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.

  • Article
  • Published:

Neuronal activity drives pathway-specific depolarization of peripheral astrocyte processes

Nature Neuroscience volume 25, pages 607–616 (2022)Cite this article

Subjects

Abstract

Astrocytes are glial cells that interact with neuronal synapses via their distal processes, where they remove glutamate and potassium (K+) from the extracellular space following neuronal activity. Astrocyte clearance of both glutamate and K+ is voltage dependent, but astrocyte membrane potential (Vm) is thought to be largely invariant. As a result, these voltage dependencies have not been considered relevant to astrocyte function. Using genetically encoded voltage indicators to enable the measurement of Vm at peripheral astrocyte processes (PAPs) in mice, we report large, rapid, focal and pathway-specific depolarizations in PAPs during neuronal activity. These activity-dependent astrocyte depolarizations are driven by action potential-mediated presynaptic K+ efflux and electrogenic glutamate transporters. We find that PAP depolarization inhibits astrocyte glutamate clearance during neuronal activity, enhancing neuronal activation by glutamate. This represents a novel class of subcellular astrocyte membrane dynamics and a new form of astrocyte–neuron interaction.

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

Fig. 1: Astrocyte GEVI imaging enables measurement of astrocyte PAP Vm changes.
Fig. 2: Astrocyte GEVI shows microdomain depolarizations.
Fig. 3: Astrocyte GEVI depolarization microdomains occur outside of astrocyte somas and primary processes.
Fig. 4: Pathway independence of astrocyte depolarization.
Fig. 5: Calibration of Arclight GEVI.
Fig. 6: Glutamate transport and increases in [K+]e contribute to astrocyte depolarization.
Fig. 7: Astrocyte depolarization contributes to activity-dependent slowing of glutamate clearance.

Similar content being viewed by others

Data availability

Source data are provided with this paper. The datasets generated during and analyzed during the current study are available from the corresponding author on request.

Code availability

All computer code used to collect and analyze data are available from the corresponding author on request.

References

  1. Levy, L., Warr, O. & Attwell, D. Stoichiometry of the glial glutamate transporter GLT-1 expressed inducibly in a Chinese hamster ovary cell line selected for low endogenous Na+-dependent glutamate uptake. J. Neurosci. 18, 9620–9628 (1998).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Higashi, K. et al. An inwardly rectifying K(+) channel, Kir4.1, expressed in astrocytes surrounds synapses and blood vessels in brain. Am. J. Physiol. Cell Physiol. 281, C922–C931 (2001).

    Article  CAS  PubMed  Google Scholar 

  3. Amzica, F. & Neckelmann, D. Membrane capacitance of cortical neurons and glia during sleep oscillations and spike-wave seizures. J. Neurophysiol. 82, 2731–2746 (1999).

    Article  CAS  PubMed  Google Scholar 

  4. Amzica, F. In vivo electrophysiological evidences for cortical neuron-glia interactions during slow (<1 Hz) and paroxysmal sleep oscillations. J. Physiol. (Paris) 96, 209–219 (2002).

    Article  Google Scholar 

  5. Ma, B., Xu, G., Wang, W., Enyeart, J. J. & Zhou, M. Dual patch voltage clamp study of low membrane resistance astrocytes in situ. Mol. Brain 7, 18 (2014).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  6. Armbruster, M., Hanson, E. & Dulla, C. G. Glutamate clearance is locally modulated by presynaptic neuronal activity in the cerebral cortex. J. Neurosci. 36, 10404–10415 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Pinky, N. F., Wilkie, C. M., Barnes, J. R. & Parsons, M. P. Region- and activity-dependent regulation of extracellular glutamate. J. Neurosci. 38, 5351–5366 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Piatkevich, K. D. et al. A robotic multidimensional directed evolution approach applied to fluorescent voltage reporters. Nat. Chem. Biol. 14, 352–360 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Jin, L. et al. Single action potentials and subthreshold electrical events imaged in neurons with a fluorescent protein voltage probe. Neuron 75, 779–785 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Lee, Y., Messing, A., Su, M. & Brenner, M. GFAP promoter elements required for region-specific and astrocyte-specific expression. Glia 56, 481–493 (2008).

    Article  PubMed  Google Scholar 

  11. Yang, Y. et al. Molecular comparison of GLT1+ and ALDH1L1+ astrocytes in vivo in astroglial reporter mice. Glia 59, 200–207 (2011).

