over a 4 minute period from when the 10 sec stimulation started, this was found to vary approximately as the amplitude of the O2 dip raised to the power 1.3 (Fig. 6F). Using this relationship, the changes in the amplitude of the O2 dip measured in Fig. 2 can be converted to relative O2 usage on different mechanisms (see below).
A similar analysis showed that (in the absence of blocking drugs) the stimulation-evoked O2 usage in 20% O2 was 77% of that occurring in 95% O2. This 23% decrease is approximately as expected, given the 38% decrease of fEPSP amplitude and 15% decrease of population spike amplitude seen in 20% O2 (Fig. 3A). Thus, at an approximately physiological O2 level, almost as much ATP is made by oxidative phosphorylation as occurs in 95% O2.
Finally, we examined the sensitivity of the O2 electrode for detecting O2 usage at different spatial locations, by simulating in 2 dimensions (into the depth of the slice and across the slice from the stratum radiatum and stratum lacunosum moleculare to the stratum oriens and alveus) the change in O2 concentration that occurs. Starting from the steady state solution to equation 1 with Vmax = 0.7 mM/min, we simulated the O2 concentration change occurring when Vmax was increased for 10 seconds to 1.5 mM/min, either solely in the stratum radiatum and stratum lacunosum moleculare (the combined width of which was measured as 258 μm in 6 slices) or solely in the stratum pyramidale, stratum oriens and alveus (combined width measured as 184 μm). MathCad was used to solve by Euler’s method the 2 dimensional diffusion equation with O2 consumption:
equation M3
A distance step of 2 μm in each direction and a time step of 0.25 msec were used, after checking that 1 μm and 0.1 msec steps gave negligibly different results. At the location we placed the O2 electrode (92 μm into the slice, at a distance 30 μm into the stratum radiatum: see above) increasing Vmax to 1.5 mM/min throughout the stratum radiatum and stratum lacunosum moleculare decreased [O2] by 61 μM, while increasing Vmax to 1.5 mM/min throughout the alveus, stratum oriens and stratum pyramidale decreased [O2] by 35 μM (i.e. 57% of 61 μM). Since the alveus/stratum oriens/stratum pyramidale is only 71% of the width of the stratum radiatum/stratum lacunosum moleculare (so the total increased O2 use was only 71% of that assumed for the simulation when there was increased O2 use in the stratum radiatum/stratum lacunosum moleculare), this means that the sensitivity to Vmax increases in the alveus/stratum oriens/stratum pyramidale is 20% (= 1 - 57%/71%) less than for Vmax changes in the stratum radiatum/stratum lacunosum moleculare. This might be thought to result in an underestimate of the O2 use on postsynaptic action potentials, since in pyramidal cells these will use O2 in the alveus, stratum oriens and stratum pyramidale. However, the underestimate will be less than 20% (and is ignored in what follows), because some of the O2 use on postsynaptic action potentials will occur in interneurons in the stratum radiatum.
To deduce the relationship between [O2] decrease and O2 use in the experiments of Fig. 2H employing glutamate superfusion, simulations similar to those described for Fig. 6F were carried out for the longer period of O2 usage evoked by glutamate superfusion, which predicted that O2 usage would vary as the amplitude of the O2 dip raised to the power 1.5.
The fraction of O2 use on the subcellular mechanisms mediating information processing
Correcting the 63% reduction in the size of the stimulation-evoked [O2] transient that is produced by NBQX+AP5 in Fig 2E, for the non-linearity of the relationship between [O2] dip and O2 consumption that is shown in Fig. 6F, we calculated that postsynaptic currents and postsynaptic action potentials are responsible for 72% of the O2 usage. Similarly the 82% block of the O2 transient produced by Cd2+, when corrected for the non-linearity of Fig. 6F, implies that 89% of the O2 is used on mechanisms that are blocked by Cd2+. The difference between the 72% reduction of the [O2] usage produced by NBQX+AP5 and the 89% reduction produced by Cd2+ implies that events that are not triggered by activation of postsynaptic glutamate ionotropic receptors but are triggered by presynaptic Ca2+ entry (i.e. pumping out presynaptic Ca2+, vesicle release and refilling, actions of mGluRs, and transmitter uptake) consume 17% of the O2. The difference between the 89% reduction of [O2] usage by Cd2+ and the complete block produced by TTX implies that 11% of the O2 usage is on presynaptic action potentials. This division of O2 usage is shown in Fig. 7A.
