Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Brief Communication
  • Published:

[18F]FDG PET signal is driven by astroglial glutamate transport

Nature Neuroscience volume 20, pages 393–395 (2017)Cite this article

Subjects

Abstract

Contributions of glial cells to neuroenergetics have been the focus of extensive debate. Here we provide positron emission tomography evidence that activation of astrocytic glutamate transport via the excitatory amino acid transporter GLT-1 triggers widespread but graded glucose uptake in the rodent brain. Our results highlight the need for a reevaluation of the interpretation of [18F]FDG positron emission tomography data, whereby astrocytes would be recognized as contributing to the [18F]FDG signal.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Figure 1: Astrocytic glutamate transport activation via GLT-1 triggers cerebral [18F]FDG uptake.
Figure 2: Astrocytic glutamate transport activation via GLT-1 disrupts region-to-region metabolic synchronicity.
Figure 3: Astrocytic glutamate transport activation via GLT-1 uncouples [18F]FDG uptake and CBFresponse.

Similar content being viewed by others

References

  1. Sokoloff, L. Dev. Neurosci. 15, 194–206 (1993).

    Article  CAS  Google Scholar 

  2. Mazziotta, J.C., Phelps, M.E., Miller, J. & Kuhl, D.E. Neurology 31, 503–516 (1981).

    Article  Google Scholar 

  3. Mosconi, L. et al. J. Nucl. Med. 49, 390–398 (2008).

    Article  Google Scholar 

  4. Nehlig, A. & Coles, J.A. Glia 55, 1238–1250 (2007).

    Article  Google Scholar 

  5. Figley, C.R. & Stroman, P.W. Eur. J. Neurosci. 33, 577–588 (2011).

    Article  Google Scholar 

  6. Volterra, A. & Meldolesi, J. Nat. Rev. Neurosci. 6, 626–640 (2005).

    Article  CAS  Google Scholar 

  7. Pellerin, L. & Magistretti, P.J. J. Cereb. Blood Flow Metab. 23, 1282–1286 (2003).

    Article  Google Scholar 

  8. Pellerin, L. & Magistretti, P.J. J. Cereb. Blood Flow Metab. 32, 1152–1166 (2012).

    Article  CAS  Google Scholar 

  9. Pellerin, L. & Magistretti, P.J. Proc. Natl. Acad. Sci. USA 91, 10625–10629 (1994).

    Article  CAS  Google Scholar 

  10. Voutsinos-Porche, B. et al. Cereb. Cortex 13, 1110–1121 (2003).

    Article  Google Scholar 

  11. Voutsinos-Porche, B. et al. Neuron 37, 275–286 (2003).

    Article  CAS  Google Scholar 

  12. Magistretti, P.J. & Pellerin, L. Mol. Psychiatry 1, 445–452 (1996).

    CAS  PubMed  Google Scholar 

  13. Rothstein, J.D. et al. Nature 433, 73–77 (2005).

    Article  CAS  Google Scholar 

  14. Zimmer, E.R. et al. J. Cereb. Blood Flow Metab. 35, 1169–1174 (2015).

    Article  CAS  Google Scholar 

  15. Lehre, K.P., Levy, L.M., Ottersen, O.P., Storm-Mathisen, J. & Danbolt, N.C. J. Neurosci. 15, 1835–1853 (1995).

    Article  CAS  Google Scholar 

  16. Chugani, H.T., Phelps, M.E. & Mazziotta, J.C. Ann. Neurol. 22, 487–497 (1987).

    Article  CAS  Google Scholar 

  17. Phelps, M.E. & Mazziotta, J.C. Science 228, 799–809 (1985).

    Article  CAS  Google Scholar 

  18. Choi, H. et al. Neuroimage 99, 226–236 (2014).

    Article  CAS  Google Scholar 

  19. Lauritzen, M. J. Cereb. Blood Flow Metab. 21, 1367–1383 (2001).

    Article  CAS  Google Scholar 

  20. Jack, C.R. Jr. et al. Lancet Neurol. 12, 207–216 (2013).

    Article  CAS  Google Scholar 

  21. Zimmer, E.R., Parent, M.J., Cuello, A.C., Gauthier, S. & Rosa-Neto, P. Trends Neurosci 37, 629–641 (2014).

    Article  CAS  Google Scholar 

  22. Furuta, A., Rothstein, J.D. & Martin, L.J. J. Neurosci. 17, 8363–8375 (1997).

    Article  CAS  Google Scholar 

  23. Souza, D.G., Bellaver, B., Souza, D.O. & Quincozes-Santos, A. PLoS One 8, e60282 (2013).

    Article  CAS  Google Scholar 

  24. Debernardi, R., Magistretti, P.J. & Pellerin, L. Brain Res. 850, 39–46 (1999).

    Article  CAS  Google Scholar 

  25. Souza, D.G. et al. Neurochem. Res. 41, 1578–1586 (2016).