    Article  PubMed  PubMed Central  Google Scholar 

  12. Miesenbock, G., De Angelis, D. & Rothman, J. Visualizing secretion and synaptic transmission with pH-sensitive green fluorescent proteins. Nature 394, 192–195 (1998).

    Article  CAS  PubMed  Google Scholar 

  13. Koivusalo, M. et al. Amiloride inhibits macropinocytosis by lowering submembranous pH and preventing Rac1 and Cdc42 signaling. J. Cell Biol. 188, 547–563 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Shigetomi, E. et al. Imaging calcium microdomains within entire astrocyte territories and endfeet with GCaMPs expressed using adeno-associated viruses. J. Gen. Physiol. 141, 633–647 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Mukamel, E. A., Nimmerjahn, A. & Schnitzer, M. J. Automated analysis of cellular signals from large-scale calcium imaging data. Neuron 63, 747–760 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Savtchenko, L. P. et al. Disentangling astroglial physiology with a realistic cell model in silico. Nat. Commun. 9, 3554 (2018).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  17. Heinemann, U. & Lux, H. D. Ceiling of stimulus induced rises in extracellular potassium concentration in the cerebral cortex of cat. Brain Res. 120, 231–249 (1977).

    Article  CAS  PubMed  Google Scholar 

  18. Olsen, M. L. & Sontheimer, H. Functional implications for Kir4.1 channels in glial biology: from K+ buffering to cell differentiation. J. Neurochem. 107, 589–601 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Olsen, M. L., Higashimori, H., Campbell, S. L., Hablitz, J. J. & Sontheimer, H. Functional expression of Kir4.1 channels in spinal cord astrocytes. Glia 53, 516–528 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Tong, X. et al. Astrocyte Kir4.1 ion channel deficits contribute to neuronal dysfunction in Huntington’s disease model mice. Nat. Neurosci. 17, 694–703 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Cui, Y. et al. Astroglial Kir4.1 in the lateral habenula drives neuronal bursts in depression. Nature 554, 323–327 (2018).

    Article  CAS  PubMed  Google Scholar 

  22. Kelley, K. W. et al. Kir4.1-dependent astrocyte-fast motor neuron interactions are required for peak strength. Neuron 98, 306–319 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Djukic, B., Casper, K. B., Philpot, B. D., Chin, L. S. & McCarthy, K. D. Conditional knock-out of Kir4.1 leads to glial membrane depolarization, inhibition of potassium and glutamate uptake, and enhanced short-term synaptic potentiation. J. Neurosci. 27, 11354–11365 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Hille, B. Ion Channels of Excitable Membranes 3rd edn (Sinauer Associates, 2001).

  25. Diamond, J. Deriving the glutamate clearance time course from transporter currents in CA1 hippocampal astrocytes: transmitter uptake gets faster during development. J. Neurosci. 25, 2906–2916 (2005).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Marvin, J. et al. An optimized fluorescent probe for visualizing glutamate neurotransmission. Nat. Methods 10, 162–170 (2013).

  27. Raimondo, J. V., Burman, R. J., Katz, A. A. & Akerman, C. J. Ion dynamics during seizures. Front. Cell. Neurosci. 9, 419 (2015).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  28. Murphy-Royal, C. et al. Surface diffusion of astrocytic glutamate transporters shapes synaptic transmission. Nat. Neurosci. 18, 219–226 (2015).

    Article  CAS  PubMed  Google Scholar 

  29. Shih, P. Y. et al. Retrograde synaptic signaling mediated by K+ efflux through postsynaptic NMDA receptors. Cell Rep. 5, 941–951 (2013).

    Article  CAS  PubMed  Google Scholar 

  30. Sancho, L., Contreras, M. & Allen, N. J. Glia as sculptors of synaptic plasticity. Neurosci. Res. 167, 17–29 (2021).

    Article  CAS  PubMed  Google Scholar 

  31. Letellier, M. et al. Astrocytes regulate heterogeneity of presynaptic strengths in hippocampal networks. Proc. Natl Acad. Sci. USA 113, E2685–E2694 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. D’Ascenzo, M. et al. Electrophysiological and molecular evidence of L-(Cav1), N- (Cav2.2), and R- (Cav2.3) type Ca2+ channels in rat cortical astrocytes. Glia 45, 354–363 (2004).