Figure 7
Figure 7
The distribution of O2 use across different subcellular processes
With the split of energy use between pre- and postsynaptic mechanisms given above, we can use the data in Fig. 2I to estimate how the O2 consumption on postsynaptic mechanisms is divided between glutamate-gated ion channels and action potentials, if we assume that glutamate-evoked energy use on mGluRs and in astrocytes is small (Attwell & Laughlin (2001) estimated that, for each vesicle of glutamate released, the ATP use on mGluRs was only 2.2% of that on ionotropic glutamate receptors, and the ATP use in astrocytes was only 6.8% of that in neurons or less if ATP use on action potentials was included). To do this, we assume that the dependence of action potential firing rate on mean glutamate-gated current is the same when action potentials are evoked by superfusing glutamate (as in Fig. 2I) and by activating the Schaffer collateral input (as in Fig. 2E), so that the relative magnitudes of the ion influxes through glutamate-gated channels and through voltage-gated Na+ channels are the same in both situations. With this assumption, the 29% reduction of the O2 dip seen in Fig. 2G was transformed through a relationship like that in Fig. 6F (see above). This transformation predicted that the O2 use attributed to postsynaptic mechanisms above is split between postsynaptic glutamate-gated currents and postsynaptic action potentials in a ratio of 64%:36%, implying that 46% (i.e. 72% x 0.64) of the O2 use evoked by Schaffer collateral stimulation is on postsynaptic currents, and 26% (72% x 0.36) is on postsynaptic action potentials. Combining these O2 usages, with those for presynaptic action potentials and non-postsynaptic events downstream of presynaptic Ca2+ entry in Fig. 7A, gives the division of O2 use shown in Fig. 7B.
NADH usage
Knowing the amount of oxygen used during Schaffer collateral stimulation allows us to calculate the NADH turnover that must be occurring. From the curve fit to Fig. 6F and the mean oxygen dip of 118 μM (Fig. 1), 0.485 mM O2 can be calculated to be consumed following Schaffer collateral stimulation. Ten NADH molecules are used for each 6 O2 molecules consumed (Fig. 1H), implying a usage of 0.808 mM NADH. Importantly, the resting level of NADH in hippocampus is only 0.057 μmoles/g tissue (Klaidman et al., 1995), or 60 μM assuming a density of 1.05 g/ml. Using this resting NADH concentration, the measured 1.4% decrease of [NADH] (Fig. 1F and associated text) implies that [NADH] decreases by only 0.84 μM, under-representing the absolute usage of NADH by 3 orders of magnitude. High rates of both NADH production and consumption must, therefore, be occurring during the NADH dip period and, since oxygen is still being used (Fig 3D), during the overshoot. As the NADH dip and overshoot poorly reflect the actual amounts of NADH used and generated, they cannot be used to quantify the amount of oxidative phosphorylation or glycolysis occurring. For this reason, we limit our interpretation of the NADH changes to arguing that the existence of a dip means that there is a larger relative contribution of oxidative phosphorylation than glycolysis to ATP production following neuronal stimulation (see above).
Our data lead to three major conclusions for the powering of neuronal activity. First, the majority of the ATP powering increases of neuronal activity is produced by oxidative phosphorylation. Second, the main mechanisms contributing to information processing, i.e. presynaptic action potentials, transmitter release, postsynaptic currents and postsynaptic action potentials, are all powered by ATP generated from oxidative phosphorylation. Third, the simplest version of the astrocyte-neuron lactate shuttle hypothesis, in which neuronal activity initially triggers ATP generation by glycolysis in astrocytes which then release lactate to rapidly power neuronal oxidative phosphorylation, is not consistent with our data.