    Article  CAS  Google Scholar 

  26. Worsley, K.J. et al. Hum. Brain Mapp. 4, 58–73 (1996).

    Article  CAS  Google Scholar 

Download references

Acknowledgements

We thank D. Onofre Souza, L. Valmor Cruz Portela, F. Urruth Fontella and A. Silva da Rocha from the Department of Biochemistry at UFRGS for fruitful discussions and for helping to conduct biochemical assays. This work was supported by a grant from iMSE from GIST and by the National Research Foundation of Korea (NRF:2013R1A2A2A01067890 to H.-I.K.), the Canadian Institutes of Health Research (CIHR; MOP-11-51-31 to P.R.-N. and MOP-142417 to E.H.), the Alan Tiffin Foundation, the Alzheimer's Association (NIRG-08-92090 to P.R.-N.), the Fonds de la recherche en santé du Québec (Chercheur boursier), the Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq), the Fundação de Amparo à Pesquisa do Estado do Rio Grande do Sul (FAPERGS), the INCT for Excitotoxicity and Neuroprotection and Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES). Work in the laboratory of L.P. is financially supported by the department of Physiology, University of Lausanne.

Author information

Author notes

  1. Eduardo R Zimmer & Antoine Leuzy

    Present address: Present address: Brain Institute of Rio Grande do Sul (BraIns), Pontifical Catholic University of Rio Grande do Sul, Porto Alegre, Brazil (E.R.Z.); Department of Neurobiology, Care Science, and Society, Centre for Alzheimer's Research, Division of Translational Alzheimer's Neurobiology, Karolinska Institutet, Stockholm, Sweden (A.L.).,

Authors and Affiliations

  1. Translational Neuroimaging Laboratory (TNL), McGill Center for Studies in Aging (MCSA), Douglas Mental Health University Institute, Departments of Neurology and Neurosurgery, Psychiatry, and Pharmacology, McGill University, Montreal, Canada

    Eduardo R Zimmer, Maxime J Parent, Antoine Leuzy, Serge Gauthier & Pedro Rosa-Neto

  2. Department of Biochemistry, Federal University of Rio Grande do Sul, Porto Alegre, Brazil

    Eduardo R Zimmer & Débora G Souza

  3. Laboratory of Cerebrovascular Research, Montreal Neurological Institute, McGill University, Montreal, Canada

    Clotilde Lecrux & Edith Hamel

  4. Department of Medical System Engineering & School of Mechatronics, Gwangju Institute of Science and Technology, Gwangju, Republic of Korea

    Hyoung-Ihl Kim

  5. Department of Neurosurgery, Presbyterian Medical Center, Jeonju, Republic of Korea

    Hyoung-Ihl Kim

  6. McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Canada

    Pedro Rosa-Neto

  7. Department of Physiology, University of Lausanne, Lausanne, Switzerland

    Débora G Souza & Luc Pellerin

Authors
  1. Eduardo R Zimmer
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Maxime J Parent
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Débora G Souza
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Antoine Leuzy
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Clotilde Lecrux
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Hyoung-Ihl Kim
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Serge Gauthier
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Luc Pellerin
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Edith Hamel
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Pedro Rosa-Neto
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

All authors participated on the conceptualization, design and interpretation of the experiments. E.R.Z., M.J.P., A.L., H.-I.K. and P.R.-N. were responsible for conducting imaging acquisitions and analysis. E.R.Z., D.G.S. and L.P. were responsible for conducting in vitro studies in cell cultures. C.L. and E.H. were responsible for conducting laser Doppler acquisitions and analysis. All authors critically revised and approved the final version of the manuscript.