    Article  PubMed  Google Scholar 

  33. Sontheimer, H., Black, J. A. & Waxman, S. G. Voltage-gated Na+ channels in glia: properties and possible functions. Trends Neurosci. 19, 325–331 (1996).

    Article  CAS  PubMed  Google Scholar 

  34. Wan, X. et al. Bimodal voltage dependence of TRPA1: mutations of a key pore helix residue reveal strong intrinsic voltage-dependent inactivation. Pflug. Arch. 466, 1273–1287 (2014).

    Article  CAS  Google Scholar 

  35. Lalo, U., Pankratov, Y., Kirchhoff, F., North, R. A. & Verkhratsky, A. NMDA receptors mediate neuron-to-glia signaling in mouse cortical astrocytes. J. Neurosci. 26, 2673–2683 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Willford, S. L., Anderson, C. M., Spencer, S. R. & Eskandari, S. Evidence for a revised ion/substrate coupling stoichiometry of GABA transporters. J. Membr. Biol. 248, 795–810 (2015).

    Article  CAS  PubMed  Google Scholar 

  37. Octeau, J. C. et al. Transient, consequential increases in extracellular potassium ions accompany channelrhodopsin2 excitation. Cell Rep. 27, 2249–2261 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Nimmerjahn, A., Kirchhoff, F., Kerr, J. & Helmchen, F. Sulforhodamine 101 as a specific marker of astroglia in the neocortex in vivo. Nat. Methods 1, 31–37 (2004).

    Article  CAS  PubMed  Google Scholar 

  39. Frankenhaeuser, B. & Hodgkin, A. L. The action of calcium on the electrical properties of squid axons. J. Physiol. 137, 218–244 (1957).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Hille, B., Woodhull, A. M. & Shapiro, B. I. Negative surface charge near sodium channels of nerve: divalent ions, monovalent ions, and pH. Philos. Trans. R. Soc. Lond. B Biol. Sci. 270, 301–318 (1975).

    Article  CAS  PubMed  Google Scholar 

  41. Isaev, D. et al. Surface charge impact in low-magnesium model of seizure in rat hippocampus. J. Neurophysiol. 107, 417–423 (2012).

    Article  CAS  PubMed  Google Scholar 

  42. Edelstein, A. D. et al. Advanced methods of microscope control using muManager software. J. Biol. Methods 1, e10 (2014).

  43. Armbruster, M., Hampton, D., Yang, Y. & Dulla, C. G. Laser-scanning astrocyte mapping reveals increased glutamate-responsive domain size and disrupted maturation of glutamate uptake following neonatal cortical freeze-lesion. Front. Cell. Neurosci. 8, 277 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  44. Hanson, E. et al. Astrocytic glutamate uptake is slow and does not limit neuronal NMDA receptor activation in the neonatal neocortex. Glia 63, 1784–1796 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  45. Cantu, D. et al. Traumatic brain injury increases cortical glutamate network activity by compromising GABAergic control. Cereb. Cortex 25, 2306–2320 (2014).

  46. Koenig, J. B. et al. Glycolytic inhibitor 2-deoxyglucose prevents cortical hyperexcitability after traumatic brain injury. JCI Insight https://doi.org/10.1172/jci.insight.126506 (2019).

  47. Pnevmatikakis, E. A. & Giovannucci, A. NoRMCorre: an online algorithm for piecewise rigid motion correction of calcium imaging data. J. Neurosci. Methods 291, 83–94 (2017).

    Article  CAS  PubMed  Google Scholar 

  48. Schindelin, J. et al. Fiji: an open-source platform for biological-image analysis. Nat. Methods 9, 676–682 (2012).

    Article  CAS  PubMed  Google Scholar 

  49. Evans, R. H., Francis, A. A., Jones, A. W., Smith, D. A. & Watkins, J. C. The effects of a series of omega-phosphonic alpha-carboxylic amino acids on electrically evoked and excitant amino acid-induced responses in isolated spinal cord preparations. Br. J. Pharmacol. 75, 65–75 (1982).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Honore, T. et al. Quinoxalinediones: potent competitive non-NMDA glutamate receptor antagonists. Science 241, 701–703 (1988).

    Article  CAS  PubMed  Google Scholar 

  51. Le Meur, K., Galante, M., Angulo, M. A. C. & Audinat, E. Tonic activation of NMDA receptors by ambient glutamate of non-synaptic origin in the rat hippocampus. J. Physiol. 580, 373–383 (2007).