The majority of ATP is generated by oxidative phosphorylation
Neuronal activity evoked by stimulating the Schaffer collaterals generated an initial decrease in both extracellular [O2] and intracellular [NADH] (Fig. 1). These decreases were also seen when a physiological oxygen level was produced in the slice by superfusion with solution gassed with 20% oxygen (Fig. 3), and they still occurred when lactate dehydrogenase was blocked with oxamate (Fig. 4). The fact that a decrease of [NADH] is seen, averaged over the neurons and astrocytes in the slice, with lactate dehydrogenase blocked to prevent inter-conversion of pyruvate and lactate, implies that at least 62% of the increase in ATP production which occurs in the slice to power the increase in neuronal activity is generated by oxidative phosphorylation (see Results).
As reviewed in the introduction, the association of glycolytic enzymes with ion pumps, the apparently larger fractional increase of glucose uptake than of oxygen uptake in response to neuronal activity (Fox et al. (1988), but see Madsen et al. (1999) who found a less significant decrease of the O2:glucose utilisation ratio), and the notion that neurons regulate their energy supply by initially increasing glycolysis in astrocytes, all suggested that neuronal activity was initially powered by glycolysis. Our data show, on the contrary, that oxidative phosphorylation is responsible for most of the increase in ATP production. In a methodologically very different approach, magnetic resonance imaging and spectroscopy have recently suggested a similar conclusion (Lin et al., 2010).
The change of O2 concentration evoked by 10 sec of 20 Hz stimulation of the Schaffer collaterals could be predicted if the rate of O2 consumption approximately doubled at the start of stimulation and decayed exponentially after the stimulation with a time constant of 24 seconds (Fig. 6). Although we assumed an immediate rise in O2 consumption in our model, in reality it is likely that the rise is slower (set by the rate of rise of [Na+]i and [K+]o which stimulate sodium pump activity), and that the kinetics of the fall of [O2] are set by diffusive equilibration with the bulk solution and are not critically dependent on the rate at which O2 usage turns on. The recovery of [O2] use after stimulation is much slower than is predicted if metabolic demand were removed immediately when the stimulation stopped (Fig. 6C), and presumably the 24 sec decay of O2 use that we derived for 95% O2 reflects the time needed for the sodium pump to restore the ion gradients across the cell membranes. In 20% O2 the decay of O2 use was greatly prolonged (Fig. 3B), implying that the local O2 level in the brain will influence the time scale on which neurons can reinstate their ion gradients after activity.
After the initial decrease of [O2] and [NADH], there was an increase of [NADH] above its pre-stimulus level, which may reflect increased NADH production either by glycolysis or by an increased activity of the TCA cycle. The [NADH] overshoot overlaps in time with the prolonged decrease in [O2] evoked by stimulation (Fig. 3D) and so occurs at a time when oxidative phosphorylation is increased.
The distribution of O2 consumption on different subcellular mechanisms
Using pharmacological agents to isolate different subcellular mechanisms contributing to neuronal activity, we demonstrated that presynaptic activity, transmitter release and recycling, and postsynaptic activity are all powered at least partly by oxidative phosphorylation (Fig. 2). Using the response to superfused glutamate, in the presence and absence of TTX, to separate energy use on postsynaptic glutamate-gated currents and on action potentials, we estimate that presynaptic action potentials consume ~11%, presynaptic Ca2+ entry, transmitter release/recycling and mGluR activity consume ~17%, postsynaptic currents use ~46% and postsynaptic action potentials consume ~26% of the O2 (Fig. 7B), so pre- and postsynaptic action potentials together use 37% of the O2.
Thus, the present findings provide evidence against the hypotheses that most energy is used presynaptically (Jueptner & Weiller, 1995) or that action potential propagation operates mainly anaerobically (Lecoq et al., 2009). On the other hand, they support findings showing that a large fraction of energy consumption is postsynaptically driven (Attwell & Laughlin, 2001; Offenhauser et al., 2005).
The energy budget of Attwell & Laughlin (2001) for rat cortex predicts the energy used on different components of neuronal signalling. From their Fig. 3A, ignoring ATP used on the resting potential, and reducing the action potential energy use by a factor of 3.08 to compensate for the fact that mammalian neurons use 3.08-fold less energy (per membrane area) on action potentials than do the squid action potentials that the Attwell & Laughlin (2001) budget was based on (Alle et al., 2009), action potentials are expected to use 28%, presynaptic Ca2+ entry, transmitter release/recycling and mGluRs to consume 11%, and postsynaptic currents to use 61% of the stimulation-evoked ATP consumption. This is in reasonable agreement with Fig. 7B, considering that we are studying hippocampus not cortex, and that the relative contributions of the different mechanisms may vary with stimulus frequency (e.g. due to AMPA receptor desensitization or NMDA receptors experiencing less Mg2+-block during high frequency stimulation).
Implications for the astrocyte-neuron lactate shuttle hypothesis
The astrocyte-neuron lactate shuttle hypothesis assumes that astrocytes convert glycolytically derived pyruvate to lactate using lactate dehydrogenase, before exporting it to neurons where it is converted back to pyruvate, again by lactate dehydrogenase, and then enters the TCA cycle as fuel for oxidative phosphorylation (Fig. 1H). On this basis, one might expect blocking lactate dehydrogenase to abolish or reduce the increase in O2 consumption evoked by neuronal activity. We found, however, that the LDH blocker oxamate had no effect on the initial decrease in [O2] or [NADH] that is evoked by Schaffer collateral stimulation (Fig. 4). We conclude that the increase in oxidative phosphorylation, that generates ATP to power an increase of neuronal activity, does not require lactate transfer from astrocytes.
It is worth highlighting that, at P21, rats express their highest levels of the monocarboxylate transporter responsible for transporting lactate into neurons (MCT2), with expression decreasing thereafter (Prins, 2008), and increased MCT2 expression is proposed to lead to increased lactate shuttle activity (Pellerin and Magistretti, 2011). If neuronal energy metabolism does not depend on lactate transfer at P21, therefore, it is unlikely to contribute at older ages, when MCT2 expression is lower.
Apparently contradicting our findings, Schurr and Payne (2007) and Schurr & Gozal (2012) found that inhibiting LDH with malonate or oxamate decreased neuronal function when hippocampal slices were maintained in glucose or lactate, but that neuronal function could be preserved by superfusing pyruvate, supporting the idea of a lactate shuttle. However, effects of malonate and oxamate on neuronal function were only seen after 30-45 minutes or after excitotoxic challenge. Furthermore, and crucially, oxidative phosphorylation was not monitored by recording oxygen level, so the interpretation of the data presented in terms of altered ATP production by mitochondria is not secure. We suggest that, while lactate may be important for long term functioning of the slice, it is not required for the short term increase in oxidative phosphorylation that occurs after an increase in neuronal activity. This interpretation is consistent with a recent review (Mangia et al., 2011) of contradictory modelling studies that disagreed over whether lactate passes from astrocytes to neurons or from neurons to astrocytes. Mangia et al. (2011) concluded that, whichever way lactate moves, its contribution to oxidative phosphorylation is small (see also Dienel & Cruz, 2008). An export of lactate from astrocytes to neurons has recently been suggested to be essential for hippocampal synaptic plasticity (Suzuki et al., 2011). Our data suggest that this effect may be mediated by lactate functioning as a signalling molecule (Song & Routh, 2005; Shimizu et al., 2007; Bezzi & Volterra, 2011), rather than as a metabolic substrate.
Acknowledgements
Supported by the European Research Council, Fondation Leducq and Wellcome Trust. We thank Paikan Marcaggi and Marieke Schölvinck for early work on this project.
  • Akgören N, Fabricius M, Lauritzen M. Importance of nitric oxide for local increases of blood flow in rat cerebellar cortex during electrical stimulation. Proc Natl Acad Sci USA. 1994;91:5903–5907. [PubMed]
  • Ali MA, Yasui F, Matsugo S, Konishi T. The lactate-dependent enhancement of hydroxyl radical generation by the Fenton reaction. Free Radic Res. 2000;32:429–438. [PubMed]
  • Alle H, Roth A, Geiger JR. Energy-efficient action potentials in hippocampal mossy fibers. Science. 2009;325:1405–1408. [PubMed]
  • Amato A, Ballerini L, Attwell D. Intracellular pH changes produced by glutamate uptake in rat hippocampal slices. J Neurophysiol. 1994;72:1686–1696. [PubMed]
  • Attwell D, Laughlin SB. An energy budget for signaling in the grey matter of the brain. J Cereb Blood Flow Metab. 2001;21:1133–1145. [PubMed]
  • Aubin JE. Autofluorescence of viable cultured mammalian cells. J Histochem Cytochem. 1979;27:36–43. [PubMed]
  • Avshalumov MV, Chen BT, Koós T, Tepper JM, Rice ME. Endogenous hydrogen peroxide regulates the excitability of midbrain dopamine neurons via ATP-sensitive potassium channels. J Neurosci. 2005;25:4222–4231. [PubMed]
  • Barros LF, Deitmer JW. Glucose and lactate supply to the synapse. Brain Res Rev. 2009;63:149–159. [PubMed]
  • Bezzi P, Volterra A. Astrocytes: powering memory. Cell. 2011;144:644–645. [PubMed]
  • Blinova K, et al. Mitochondrial NADH fluorescence is enhanced by complex I binding. Biochemistry. 2008;47:9636–9645. [PMC free article] [PubMed]
  • Brazitikos PD, Pournaras CJ, Munoz JL, Tsacopoulos M. Microinjection of L-lactate in the preretinal vitreous induces segmental vasodilation in the inner retina of miniature pigs. Invest Ophthalmol Vis Sci. 1993;34:1744–1752. [PubMed]
  • Brennan AM, Connor JA, Shuttleworth CW. NAD(P)H fluorescence transients after synaptic activity in brain slices: predominant role of mitochondrial function. J Cereb Blood Flow Metab. 2006;26:1389–1406. [PubMed]
  • Caesar K, Thomsen K, Lauritzen M. Dissociation of spikes, synaptic activity, and activity-dependent increments in rat cerebellar blood flow by tonic synaptic inhibition. Proc Natl Acad Sci USA. 2003;100:16000–16005. [PubMed]
  • Chan BS, Endo S, Kanai N, Schuster VL. Identification of lactate as a driving force for prostanoid transport by prostaglandin transporter PGT. Am J Physiol Renal Physiol. 2002;282:F1097–F1102. [PubMed]
  • Chance B, Williams GR. Respiratory enzymes in oxidative phosphorylation. III. The steady state. J Biol Chem. 1955;217:409–427. [PubMed]
  • Contreras L, Satrústegui J. Calcium signaling in brain mitochondria: interplay of malate aspartate NADH shuttle and calcium uniporter/mitochondrial dehydrogenase pathways. J Biol Chem. 2009;284:7091–7099. [PubMed]
  • Cooper CE. Competitive, reversible, physiological? Inhibition of mitochondrial cytochrome oxidase by nitric oxide. IUBMB Life. 2003;55:591–597. [PubMed]
  • Dahlquist G, Persson B. The rate of cerebral utilization of glucose, ketone bodies and oxygen: a comparative in vivo study of infant and adult rats. Pediat Res. 1976;10:910–917. [PubMed]