Corresponding author

Correspondence to Pedro Rosa-Neto.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Integrated supplementary information

Supplementary Figure 1 Ceftriaxone increases astroglial glutamate transport and glucose utilization without affecting GLT-1 expression in cultured adult cortical astrocytes.

(a) Glial fibrillary acidic protein (GFAP, green) and DAPI (blue), (b) Vimentin (red) and DAPI (blue), (c) GLT-1 (green) and DAPI (blue), and (d) NeuN (red) and DAPI (blue). (e) GLT-1 immunocontent (n = 6, two-tailed unpaired t-test, t(10) = 0.5469, p= 0.5964). (f) [3H]2DG uptake assay (n = 9-14; One-way ANOVA corrected by Bonferroni, F(3,39) = 16.88, p <0.0001). (g) [3H]D-Aspartate uptake assay (n = 9, two-tailed unpaired t-test, t(16) = 2.71, p = 0.0155). (h) Glutamate concentration in the extracellular medium in presence or absence of CEF after 70 minutes (n = 7, two-tailed unpaired t-test, t(12) = 2.968, p = 0.0117), (i) Glutamate concentration before (green circle) and after incubation (basal, blue square; and CEF, orange triangle). *p < 0.05 and ****p < 0.0001. Dashed line (mean) and yellow-shadowed area (s.d.) represent glutamate levels in the medium before incubation. Data are presented as mean values ± s.d. and individual scatter plots. Scale bar 10 μm.

Supplementary Figure 2 Astrocytic glutamate transport activation via GLT-1 does not alter spontaneous locomotion in the open field.

(a) Group representative occupancy plot. (b) Dynamic raster plots displaying individual patterns of habituation. (c) Total distance travelled (t(28) = 0.0756, p = 0.942), (d) mobile time (t(28) = 0.0351, p = 0.972), (e) mean speed (t(28) = 0.242, p = 0.8106), (f) time in central zone (t(28) = 1.016, p = 0.3182), and (g) distance travelled (t(28) = 0.3128, p = 0.7568) in the central zone. n = 15 rats per group. Two tailed unpaired t-test. Data are presented as mean values ± s.d. and individual scatter plots.

Supplementary Figure 3 Averaged brain maps and astrocytic glutamate transport activation patterns.

(a) Baseline SUV averaged maps. (b) CEF challenge SUV averaged maps. (c) Dynamic raster plots displaying individual patterns of [18F]FDG uptake after astrocytic glutamate transport activation via GLT-1. n = 10 per group.

Supplementary Figure 4 GLT-1 mRNA expression in the mouse brain.

(a) Regional GLT-1 mRNA expression. (b) Correlation between regional averaged percentage of change (CEF challenge – baseline) and regional GLT-1 mRNA expression. (c) GLT-1 in situ hybridization in sagittal view. (d) GLT-1 mRNA expression in the prefrontal cortex. (e) GLT-1 mRNA expression in the hippocampus. (f) GLT-1 mRNA expression in the striatum. (g) GLT-1 mRNA expression in the thalamus. (h) GLT-1 mRNA expression in the cerebellum. All images were acquired from the Allen Mouse Brain Connectivity Atlas (Image credit: Allen Institute for Brain Science; ©2012 Allen Institute for Brain Science. Allen Mouse Brain Atlas [Internet]. Available from: http://mouse.brain-map.org).

Supplementary Figure 5 Astrocytic glutamate transport activation via GLT-1 disrupts region-to-region metabolic synchronicity.

Cross-correlation matrices: inter-subject cross correlation maps displaying region-to-region associations in the baseline (a) and CEF challenge (b) conditions. Metabolic networks: 3D brain surfaces displaying large-scale metabolic cross-correlation maps in the baseline (c) and in the CEF challenge (d) conditions. n = 10 rats per group. Size of white circles (hubs) indicates number of connections. Data presented as correlation values with False Discovery Rate (FDR) correction at p<0.05.

Supplementary Figure 6 Full-length blots for data shown in Supplementary Figure 1.

Supplementary information

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zimmer, E., Parent, M., Souza, D. et al. [18F]FDG PET signal is driven by astroglial glutamate transport. Nat Neurosci 20, 393–395 (2017). https://doi.org/10.1038/nn.4492

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nn.4492

This article is cited by

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing