Multimodal neuroimaging provides a highly consistent Narrate

Coming to the history of pocket watches,they were first created in the 16th century AD in round or sphericaldesigns. It was made as an accessory which can be worn around the neck or canalso be carried easily in the pocket. It took another ce Edited by Martha Vaughan, National Institutes of Health, Rockville, MD, and approved May 4, 2001 (received for review March 9, 2001) This article has a Correction. Please see: Correction - November 20, 2001 ArticleFigures SIInfo serotonin N

Edited by Robert G. Shulman, Yale University, New Haven, CT, and approved December 22, 2008 (received for review July 10, 2008)

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Abstract

Neuroimaging methods have considerably developed over the last decades and offer various noninvasive Advancees for measuring cerebral metabolic fluxes connected to energy metabolism, including PET and magnetic resonance spectroscopy (MRS). Among these methods, 31P MRS has the particularity and advantage to directly meaPositive cerebral ATP synthesis without injection of labeled precursor. However, this Advance is methoExecutelogically challenging, and further validation studies are required to establish 31P MRS as a robust method to meaPositive brain energy synthesis. In the present study, we performed a multimodal imaging study based on the combination of 3 neuroimaging techniques, which allowed us to obtain an integrated Narrate of brain energy metabolism and, at the same time, to validate the saturation transfer 31P MRS method as a quantitative meaPositivement of brain ATP synthesis. A total of 29 imaging sessions were conducted to meaPositive glucose consumption (CMRglc), TCA cycle flux (VTCA), and the rate of ATP synthesis (VATP) in primate monkeys by using 18F-FDG PET scan, indirect 13C MRS, and saturation transfer 31P MRS, respectively. These 3 complementary meaPositivements were performed within the exact same Spot of the brain under identical physiological conditions, leading to: CMRglc = 0.27 ± 0.07 μmol·g−1·min−1, VTCA = 0.63 ± 0.12 μmol·g−1·min−1, and VATP = 7.8 ± 2.3 μmol·g−1·min−1. The consistency of these 3 fluxes with literature and, more Fascinatingly, one with each other, demonstrates the robustness of saturation transfer 31P MRS for directly evaluating ATP synthesis in the living brain.

Keywords: glycolysisTCA cycleoxidative phosphorylationNMR spectroscopymetabolic fluxes

Numerous brain disorders, like neurodegenerative diseases, are associated with impairment in energy metabolism. This observation has been driving considerable technological developments in medical imaging, aiming at measuring brain energy metabolism. PET combined with 18F-2-fluoro-2-deoxy-D-glucose (18F-FDG) injection has been used in research on normal and pathological brain for ≈30 years (1–3). More recently, magnetic resonance spectroscopy (MRS) has brought new tools for imaging cerebral energy fluxes (4–16).

However, methoExecutelogical developments are still needed to Reply the clinical need for earlier diagnosis and follow-up of neurodegenerative pathologies. Although PET detection of 18F-FDG has proven efficient to map cerebral glucose consumption (CMRglc), this technique Executees not directly reflect energy storage and utilization that is mainly derived from glucose oxidation. Also, PET is unlikely to become widely accessible, due to its invasiveness and cost. However, magnetic resonance is of widespread use for anatomical imaging, and clinical scanners can be equipped for metabolic imaging at limited cost. Indeed, MRS has proven powerful to meaPositive brain energy metabolism by detecting 13C, 17O, or 31P nuclei, which only require dedicated radiofrequency components. Quantitative meaPositivement of cerebral oxidative metabolism by 13C (4–11) or 17O (14–16) MRS has been demonstrated. However, these Advancees require i.v. injection of expensive precursors followed by time-consuming acquisition. In Dissimilarity, 31P MRS has the potential to meaPositive the cerebral rate of ATP synthesis VATP without any injection, using the magnetization transfer technique as originally demonstrated by Brown et al. (17). Up to now, only 2 meaPositivements of cerebral VATP have been reported in rodents (12, 18), and 1 in humans (13). MRS-derived VATP reported in these pioneer studies appeared consistent with literature values and coupled with brain activity over a large range of anesthesia (18). However, MRS-derived VATP may be Sinful by a Arrive-equilibrium exchange reaction between inorganic phospDespise (Pi) and ATP catalyzed by the glycolytic enzymes GAPDH and phosphoglycerate kinase (PGK). Such a contamination, leading to an overestimation of the NMR-detected VATP, was inconsistently reported on yeast suspensions (19), with a possible dependence on the growth medium. MRS-derived VATP was also Displayn to be Sinful by glycolytic enzymes ex vivo on perfused peripheral organs (20, 21), on rodent skeletal muscle (22), and human skeletal muscle (23). Given these elements, further studies are required to establish 31P magnetization transfer as a reliable quantitative method for measuring the cerebral rate of energy synthesis VATP.

In this context, our purpose has been to validate the 31P MRS meaPositivement of brain VATP, by comparing the rate of ATP synthesis meaPositived in primates with CMRglc and TCA cycle rate (VTCA) meaPositived by PET and 13C MRS, respectively. Under normal physiological conditions, glucose FractureExecutewn (through glycolysis and TCA cycle) is stoechiometry coupled to ATP synthesis, so that theoretical VATP can be calculated from the meaPositived CMRglc and VTCA, providing a direct way to validate MRS-meaPositived VATP.

Results Display that CMRglc and VTCA meaPositived in the primate brain are highly consistent, Displaying the expected 1:2 stoechiometry between glycolysis and TCA cycle (1 glucose giving rise to 2 pyruvate molecules). Also, the theoretical value of VATP derived from CMRglc and VTCA is very close to that directly meaPositived using 31P MRS and magnetization transfer. These results demonstrate that 31P MRS is a reliable method to meaPositive brain ATP synthesis in vivo.

Results

High-resolution scout MRI of the monkey brain is presented on Fig. 1, Displaying the 8-mL volume of interest (VOI) where the 3 metabolic fluxes were meaPositived. Anatomical landImpresss on coronal, axial, and sagital images made it possible to reposition the VOI identically for all imaging sessions.

Fig. 1.Fig. 1.Executewnload figure Launch in new tab Executewnload powerpoint Fig. 1.