    Article  PubMed  CAS  Google Scholar 

  52. Heaulme, M. et al. Biochemical characterization of the interaction of three pyridazinyl-GABA derivatives with the GABAA receptor site. Brain Res. 384, 224–231 (1986).

    Article  CAS  PubMed  Google Scholar 

  53. Williams, K. Ifenprodil discriminates subtypes of the N-methyl-d-aspartate receptor: selectivity and mechanisms at recombinant heteromeric receptors. Mol. Pharmacol. 44, 851–859 (1993).

    CAS  PubMed  Google Scholar 

  54. Shimamoto, K. et al. Characterization of novel L-threo-beta-benzyloxyaspartate derivatives, potent blockers of the glutamate transporters. Mol. Pharmacol. 65, 1008–1015 (2004).

    Article  CAS  PubMed  Google Scholar 

  55. Hanson, E. et al. Tonic activation of GluN2C/GluN2D-containing NMDA receptors by ambient glutamate facilitates cortical interneuron maturation. J. Neurosci. 39, 3611–3626 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Armbruster, M., Dulla, C. G. & Diamond, J. S. Effects of fluorescent glutamate indicators on neurotransmitter diffusion and uptake. eLife 9, e54441 (2020).

Download references

Acknowledgements

We thank members of the Dulla, Haydon and Rios laboratories, and J. Raimondo and J. Diamond for helpful comments on the manuscript. We thank Y. Yang (Tufts) for EAAT2-tdTomato mice. We thank L. Looger (UCSD), V. Pieribone (Yale), B. Khakh (UCLA) and S. Grinstein (University of Toronto) for making available plasmids and constructs. This work was supported by the NIH (nos. NS113499, NS104478 and NS100796 to C.G.D.; MH117042 to AEC).

Author information

Author notes

  1. Yoav Adam

    Present address: Edmond and Lily Safra Center for Brain Sciences, the Hebrew University of Jerusalem, Jerusalem, Israel

Authors and Affiliations

  1. Department of Neuroscience, Tufts University School of Medicine, Boston, MA, USA

    Moritz Armbruster, Saptarnab Naskar, Jacqueline P. Garcia, Mary Sommer, Elliot Kim, Philip G. Haydon & Chris G. Dulla

  2. Cell, Molecular, and Developmental Biology Program, Tufts Graduate School of Biomedical Sciences, Boston, MA, USA

    Jacqueline P. Garcia

  3. Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA

    Yoav Adam & Adam E. Cohen

  4. Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA

    Edward S. Boyden

  5. Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA

    Edward S. Boyden

  6. McGovern Institute, Massachusetts Institute of Technology, Cambridge, MA, USA

    Edward S. Boyden

  7. Howard Hughes Medical Institute, Massachusetts Institute of Technology, Cambridge, MA, USA

    Edward S. Boyden

  8. Koch Institute, Massachusetts Institute of Technology, Cambridge, MA, USA

    Edward S. Boyden

  9. Center for Neurobiological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA

    Edward S. Boyden

  10. Department of Physics, Harvard University, Cambridge, MA, USA

    Adam E. Cohen

Authors
  1. Moritz Armbruster
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Saptarnab Naskar
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jacqueline P. Garcia
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Mary Sommer
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Elliot Kim
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Yoav Adam
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Philip G. Haydon
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Edward S. Boyden
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Adam E. Cohen
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Chris G. Dulla
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

M.A. oversaw conceptualization, methodology, investigation, formal analysis, data curation, visualization and writing of the original draft. S.N. carried out investigation, formal analysis, writing and review and editing. J.P.G., M.S. and E.K. performed investigation. Y.A. carried out methodology and investigation. P.G.H., A.E.C. and E.S.B. were responsible for resources and methodology. C.G.D. oversaw conceptualization, formal analysis, visualization, supervision, funding acquisition, project administration, resources and writing of the original draft.

Corresponding authors

Correspondence to Moritz Armbruster or Chris G. Dulla.

Ethics declarations

Competing interests

The authors declare no competing interests.

Peer review

Peer review information

Nature Neuroscience thanks Yukiko Goda, Michelle L. Olsen and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Extended Data Fig. 1 GEVI expression does not induce reactive astrocytosis.