  • Dienel GA, Cruz NF. Imaging brain activation: simple pictures of complex biology. Ann NY Acad Sci. 2008;1147:139–170. [PMC free article] [PubMed]
  • Dings J, Meixensberger J, Jager A, Roosen K. Clinical experience with 118 brain tissue oxygen partial pressure catheter probes. Neurosurgery. 1998;43:1082–1095. [PubMed]
  • Dubinsky WP, Mayorga-Wark O, Schultz SG. Colocalization of glycolytic enzyme activity and KATP channels in basolateral membrane of Necturus enterocytes. Am J Physiol. 1998;275:C1653–1659. [PubMed]
  • Duchen MR. Ca2+-dependent changes in the mitochondrial energetics in single dissociated mouse sensory neurons. Biochem J. 1992;283:41–50. [PubMed]
  • Fox PT, Raichle ME, Mintun MA, Dence C. Nonoxidative glucose consumption during focal physiologic neural activation. Science. 1988;241:462–464. [PubMed]
  • Ganfield RA, Nair P, Whalen WJ. Mass transfer, storage, and utilization of O2 in cat cerebral cortex. Am J Physiol. 1970;219:814–821. [PubMed]
  • Gellerich FN, et al. Extramitochondrial Ca2+ in the nanomolar range regulates glutamate-dependent oxidative phosphorylation on demand. PLoS One. 2009;4:e8181. [PMC free article] [PubMed]
  • Gellerich FN, et al. The regulation of OXPHOS by extramitochondrial calcium. Biochim Biophys Acta. 2010;1797:1018–1027. [PubMed]
  • Gjedde A. The pathways of oxygen in brain. I. Delivery and metabolism of oxygen. Adv Exp Med Biol. 2005;566:269–275. [PubMed]
  • Gordon GR, Choi HB, Rungta RL, Ellis-Davies GC, MacVicar BA. Brain metabolism dictates the polarity of astrocyte control over arterioles. Nature. 2008;456:745–749. [PubMed]
  • Gunter TE, Yule DI, Gunter KK, Eliseev RA, Salter JD. Calcium and mitochondria. FEBS Lett. 2004;567:96–102. [PubMed]
  • Hall CN, Attwell D. Assessing the physiological concentration and targets of nitric oxide in brain tissue. J Physiol. 2008;586:3597–3615. [PubMed]
  • Hyder F, Patel AB, Gjedde A, Rothman DL, Behar KL, Shulman RG. Neuronal-glial glucose oxidation and glutamatergic-GABAergic function. J Cereb Blood Flow Metab. 2006;26:865–877. [PubMed]
  • Ichord RN, Johnston MV, Traystman RJ. MK801 decreases glutamate release and oxidative metabolism during hypoglycemic coma in piglets. Brain Res Dev Brain Res. 2001;128:139–148. [PubMed]
  • Jang L-S, Ito Y, Akaike N. Feed forward facilitation of glutamate release by presynaptic GABAA receptors. Neuroscience. 2005;135:737–748. [PubMed]
  • Jueptner M, Weiller C. Does measurement of regional cerebral blood flow reflect synaptic activity? – Implications for PET and fMRI. NeuroImage. 1995;2:148–156. [PubMed]
  • Kasischke KA, Vishwasrao HD, Fisher PJ, Zipfel WR, Webb WW. Neural activity triggers neuronal oxidative metabolism followed by astrocytic glycolysis. Science. 2004;305:99–103. [PubMed]
  • Kety SS. The general metabolism of the brain in vivo. In: Richter D, editor. Metabolism of the nervous system. Pergamon; London: 1957. pp. 221–237.
  • Klaidman LK, Leung AC, Adams JD. High-performance liquid chromatography analysis of oxidized and reduced pyridine dinucleotides in specific brain regions. Analyt Biochem. 1995;228:312–317. [PubMed]
  • Knull HR. Association of glycolytic enzymes with particulate fractions from nerve endings. Biochim Biophys Acta. 1978;522:1–9. [PubMed]
  • Koch H, et al. Prostaglandin E2-induced synaptic plasticity in neocortical networks of organotypic slice cultures. J Neurosci. 2010;30:11678–11687. [PubMed]
  • Lecoq J, Tiret P, Najac M, Shepherd GM, Greer CA, Charpak S. Odor-evoked oxygen consumption by action potential and synaptic transmission in the olfactory bulb. J Neurosci. 2009;29:1424–1433. [PMC free article] [PubMed]
  • Leutgeb JK, Leutgeb S, Moser M-B, Moser EI. Pattern separation in the dentate gyrus and CA3 of the hippocampus. Science. 2007;315:961–966. [PubMed]
  • Li J, Iadecola C. Nitric oxide and adenosine mediate vasodilation during functional activation in cerebellar cortex. Neuropharmacol. 1994;33:1453–1461. [PubMed]
  • Lin AL, Fox PT, Hardies J, Duong TQ, Gao JH. Nonlinear coupling between cerebral blood flow, oxygen consumption, and ATP production in human visual cortex. Proc Natl Acad Sci USA. 2010;107:8446–8451. [PubMed]
  • Lipton P, Robacker K. Glycolysis and brain function: [K+]o stimulation of protein synthesis and K+ uptake require glycolysis. Fed Proc. 1983;42:2875–2880. [PubMed]
  • Lu M, Holliday LS, Zhang L, Dunn WA, Gluck SL. Interaction between aldolase and vacuolar H+-ATPase: evidence for direct coupling of glycolysis to the ATP-hydrolyzing proton pump. J Biol Chem. 2001;276:30407–30413. [PubMed]
  • Madsen PL, Cruz NF, Sokoloff L, Dienel GA. Cerebral oxygen/glucose ratio is low during sensory stimulation and rises above normal during recovery: excess glucose consumption during stimulation is not accounted for by lactate efflux from or accumulation in brain tissue. J Cereb Blood Flow Metab. 1999;19:393–400. [PubMed]
  • Magistretti PJ, Pellerin L, Rothman DL, Shulman RG. Energy on demand. Science. 1999;283:496–497. [PubMed]
  • Malonek D, Grinvald A. Interactions between electrical activity and cortical microcirculation revealed by imaging spectroscopy: implications for functional brain mapping. Science. 1996;272:551–554. [PubMed]
  • Mangia S, DiNnuzzo M, Giove F, Carruthers A, Simpson IA, Vannucci SJ. Response to ‘comment on recent modeling studies of astrocyte-neuron metabolic interactions’: much ado about nothing. J Cereb Blood Flow Metab. 2011;31:1346–1353. [PMC free article] [PubMed]
  • Martin-Requero A, Ayuso MS, Parrilla R. Interaction of oxamate with the gluconeogenic pathway in liver. Arch Biochem Biophys. 1986a;246:114–127. [PubMed]
  • Martin-Requero A, Ayuso MS, Parrilla R. Rate-limiting steps for hepatic gluconeogenesis. Mechanism of oxamate inhibition of mitochondrial pyruvate metabolism. J Biol Chem. 1986b;261:13973–13978. [PubMed]
  • Mathiesen C, Caesar K, Thomsen K, Hoogland TM, Witgen BM, Brazhe A, Lauritzen M. Activity-dependent increases in local oxygen consumption correlate with postsynaptic currents in the mouse cerebellum in vivo. J Neurosci. 2011;31:18327–18337. [PubMed]
  • Mercer RW, Dunham PB. Membrane-bound ATP fuels the Na/K pump. Studies on membrane-bound glycolytic enzymes on inside-out vesicles from human red cell membranes. J Gen Physiol. 1981;78:547–568. [PMC free article] [PubMed]
  • Offenhauser N, Thomsen K, Caesar K, Lauritzen M. Activity induced tissue oxygenation changes in rat cerebellar cortex: interplay of postsynaptic activation and blood flow. J Physiol. 2005;565:279–294. [PubMed]
  • Ogawa S, Lee RM, Barrere B. The sensitivity of magnetic resonance image signals of a rat brain to changes in the cerebral venous blood oxygenation. Magn Reson Med. 1993;29:205–210. [PubMed]
  • Paul RJ, Bauer M, Pease W. Vascular smooth muscle: aerobic glycolysis linked to sodium and potassium transport processes. Science. 1979;206:1414–1416. [PubMed]
  • Paul RJ, Hardin CD, Raeymaekers L, Wuytack F, Casteels R. Preferential support of Ca2+ uptake in smooth muscle plasma membrane vesicles by an endogenous glycolytic cascade. FASEB J. 1989;3:2298–301. [PubMed]
  • Pellerin L, Magistretti PJ. Glutamate uptake into astrocytes stimulates aerobic glycolysis: a mechanism coupling neuronal activity to glucose utilization. Proc Natl Acad Sci USA. 1994;91:10625–10629. [PubMed]
  • Pellerin L, Magistretti PJ. Sweet sixteen for ANLS. J Cereb Blood Flow Metab. 2011 doi: 10.1038/jcbfm.2011.149. [Epub ahead of print] [PMC free article] [PubMed]
  • Pellerin L, et al. Activity-dependent regulation of energy metabolism by astrocytes: an update. Glia. 2007;55:1251–1262. [PubMed]
  • Prins ML. Cerebral metabolic adaptation and ketone metabolism after brain injury. J Cereb Blood Flow Metab. 2008;28:1–16. [PMC free article] [PubMed]
  • Rei R. Measurement of aspartate aminotransferase activity: effects of oxamate. Clin Chem. 1979;25:555–559. [PubMed]
  • Schurr A, Gozal E. Aerobic production and utilization of lactate satisfy increased energy demands upon neuronal activation in hippocampal slices and provide neuroprotection against oxidative stress. Front Pharmacol. 2011;2:96. [PMC free article] [PubMed]
  • Schurr A, Payne RS. Lactate, not pyruvate, is neuronal aerobic glycolysis end product: an in vitro electrophysiological study. Neuroscience. 2007;147:613–619. [PubMed]
  • Shimizu H, et al. Glial Nax channels control lactate signaling to neurons for brain [Na+] sensing. Neuron. 2007;54:59–72. [PubMed]
  • Sokoloff L. The metabolism of the central nervous system in vivo. In: Field J, Magoun HW, Hall VE, editors. Handbook of Physiology, Section I, Neurophysiology. vol. 3. American Physiological Society; Washington D.C.: 1960. pp. 1843–1864.
  • Sokoloff L, et al. The [14C]deoxyglucose method for the measurement of local cerebral glucose utilization: theory, procedure, and normal values in the conscious and anesthetized albino rat. J Neurochem. 1977;28:897–916. [PubMed]
  • Song Z, Routh VH. Differential effects of glucose and lactate on glucosensing neurons in the ventromedial hypothalamic nucleus. Diabetes. 2005;54:15–22. [PubMed]
  • Suzuki A, et al. Astrocyte-neuron lactate transport is required for long-term memory formation. Cell. 2011;144:810–823. [PMC free article] [PubMed]
  • Territo PR, Mootha VK, French SA, Balaban RS. Ca2+ activation of heart mitochondrial oxidative phosphorylation: role of the FoF1-ATPase. Am J Physiol Cell Physiol. 2000;278:C423–435. [PubMed]
  • Thompson JK, Peterson MR, Freeman RD. Single-neuron activity and tissue oxygenation in the cerebral cortex. Science. 2003;299:1070–1072. [PubMed]
  • van Stroe AJ, Janssen LJJ. Determination of the diffusion coefficient of oxygen in sodium chloride solutions with a transient pulse technique. Analyt Chim Acta. 1993;279:213–219.
  • Wu M. Multiparameter metabolic analysis reveals a close link between attenuated mitochondrial bioenergetic function and enhanced glycolysis dependency in human tumor cells. Am J Physiol. 2007;292:C126–136. [PubMed]
  • Zhu X-H, Zhang Y, Zhang N, Ugurbil K, Chen W. Noninvasive and three-dimensional imaging of CMRO2 in rats at 9.4 T: reproducibility test and normothermia/ hypothermia comparison study. J Cereb Blood Flow Metab. 2007;27:1225–1234. [PubMed]