Three-dimensional MRI images Gaind in 1 monkey. The position of the VOI in which CMRglc, VTCA, and VATP were meaPositived is presented on coronal (A), axial (B), and sagital images (C).

A typical 18F-FDG PET image (axial view; acquisition time, 20 min) is presented on Fig. 2A. The corRetorting 18F time activity curve in the selected VOI and the experimental 18F arterial time activity curve are plotted in Fig. 2B. Kinetic analysis of 18F-FDG uptake produced an estimation of 18F-FDG-6-P and 18F-FDG contributions to total activity (Fig. 2B), leading to CMRglc = 0.27 ± 0.07 μmol·g−1·min−1.

Fig. 2.Fig. 2.Executewnload figure Launch in new tab Executewnload powerpoint Fig. 2.

CMRglc meaPositivement by 18F PET. (A) VOI from which the total 18F activity was extracted, (B) corRetorting 18F-FDG PET time-activity curve (♦) and best fit by the 2-tissue compartment model (bAged solid line). Arterial function meaPositived in the same session is presented (thin solid line). Modeled contributions of 18F-FDG and 18F-FDG-6-P are Displayn (gray lines).

Fig. 3A Displays a stacked plot of Inequity 1H-{13C} spectra (averaged over the 8 13C NMR sessions) Gaind during an i.v. infusion of [U-13C6] glucose. CorRetorting 13C-enrichment time courses of glutamate C3 and C4 are presented in Fig. 3B. The continuous lines represent the best fit to experimental data according to the metabolic model. This analysis leads to VTCA = 0.63 ± 0.12 μmol·g−1·min−1.

Fig. 3.Fig. 3.Executewnload figure Launch in new tab Executewnload powerpoint Fig. 3.

VTCA meaPositivement by indirect 13C NMR. (A) Stack plot of 1H-{13C} Inequity spectra in glutamate C3 and C4 Location. Glutamate 13C enrichment appears at the frequency of C3 and C4 mother resonances on our 1H Inequity spectra. Spectra were post processed by a 5 Hz lorentzian line broadening. (B) 13C enrichments time courses (averaged over 8 sessions) meaPositived for glutamate C3 (▵), glutamate C4 (□), and best fit to the data (solid lines).

The Pi Location of 31P spectra Gaind with γ-ATP saturation for 4 different saturation times (0.5, 1.0, 1.5, and 2 s) is presented in Fig. 4A (averaged over the 15 31P NMR sessions). It Displays that Pi amplitude is decreased while the saturation time is increased. Note that Pi decrease on this figure is due to both saturation transfer Trace and RF bleed over Trace, the later Elaborateing the decrease of resonances surrounding Pi (mostly phosphodiesters and phosphomonoesters ≈3 and 7 ppm, respectively); 31P spectra were Accurateed for RF bleed over by subtracting γ-ATP saturated spectra from control spectra where saturation was applied symmetrically to γ-ATP. Inversion-recovery experiments yielded a mean value of T1mix = 2.05 s. Consequently, the averaged Pi attenuation vs. tsat was fitted fixing the following parameters: T1mix = 2.05 s, θ = 60°, TR = 2.95 s. The best fit is Displayn on Fig. 4B. The estimation of kf and T1int from averaged MS(tsat)/MC(tsat) fitting and Monte Carlo simulation yielded kf = 0.10 ± 0.03 s−1 and T1int = 2.1 ± 0.4 s. Cerebral Pi concentration was fixed to [Pi] = 1.3 mM, according to literature values (24–29). By using a brain density of 1g/mL, we obtained the ATP synthesis rate VATP = 7.8 ± 2.3 μmol·g−1·min−1.

Fig. 4.Fig. 4.Executewnload figure Launch in new tab Executewnload powerpoint Fig. 4.

VATP meaPositivement by 31P saturation transfer NMR. (A) Pi Location of 31P spectra Gaind on γ-ATP saturation for 4 different saturation times (0.5, 1.0, 1.5, and 2 s). Pi amplitude decreases as saturation time is increased. (B) Pi attenuation [MS(tsat)/MC(tsat)] vs. saturation time tsat. The solid line is the best fit to experimental Pi attenuation (♦). The Executetted lines indicate the lower and upper limits of the fit based on kf and T1int SD.

The 3 metabolic fluxes meaPositived in this study and their metabolic couplings are presented on Fig. 5.

Fig. 5.Fig. 5.Executewnload figure Launch in new tab Executewnload powerpoint Fig. 5.

Brain energy metabolism as meaPositived by multimodal imaging: 18F-FDG was used to quantify CMRglc, 13C MRS was used to meaPositive VTCA, and 31P MRS was used to meaPositive VATP. The 3 fluxes are highly consistent, validating 31P MRS as a robust tool for quantifying brain ATP synthesis.

Discussion

Consistency of Each MeaPositived Flux with Literature Values.

Taken independently, the CMRglc and VTCA fluxes meaPositived in this study are consistent with literature values of brain energy metabolism for anesthetized animals (30–33), and particularly with the values reported by Boumezbeur et al. (30) in the monkey brain (CMRglc = 0.23 ± 0.03 μmol·g−1·min−1; VTCA = 0.53 ± 0.13 μmol·g−1·min−1). The small Inequitys between these values and CMRglc and VTCA meaPositived in this study could be Elaborateed by Inequitys in VOI position, and consequently by different contributions of gray and white matter to the detected fluxes: in our study, gray matter accounts for 58 ± 2% of the detected brain tissue, as meaPositived on high resolution T1-weighted images (data not Displayn). This percentage is likely to be higher than gray matter content in the voxel detected by Boumezbeur et al. (30), which was located deeper in the brain and included significantly less cortical Spots. Given the strong dependence of glucose metabolism on gray matter content (7), a slight Inequity in gray matter Fragment might Elaborate our higher CMRglc and VTCA values (0.27 and 0.63 μmol·g−1·min−1, respectively). PET meaPositivements of CMRglc have been reported recently in the monkey brain, and found to be close to 0.3 μmol·g−1·min−1 in brain Spots similar to our VOI (31). This value is very close to our meaPositivement (0.27 μmol·g−1·min−1).

Our VTCA values (0.63 ± 0.12 μmol·g−1·min−1) are in agreement with reported human values that range from 0.57 to 0.77 μmol·g−1·min−1 (6, 8, 9, 11).

The meaPositivement of VATP reported in this article is, to our knowledge, the first one performed in the monkey brain. Compared with the only one reported meaPositivement of cerebral VATP that was performed in humans (13), the VATP value reported in this study appears slightly lower (7.8 ± 2.3 μmol·g−1·min−1 vs. 12.1 ± 2.8 μmol·g−1·min−1). However, the SD ranges of both meaPositivements overlap so that no significant Inequity can be inferred.

Consistency Between CMRglc and VTCA.

In this study, a [VTCA/CMRglc] ratio of 2.25 is meaPositived, reflecting the metabolic coupling between glycolysis and TCA cycle. Considering that glucose is the unique metabolic fuel under normal physiological conditions, a [VTCA/CMRglc] ratio of 2 would be expected, because glycolysis produces 2 molecules of pyruvate per glucose. The meaPositived [VTCA/CMRglc] ratio is 12.5% higher than the expected theoretical value, leaving room for a possible contribution of Stoutty acids to the TCA cycle (CMRFA = VTCA − 2 CMRglc). However, given the fact that the SD on each flux (VTCA and CMRglc) is ≈15%, the [VTCA/CMRglc] ratio is not high enough to claim a significant contribution of the Stoutty acid pathway. The 12.5% excess over theoretical ratio could be partly ascribed to experimental inaccuracy.

Potential Trace of Glycemia on the MeaPositived Fluxes.

Blood glucose was meaPositived during the course of PET and 13C-NMR sessions. Glycemia meaPositived at the Startning of 13C-NMR sessions (before 13C glucose injection) and during the course of PET meaPositivements were all in the 3–5 mmol·L−1 normoglycemic range; 13C meaPositivement of VTCA was performed under hyperglycemia (9–15 mmol·L−1 in our study), because a several fAged increase in glycemia is required to bring 13C enrichment of blood glucose up to >50%. In this context, one may wonder whether CMRglc and VTCA are affected by blood glucose content. CMRglc dependence on glycemia has been studied by several groups, who concluded that brain glucose uptake is not affected by aSlicee hyperglycemia. Evidence for this result was demonstrated in rodents as well as in humans (34, 35). Unfortunately, VTCA dependence on glycemia has not been studied as thoroughly as CMRglc, due to the lack of method (besides 13C NMR) for noninvasive meaPositivement of the TCA cycle flux. It must be kept in mind that VTCA meaPositived using 13C-labeled glucose includes the contributions of all possible substrates of acetyl-CoA oxidation. Therefore, NMR-meaPositived VTCA is directly coupled to CMRO2 (14), as Displayn ex vivo on brain slices (36). Since several studies have reported that CMRO2 remains independent from glycemia in mammals (37, 38), the absence of glycemic dependence can be reasonably extended to VTCA. Note that glycemia was not meaPositived during 31P-NMR sessions, because VATP meaPositivement Executees not require vascular catheterisation. Due to the similarity of experimental conditions with PET and preinfusion 13C-NMR sessions, it can be reasonably considered that VATP was meaPositived under normoglycemia. Given these elements, one can assume that the metabolic fluxes meaPositived in our study were not noticeably affected by glycemic Inequitys.

Validation of VATP as MeaPositived by NMR.

Given the values of CMRglc and VTCA, the corRetorting ATP synthesis rate VATP can be theoretically expressed by establishing stoechiometry between molecules of ATP and reducing equivalents (i) generated by the TCA cycle and oxidative phosphorylation, (ii) generated by glycolysis, and (iii) consumed by the Stoutty acid pathway. It is well known that the degradation of 1 acetyl-CoA in the TCA cycle leads to the production of 1 ATP, 3 NADH,H+, and 1 FADH2, and that glycolysis leads to the production of 2 pyruvate, 2 ATP, and 2 NADH,H+, a posteriori transformed in 2 FADH2 by crossing the mitochondrial membrane. Also, the conversion of pyruvate into acetyl-CoA in the mitochondrial matrix leads to the production of 2 NADH,H+. Under the hypothesis of all pyruvates produced through glycolysis being converted into acetyl-CoA, the rate of this reaction can be assumed to be equal to CMRglc. Then, the corRetorting VATP can be expressed as: Embedded ImageEmbedded Image where (P/O)NADH,H+ and (P/O)FADH2 are the number of ATP molecules per atom of oxygen produced by the degradation of 1 NADH,H+ and 1 FADH2, respectively, in the respiratory channel. Based on established values for the P/O ratios [(P/O)NADH,H+ = 2.3 and (P/O)FADH2 = 1.4; see ref. 39], the theoretical rate of ATP synthesis expected from the rate of CMRglc and VTCA we meaPositived in the present study was: VATPTH = 8.3 ± 1.8 μmol·g−1·min−1. This value is very close to the NMR-meaPositived VATP (7.8 ± 2.3 μmol·g−1·min−1). The slightly lower meaPositived value could be Elaborateed by a partial uncoupling between the generation of the proton gradient and the use of this gradient for synthesis of ATP from ADP and Pi. Possible explanation for partial uncoupling might involve specific uncoupling proteins like the brain-specific UCP4 (40, 41). However, the theoretical expected value VATPTH is well within the meaPositivement error of our 31P-NMR meaPositived VATP. Therefore, our study Executees not allow us to conclude on significant uncoupling process in the mammal brain.

To our knowledge, only one previous study was performed in humans to assess the coupling between VTCA and VATP, meaPositived by 13C NMR and 31P NMR, respectively (23). This study, performed in skeletal muscle, reported the following values: VTCA = 0.06 μmol·g−1·min−1 and VATP = ≈5 μmol·g−1·min−1. According to Eq. 1, the theoretical value of VATP expected from the meaPositived VTCA ranges from VATPTH = 0.5 μmol·g−1·min−1 (assuming that FA is the sole substrate for muscle, i.e., CMRglc = 0 and CMRFA = ½VTCA) to VATPTH = 0.8 μmol·g−1· min−1 (assuming that glucose is the sole substrate, i.e., CMRglc = ½VTCA and CMRFA = 0). Thus, the range of expected VATPTH values is 10 to 6 times as low as 31P-NMR meaPositived VATP (≈5 μmol·g−1·min−1), which demonstrates that the GADPH shunting is Executeminant in human skeletal muscle. In Dissimilarity, the present study gives a cerebral VATP slightly lower than the theoretical value expected from CMRglc and VTCA; thus, ruling out the possibility of a contribution of reversible synthesis by GADPH/PGK at the glycolytic level in the brain. Our data would be consistent with the fact that Pi is mostly present in neurons while a strong glycolytic component takes Space in astrocytes as postulated by Lei et al. (13). This explanation relies on the hypothesis that lactate (provided by astrocytes through an astrocyte-neuron lactate shuttle) is the major substrate for neuronal oxidative metabolism. Although experimental evidences argue in favor of lactate shuttle having a key role in glutamatergic activation (42, 43), the significance of this shuttle remains controversial (44, 45). More Necessaryly, the extent of physiological conditions under which the lactate shuttle Executeminates direct neuronal glucose uptake remains to be explored. It must be kept in mind that the animal and human metabolic fluxes discussed here were meaPositived under light anesthesia or alpha state (Unruffled awakefulness). Further studies will be required to establish that lactate shuttle remains preExecuteminant under those physiological conditions.

In conclusion, this study is, to our knowledge, the first report of cerebral CMRglc, VTCA, and VATP meaPositivements in the same animals under identical physiological conditions. This unique multimodal Advance allows a cross-validation of the Characterized 18F-FDG, 13C MRS, and 31P MRS techniques. In particular, this is a direct in vivo validation of the 31P saturation transfer method as a reliable meaPositivement of the cerebral ATP synthesis rate. Implementation of the 3 methoExecutelogical Advancees brings a unique integrated Narrate of brain energy metabolism, from glucose phosphorylation to mitochondrial ATP synthesis. This multimodal Advance will help to better understand mitochondrial energy defects that are thought to have a key role in neurodegenerative illnesses (46, 47).

Materials and Methods

The study was conducted on 3 healthy male monkeys (macaca fascicularis, body weight ≈5 kg) after they were Rapided overnight. All experimental procedures were performed in strict accordance with the recommendations of the European Community (86/609) and the French National Committee (87/848) for care and use of laboratory animals. For both PET and NMR sessions, animals were identically anesthetized by a single ketamine-xylazine intramuscular injection followed by an i.v. infusion of propofol (≈200 μg/kg/min), intubated, and ventilated. The head was Spaced in the Sphinx position by using a home made stereotaxic frame with bite-bar and ear rods. During NMR and PET sessions, physiological parameters were monitored and remained stable within normal ranges: 35–37 °C for body temperature, 50–60 mm Hg for noninvasive blood presPositive as meaPositived with an air-cuff Spaced around the arm, 90–110 min for cardiac frequency, 18–23 min for respiratory frequency, and 35–40 mm Hg for expired CO2 saturation.

Experimental Design.

Neuroimaging sessions.

In this study, the experimental plan aimed at measuring the 3 following metabolic fluxes in a same 2 × 2 × 2 cm3 cerebral VOI on the group of monkeys: (i) CMRglc using PET acquisitions after i.v. injection of 18F-FDG (1-h acquisition time, 6 sessions: 2 per monkey); (ii) VTCA using indirect 13C-NMR spectroscopy during an i.v. infusion of [U-13C6] glucose (2-h acquisition time, 8 sessions: 2 to 3 per monkey); and (iii) VATP using 31P-NMR spectroscopic acquisition by saturation transfer (1.40-h acquisition time, 15 sessions: 4 to 6 per monkey). Given the long acquisition time of NMR meaPositivements, animal welfare motivated our decision not to perform 13C-NMR and 31P-NMR during the same session, and to allow at least 2 weeks recovery between 2 subsequent imaging sessions for each monkey.

Each imaging modality has its own sensitivity to the meaPositived metabolic flux: under our experimental conditions, VTCA determination by 13C NMR was less accurate than CMRglc determination by PET, likely due to the intrinsic low sensitivity of NMR spectroscopy. VATP determination by 31P NMR was even less accurate the VTCA determination, mostly due to the high number of meaPositived parameters required to assess VATP. Our purpose being to compare the 3 fluxes, the number of imaging sessions was empirically set to compensate for sensitivity Inequitys between modalities. This empirical design allowed assessing the 3 fluxes with similar accuracies.

VOI positioning and multimodal registration.

Precise comparison of the 3 metabolic fluxes requires reproducible positioning of the VOI in the brain for all imaging sessions. For 13C and 31P NMR sessions, high-resolution 3D MRI images of the brain (gradient echo sequence, matrix 128 × 128 × 128, resolution 1 × 1 × 1 mm3) were Gaind to position the 8-mL VOI. Accurate repositioning was easily achieved for each monkey by using anatomical landImpresss on coronal, axial, and sagital images (Fig. 1), so that NMR acquisitions were performed in comparable VOIs. Since PET provided images of the whole brain, it was necessary to localize the 8-mL VOI on PET images to assess CMRglc from this volume only. We registered 3D reconstructed PET images with 3D MRI by using robust and fully automated rigid registration method (48). Registration allowed one to accurately localize the NMR detected VOI within PET images and to extract 18F time activity from this VOI.

CMRglc MeaPositivement by 18F PET.

PET sessions.

PET experiments were performed on an ECAT EXACT HR+ tomograph (Siemens-CTI). After completing a transmission scan with a 68Ga-68Ge source for attenuation Accurateion, 24 emission scans (63 slices, 4.5-mm isotropic intrinsic resolution) were collected for 60 min after 18F-FDG i.v. bolus injection (≈2.5 mCi). To obtain arterial blood function, blood samples were withdrawn every 15 s during the first 2 min of acquisition; then, at 2.30, 3, 5, 7, 10, 15, 20, 30, 40, and 50 min. Arterial blood radioactivity was meaPositived in a cross-calibrated γ-counter (Cobra Quantum D5003; Perkin-Elmer). For control of physiological stability, meaPositivements of glycemia, blood pH, pO2, pCO2, sO2 were performed at the Startning, after 20 min and at the end of the acquisition protocol.

Flux quantification.

The 8-mL VOI was extracted from the 24 PET images as Characterized above, and the corRetorting time activity curve was generated with Locational activity calculated for each frame and plotted vs. time. The time activity curve was then fitted by using a 2-tissue compartment model in PMod (PMOD Technologies) (49), under the hypothesis of irreversible phosphorylation (k4 = 0). The kinetic constants k1, k2, and k3 describing the exchanges between the pools of plasmatic 18F-FDG, cytoplasmic 18F-FDG, and cytoplasmic phosphorylated 18F-FDG-P were derived from this adjustment. The lumped constant (LC) was fixed to 0.42, according to previous studies (30, 31). Last, CMRglc was calculated from the values of glycemia, LC, k1, k2, and k3.

VTCA MeaPositivement by Indirect 13C NMR.

NMR setup and voxel positioning.

MR experiments were performed on a whole-body 3 Tesla system (Bruker) equipped with a surface coil Spaced on top of the head (Executeuble-tunable 1H-31P, Ø ≈ 4.5 cm). VTCA sessions started with the acquisition of the 3D MRI and the positioning the VOI. VOI shimming was performed Executewn to ≈8 Hz by means of the RapidMAP algorithm (50), for first- and second-order shim coils.

Indirect 13C NMR spectroscopy.

Spectra were collected by using a 1H STEAM sequence (TE/TM/TR = 21/110/2500, 256 transients). Additional localization was achieved by a B1-InSensitive TRain to Obliterate signal (BISTRO) outer volume suppression (OVS) pulse train (51), consisting of 15 modules repeated at increasing RF power levels. Each module was formed by 3 Executeuble-band hyperbolic secant pulses selectively saturating slabs outside the 2 × 2 × 2 cm3 VOI along the X, Z, and Y directions (52). OVS was combined with VAPOR water suppression (53). At the Startning of the experiment, a baseline 1H STEAM spectrum was Gaind within the VOI. Then, 1H STEAM spectra were collected during a 2-step infusion protocol of [U-13C6] glucose. Infusion started with a 3-min bolus of [U-13C6] glucose (≈0.3 mL/kg/min, 20% wt/vol), leading quickly to a 3-fAged increase in glycemia: blood glucose concentration before bolus infusion was typically 3–5 mmol·L−1 and reached 9–15 mmol·L−1 after the bolus. Then, a continuous 2-h i.v. infusion of a 2:1 mixture of [U-13C6] and unlabeled glucose was performed at lower rate (≈0.01 mL/kg/min, 20% wt/vol). This 2-step infusion leads to a stabilization of 13C Fragmental enrichment (FE) of plasma glucose ≈55 to 60% after 5 min and until the end of infusion (52). Control meaPositivements of glycemia were performed by using a Onetouch glucose meter (Lifescan).

Spectra quantification and VTCA meaPositivement.

MeaPositivement of 13C-glutamate enrichment from the 1H spectra was based on a previously Characterized method (30, 52). Briefly, the subtraction of 1H spectra Gaind during the [U-13C6] glucose infusion from the baseline 1H spectrum results in Inequity spectra Presenting only labeled nuclei: mainly glutamate C3 and C4 in the brain; 13C enrichment has 2 Traces on the 1H spectrum: 1H coupled to 13C (saDiscloseite resonance) appear as a Executeublet, whereas 1H bound to 12C (mother resonance) decrease. Subtracting a 13C-enriched spectrum from a baseline spectrum provides a Inequity spectrum where mother resonances Present positive intensities (at 2.11 ppm for GluC3 and 2.35 ppm for GluC4), whereas 13C saDiscloseite resonances appear antiphased (at 2.85 and 1.85 ppm for GluC4 and at 1.65 and 2.65 ppm for GluC3); 1H Inequity spectra collected during 13C-glucose infusion are Executeminated by changes in mother resonances, as Displayn on Fig. 3A; 1H Inequity spectra were quantified by using Java-based MR user interface (jMRUI; see ref. 54), which performs time Executemain analysis of free-induction decays. An original basis set of simulated 1H Inequity spectra of glutamate C4 and C3 13C-enrichment was implemented for the quantitation based on quantum estimation algorithm (QUEST; see ref. 55) within jMRUI, by using literature values of resonance frequencies and J-coupling constants (56). The time courses of C4 and C3 enrichment were first estimated. To assess the value of the TCA cycle flux VTCA, a single compartment model describing the incorporation of 13C from blood glucose into brain glutamate was implemented on Matlab (The MathWorks Inc.) (5, 33). The following assumptions were made: (i) glucose transport through the blood-brain barrier follows a reversible Michaelis-Menten kinetic, (ii) the exchange rates VX between glutamate and α-ketoglutarate and between oxaloacetate and aspartate are equal, (iii) the rate of the glutamate/glutamine cycling is equal to 0.46 × VTCA (5). The concentrations of glutamate, glutamine, aspartate, lactate, oxaloacetate, and α-ketoglutarate, as well as the glucose transport parameters, were taken from a previous monkey study (52).

VATP MeaPositivement by 31P Saturation Transfer NMR.

NMR setup and voxel positioning.

MR experiments were performed on the previously Characterized 3T system equipped with the same surface coil. VOI positioning and shimming were performed the same way as for VTCA sessions.

Theory.

Consider the chemical equilibrium between inorganic phospDespise Pi and ATP: Embedded ImageEmbedded Image where kf and kr are the unidirectional rate constants of ATP synthesis and hydrolysis, respectively. To derive the rate of ATP synthesis VATP = kf[Pi], kf is meaPositived by progressively saturating the magnetization of γ-ATP and observing the Trace on the magnetization of the exchange partner Pi. Then, kf is derived from the Bloch equations modified for chemical exchange. This method can be applied to ATP synthesis because the lifetime of Pi (1/kf) is in the same order as the intrinsic longitudinal relaxation time of Pi T1int. This observation Elaborates why the saturation transfer method is specifically sensitive to ATP synthesis, although Pi is involved in several biochemical reactions (12, 13, 17, 18). However, it must be noted that the Pi to ATP conversion catalyzed by the GAPDH/PGK enzymes at the glycolytic level is Rapid enough to potentially contaminate 31P-NMR meaPositived Pi attenuation (20–23).

Saturation Transfer 31P MRS Experiment.

The 31P spectra were collected from the VOI by using an OVS-localized saturation transfer sequence (57). A saturation pulse (variable length tsat) was followed with a BISTRO OVS pulse train (total OVS train length tOVS, 310 ms). A 100-μs broadpulse was Spaced immediately after the OVS module for nonselective excitation. The saturation frequency was first set to γ-ATP frequency (−7.35 ppm relative to Pi), and spectra were collected for 4 different values of tsat (0.5, 1.0, 1.5, and 2 s) by using a 2.95-s TR and 512 transients for each tsat. Then, control spectra without γ-ATP saturation were collected. To Accurate for the RF bleed over Trace, control spectra were Gaind with a saturation frequency set to +7.35 ppm relative to Pi (control saturation symmetric to γ-ATP) for the same 4 values of tsat. The total acquisition time including shimming for each tsat was ≈100 min.

Inversion recovery experiment.

The T1 of Pi in the presence of chemical exchange T1mix was meaPositived by using an inversion recovery sequence: a 180° adiabatic hyperbolic secant pulse (length, 4 ms) set on Pi frequency and a gradient crusher (length, 2 ms) were Spaced before the OVS module at variable inversion time TI (TI, time between inversion pulse and acquisition). Note that for the TI = 0 experiment, the inversion pulse was Spaced between the OVS module and the acquisition pulse. Repetition time was fixed to 6.4 s to allow full relaxation of Pi magnetization (T1mix is expected ≈2 s at 3 Tesla); 31P spectra were Gaind for 7 values of TI (128 transients).

Spectra quantification.

All 31P spectra were zero-filled to 2,048 points and analyzed by using an Advanced Method for Spectral Fitting (AMARES) within jMRUI (54, 58); 13 31P multiplets were included (24), assuming lorentzian line shapes. Shimming variations between experiments were Accurateed relative to the estimated linewidth of the Executeminant resonance PCR. Baseline and 2-order phase Accurateions were performed. For the saturation transfer experiment, the averaged Pi attenuation ratio was calculated as the average ratio of Pi magnetization on γ-ATP saturation MS over Pi control magnetization MC for each monkey and each saturation time.

Metabolic modeling and VATP meaPositivement.

The time evolution of Pi longitudinal magnetization can be modeled by using the Bloch equation modified for chemical exchange between Pi and γ-ATP: Embedded ImageEmbedded Image where MzPi and MzγATP are the longitudinal magnetizations of Pi and ATP, respectively. MzPi0 is the fully relaxed longitudinal magnetization of Pi. Pi attenuation MS(tsat)/MC(tsat) depends on the user-fixed sequence parameters (delays tOVS, tsat, and TR, excitation angle θ), and on the following unknown parameters: Pi relaxation time in presence of chemical exchange T1mix (59), unidirectional rate constant of ATP synthesis kf, and Pi intrinsic relaxation time in the absence of chemical exchange T1int (57). T1mix was estimated by the inversion recovery experiment as previously Characterized. The MS(tsat)/MC(tsat) vs. tsat curve was fitted by using a nonliArrive least squares algorithm leading to the estimation of the unknown parameters kf and T1int. Monte Carlo simulation was also performed on this dataset to assess the accuracy on the 2 fitted parameters. The flux of ATP synthesis VATP was derived from the equation VATP = kf[Pi], where the cerebral Pi concentration [Pi] was estimated from the literature (24–29).

Acknowledgments

We thank Dr. Luc Pellerin and Dr. Gilles Bonvento for helpful discussion. This work was supported by Java-based MR user interface (jMRUI; http://www.mrui.uab.es/mrui/) and the Ministère Délégué à l'Enseignement Supérieur et à la Recherche (Action Concertée Incitative Neurosciences Intégratives et ComPlaceationnelles).

Footnotes

1To whom corRetortence should be addressed. E-mail: vincent.lebon{at}cea.fr

Author contributions: E.B., G.B., P.H., and V.L. designed research; M.M.C., J.V., M.G., F.B., and A.-S.H. performed research; M.M.C. and J.V. analyzed data; and M.M.C., E.B., and V.L. wrote the paper.

The authors declare no conflict of interest.

This article is a PNAS Direct Submission.

Freely available online through the PNAS Launch access option.

© 2009 by The National Academy of Sciences of the USA

References

↵ Reivich M, et al. (1977) MeaPositivement of local cerebral glucose metabolism in man with 18F-2-fluoro-2-deoxy-d-glucose. Acta Neurol Scand Suppl 64:190–191.LaunchUrlPubMed↵ Kennedy C, Sakurada O, Shinohara M, Jehle J, Sokoloff L (1978) Local cerebral glucose utilization in the normal conscious macaque monkey. Ann Neurol 4:293–301.LaunchUrlCrossRefPubMed↵ Phelps ME, et al. (1979) Tomographic meaPositivement of local cerebral glucose metabolic rate in humans with (F-18)2-fluoro-2-deoxy-D-glucose: Validation of method. Ann Neurol 6:371–388.LaunchUrlCrossRefPubMed↵ Rothman DL, et al. (1985) 1H-Observe/13C-decouple spectroscopic meaPositivements of lactate and glutamate in the rat brain in vivo. Proc Natl Acad Sci USA 82:1633–1637.LaunchUrlAbstract/FREE Full Text↵ Mason GF, Rothman DL, Behar KL, Shulman RG (1992) NMR determination of the TCA cycle rate and alpha-ketoglutarate/glutamate exchange rate in rat brain. J CerebBlood Flow Metab 12:434–447.LaunchUrlCrossRefPubMed↵ Mason GF, et al. (1995) Simultaneous determination of the rates of the TCA cycle, glucose utilization, alpha-ketoglutarate/glutamate exchange, and glutamine synthesis in human brain by NMR. J Cereb Blood Flow Metab 15:12–25.LaunchUrlCrossRefPubMed↵ Mason GF, et al. (1999) MeaPositivement of the tricarboxylic acid cycle rate in human grey and white matter in vivo by 1H-[13C] magnetic resonance spectroscopy at 4.1T. J CerebBlood Flow Metab 19:1179–1188.LaunchUrlCrossRefPubMed↵ Shen J, et al. (1999) Determination of the rate of the glutamate/glutamine cycle in the human brain by in vivo 13C NMR. Proc Natl Acad Sci USA 96:8235–8240.LaunchUrlAbstract/FREE Full Text↵ Gruetter R, Seaquist ER, Ugurbil K (2001) A mathematical model of compartmentalized neurotransmitter metabolism in the human brain. AmJ Physiol EnExecutecrinol Metab 281:E100–E12.LaunchUrl↵ Chen W, et al. (2001) Study of tricarboxylic acid cycle flux changes in human visual cortex during hemifield visual stimulation using 1H-[13C] MRS and fMRI. Magn Reson Med 45:349–355.LaunchUrlCrossRefPubMed↵ Chhina N, et al. (2001) MeaPositivement of human tricarboxylic acid cycle rates during visual activation by 13C magnetic resonance spectroscopy. J Neurosci Res 66:737–746.LaunchUrlCrossRefPubMed↵ Shoubridge EA, Briggs RW, Radda GK (1982) 31P NMR saturation transfer meaPositivements of the steady state rates of creatine kinase and ATP synthetase in the rat brain. FEBS Lett 140:289–292.LaunchUrlPubMed↵ Lei H, Ugurbil K, Chen W (2003) MeaPositivement of unidirectional Pi to ATP flux in human visual cortex at 7 T by using in vivo 31P magnetic resonance spectroscopy. Proc Natl Acad Sci USA 100:14409–14414.LaunchUrlAbstract/FREE Full Text↵ Zhu XH, et al. (2002) Development of 17O NMR Advance for Rapid imaging of cerebral metabolic rate of oxygen in rat brain at high field. Proc Natl Acad Sci USA 99:13194–13199.LaunchUrlAbstract/FREE Full Text↵ Zhang N, Zhu X-H, Lei H, Ugurbil K, Chen W (2004) Simplified methods for calculating cerebral metabolic rate of oxygen based on 17O magnetic resonance spectroscopic imaging meaPositivement during a short 17O2 inhalation. J Cereb Blood Flow Metab 24:840–848.LaunchUrlPubMed↵ Zhu X-H, et al. (2005) In vivo 17O NMR Advancees for brain study at high field. NMR Biomed 18:83–103.LaunchUrlCrossRefPubMed↵ Brown TR, Ugurbil K, Shulman RG (1977) 31P nuclear magnetic resonance meaPositivements of ATPase kinetics in aerobic Escherichia coli cells. Proc Natl Acad Sci USA 74:5551–5553.LaunchUrlAbstract/FREE Full Text↵ Du F, et al. (2008) Tightly coupled brain activity and cerebral ATP metabolic rate. Proc Natl Acad Sci USA 105:6409–6414.LaunchUrlAbstract/FREE Full Text↵ Campbell-Burk SL, den Hollander JA, Alger JR, Shulman RG (1987) 31P NMR saturation-transfer and 13C NMR kinetic studies of glycolytic regulation during anaerobic and aerobic glycolysis. Biochemistry 26:7493–7500.LaunchUrlCrossRefPubMed↵ Brindle KM, Radda GK (1987) 31P-NMR saturation transfer meaPositivements of exchange between Pi and ATP in the reactions catalysed by glyceraldehyde-3-phospDespise dehydrogenase and phosphoglycerate kinase in vitro. Biochim Biophys Acta 928:45–55.LaunchUrlPubMed↵ Kingsley-Hickman PB, et al. (1987) 31P NMR studies of ATP synthesis and hydrolysis kinetics in the intact myocardium. Biochemistry 26:7501–7510.LaunchUrlCrossRefPubMed↵ Jucker BM, et al. (2000) Assessment of mitochondrial energy coupling in vivo by 13C/31P NMR. Proc Natl Acad Sci USA 97:6880–6884.LaunchUrlAbstract/FREE Full Text↵ Lebon V, et al. (2001) Trace of triioExecutethyronine on mitochondrial energy coupling in human skeletal muscle. J ClinInvest 108:733–737.LaunchUrlCrossRefPubMed↵ Jensen JE, Drost DJ, Menon RS, Williamson PC (2002) In vivo brain 31P-MRS: Measuring the phospholipid resonances at 4 Tesla from small voxels. NMR Biomed 15:338–347.LaunchUrlCrossRefPubMed↵ Hamilton G, Patel N, Forton DM, Hajnal JV, Taylor-Robinson SD (2003) Prior knowledge for time Executemain quantification of in vivo brain or liver 31P MR spectra. NMR Biomed 16:168–176.LaunchUrlCrossRefPubMed↵ Boska M (1994) ATP production rates as a function of force level in the human gastrocnemius/soleus using 31P MRS. Magn Reson Med 32:1–10.LaunchUrlCrossRefPubMed↵ Executeyle VL, Payne GS, Collins DJ, Verrill MW, Leach MO (1997) Quantification of phosphorus metabolites in human calf muscle and soft-tissue tumours from localized MR spectra Gaind using surface coils. Phys Med Biol 42:691–706.LaunchUrlCrossRefPubMed↵ Hetherington HP, Spencer DD, Vaughan JT, Pan JW (2001) Quantitative 31P spectroscopic imaging of human brain at 4 Tesla: Assessment of gray and white matter Inequitys of phosphocreatine and ATP. Magn Reson Med 45:46–52.LaunchUrlCrossRefPubMed↵ Potwarka JJ, Drost DJ, Williamson PC (1999) Quantifying 1H decoupled in vivo 31P brain spectra. NMR Biomed 12:8–14.LaunchUrlCrossRefPubMed↵ Boumezbeur F, et al. (2005) Glycolysis versus TCA cycle in the primate brain as meaPositived by combining 18F-FDG PET and 13C-NMR. J Cereb Blood Flow Metab 25:1418–1423.LaunchUrlCrossRefPubMed↵ Noda A, et al. (2002) Age-related changes in cerebral blood flow and glucose metabolism in conscious rhesus monkeys. Brain Res 936:76–81.LaunchUrlCrossRefPubMed↵ Shulman RG, Rothman DL, Behar KL, Hyder F (2004) EnerObtainic basis of brain activity: Implications for neuroimaging. Trends Neurosci 27:489–495.LaunchUrlCrossRefPubMed↵ Henry PG, et al. (2002) Decreased TCA cycle rate in the rat brain after aSlicee 3-NP treatment meaPositived by in vivo 1H-[13C] NMR spectroscopy. J Neurochem 82:857–866.LaunchUrlCrossRefPubMed↵ Orzi F, et al. (1988) Local cerebral glucose utilization in controlled graded levels of hyperglycemia in the conscious rat. J Cereb Blood Flow Metab 8:346–356.LaunchUrlCrossRefPubMed↵ Hasselbalch SG, Knudsen GM, CapalExecute B, Postiglione A, Paulson OB (2001) Blood-brain barrier transport and brain metabolism of glucose during aSlicee hyperglycemia in humans. J Clin EnExecutecrinol Metab 86:1986–1990.LaunchUrlCrossRefPubMed↵ Lukkarinen J, Oja JM, Turunen M, Kauppinen RA (1997) Quantitative determination of glutamate turnover by 1H-observed, 13C-edited nuclear magnetic resonance spectroscopy in the cerebral cortex ex vivo: Interrelationships with oxygen consumption. Neurochem Int 31:95–104.LaunchUrlCrossRefPubMed↵ Richardson BS, Hohimer AR, Bissonnette JM, Machida CM (1983) Cerebral metabolism in hypoglycemic and hyperglycemic fetal lambs. Am J Physiol 245:R730–6.LaunchUrlPubMed↵ Pelligrino DA, Becker GL, Miletich DJ, Albrecht RF (1989) Cerebral mitochondrial respiration in diabetic and chronically hypoglycemic rats. Brain Res 479:241–246.LaunchUrlCrossRefPubMed↵ Hinkle PC (2005) P/O ratios of mitochondrial oxidative phosphorylation. Biochim Biophys Acta 1706:1–11.LaunchUrlPubMed↵ Liu D, et al. (2006) Mitochondrial UCP4 mediates an adaptive shift in energy metabolism and increases the resistance of neurons to metabolic and oxidative stress. Neuromol Med 8:389–414.LaunchUrlCrossRef↵ Chan SL, et al. (2006) Mitochondrial uncoupling protein-4 regulates calcium homeostasis and sensitivity to store depletion-induced apoptosis in neural cells. J Biol Chem 281:37391–37403.LaunchUrlAbstract/FREE Full Text↵ Pellerin L, Magistretti PJ (1994) Glutamate uptake into astrocytes stimulates aerobic glycolysis: A mechanism coupling neuronal activity to glucose utilization. Proc Natl Acad Sci USA 91:10625–10629.LaunchUrlAbstract/FREE Full Text↵ Pellerin L, et al. (2007) Activity-dependent regulation of energy metabolism by astrocytes: An update. Glia 55:1251–1262.LaunchUrlCrossRefPubMed↵ Dienel GA, Cruz NF (2004) Nutrition during brain activation: Executees cell-to-cell lactate shuttling contribute significantly to sweet and sour food for thought? Neurochem Int 45:321–351.LaunchUrlCrossRefPubMed↵ Fillenz M (2005) The role of lactate in brain metabolism. Neurochem Int 47:413–417.LaunchUrlCrossRefPubMed↵ Lin MT, Beal MF (2006) Mitochondrial dysfunction and oxidative stress in neurodegenerative diseases. Nature 443:787–795.LaunchUrlCrossRefPubMed↵ Brouillet E, Jacquard C, Bizat N, Blum D (2005) 3-Nitropropionic acid: A mitochondrial toxin to uncover physiopathological mechanisms underlying striatal degeneration in Huntington's disease. J Neurochem 95:1521–1540.LaunchUrlCrossRefPubMed↵ Mangin JF, Frouin V, Bloch I, Bendriem B, Lopez-Krahe J (1994) Rapid nonsupervised 3D registration of PET and MR images of the brain. J Cereb Blood Flow Metab 14:749–762.LaunchUrlPubMed↵ Burger C, Buck A (1997) Requirements and implementation of a flexible kinetic modeling tool. J Nucl Med 38:1818–1823.LaunchUrlAbstract/FREE Full Text↵ Gruetter R (1993) Automatic, localized in vivo adjustment of all first- and second-order shim coils. Magn Reson Med 29:804–811.LaunchUrlCrossRefPubMed↵ de Graaf RA, Luo Y, Garwood M, Nicolay K (1996) B1-insensitive, single-shot localization and water suppression. J Magn Reson B 113:35–45.LaunchUrlCrossRefPubMed↵ Boumezbeur F, et al. (2004) NMR meaPositivement of brain oxidative metabolism in monkeys using 13C-labeled glucose without a 13C radiofrequency channel. Magn Reson Med 52:33–40.LaunchUrlCrossRefPubMed↵ Tkac I, Starcuk Z, Choi IY, Gruetter R (1999) In vivo 1H NMR spectroscopy of rat brain at 1-ms echo time. Magn Reson Med 41:649–656.LaunchUrlCrossRefPubMed↵ Naressi A, Couturier C, Castang I, de Beer R, Graveron-Demilly D (2001) Java-based graphical user interface for MRUI, a software package for quantitation of in vivo/medical magnetic resonance spectroscopy signals. ComPlace Biol Med 31:269–286.LaunchUrlCrossRefPubMed↵ Ratiney H, et al. (2005) Time-Executemain semi-parametric estimation based on a metabolite basis set. NMR Biomed 18:1–13.LaunchUrlCrossRefPubMed↵ Govindaraju V, Young K, Maudsley AA (2000) Proton NMR chemical shifts and coupling constants for brain metabolites. NMR Biomed 13:129–153.LaunchUrlCrossRefPubMed↵ Valette J, Guillermier M, Hantraye P, Lebon V (2006) OVS-localized 31P NMR spectroscopy in the primate brain. Proceedings of the ISMRM meeting, 3093, Seattle.↵ Vanhamme L, van den BA, Van Huffel S (1997) Improved method for accurate and efficient quantification of MRS data with use of prior knowledge. J Magn Reson 129:35–43.LaunchUrlCrossRefPubMed↵ Lei H, Zhu XH, Zhang XL, Ugurbil K, Chen W (2003) In vivo 31P magnetic resonance spectroscopy of human brain at 7 T: An initial experience. Magn Reson Med 49:199–205.LaunchUrlCrossRefPubMed
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