Representative confocal IHC images stained for GFAP in Arclight infected and Archon1-EGFP (EGFP fluorescence shown) infected cortices. Additionally, staining in matched uninfected contralateral cortex. Neither GEVI infected or uninfected contralateral cortex shows high GFAP levels, indicative of a lack of reactive astrocytosis. In order to verify the sensitivity of our GFAP antibody, we stained slices 3 days following controlled cortical impact, a robust model of traumatic brain injury. In this positive control, astrocytes are labeled with the astrocyte specific marker Sox9 and shows high levels of GFAP staining and astrocytosis. Scalebar = 50 µm.

Extended Data Fig. 2 GEVI expression does not change astrocyte morphology.

Example confocal sections and reconstruction of the astrocyte cell-fill reporter tdTomato either uninfected controls (left column), Arclight infected (middle column), or Archon infected (right column). No significant changes were observed in total astrocyte volume or soma volume between control or GEVI infected astrocytes. N= 8 control, 5 Arclight, 6 Archon astrocytes. One way ANOVA Control v Arclight p = 0.23, Control v Archon p = 0.058, Arclight v Archon p = 0.81. All panels: Error bars = Standard error of the mean.

Extended Data Fig. 3 Correcting pH transients.

Average pH transients (Lyn-pHluorin) and Arclight GEVI responses to A) 1 Stim, B) 5 Stimuli at 100Hz, C) 10 Stimuli at 100Hz. D) The GEVI decays are corrected for the pH changes using the difference in the Arclight and pHluorin traces. n = 9 Slices/ 3 mice (pHluorin). n = 17 slices/6 mice (Arclight). All panels: Error bars = Standard error of the mean.

Extended Data Fig. 4 Astrocyte membrane probes primarily localize to astrocyte process rather than soma.

Example confocal images from a 3D Z-stack of astrocyte targeted Arclight (a membrane targeted GEVI) and an astrocyte cell fill (GFAP-tdTomato). We subsequently quantified the Arclight fluorescence originating from the soma membrane compared to the total astrocyte Arclight fluorescence in all Z-sections. Soma fluorescence represents 1.0 ± 0.0005% of the total Arclight fluorescence N = 6 astrocytes. Scale bar = 10 μm.

Extended Data Fig. 5 Confocal Laser Scanning Microscopy shows ROI hotspots have skewed distributions.

Half of individual ROI hotspots from Fig. 3g,h, are fit with 2D gaussians to determine one-sided standard deviations for X and Y- axis. Both Arclight and Archon show significantly more skewed fluorescence distribution along the Y-axis. Box-Whisker plot, Box = 25, 50, 75th percentile, whiskers = 5-95th percentile, square = mean. *** = p < 0.001. N= 1109 ROIs (Arclight, p = 1.1E-30) and N=104 ROIs (Archon p = 3.3E-11).

Extended Data Fig. 6 K+ wash-on calibration induces uniform depolarization.

Example image of Arclight (scale bar = 30 μm) and response image to +5mM K+ wash-on, shows largely uniform voltage response across the field. Outliers, such as those highlighted with white arrows, tend to be areas excluding the Arclight sensor such as somas, or blood vessels. Distribution of pixel responses to +5mM K+ shows a uniform distribution of depolarization responses.

Extended Data Fig. 7 Kir4.1 Overexpression.

A) Confocal example image of immunofluorescence staining of Kir4.1 in Kir4.1 overexpression (Kir4.1-OE), (AAV5-GFAP-Kir4.1-EGFP) or control (AAV5-GFAP-GFP) infected cortex. B) Quantification of widefield Kir4.1 IHC staining shows significantly enhanced Kir4.1 staining. Scale bar = 50 µm. Two-sample t-test, n=3, 4 mice, p = 0.038. C, D) Astrocyte whole-cell voltage clamp shows enhanced Ba2+ (Kir4.1 inhibitor) sensitive currents in Kir4.1-OE compared to control-infected cortex. 9 cells/3 mice each. E) Ba2+- sensitive currents are significantly increase in Kir4.1-OE astrocytes, p = 0.028. F) Western blot quantification of Kir4.1-OE (AAV5-GFAP=Kir4.1-mCherry), shows significantly increased Kir4.1 protein compared to control virus (AAV5-GFAP-tdTomato). p = 0.049 * = p < 0.05 All panels: Error bars = Standard error of the mean.

Source data

Extended Data Fig. 8 Kir4.1 depolarizes astrocyte soma during neuronal activity.

Astrocyte-whole cell current clamp recordings were made in the cortex to measure somatic Vm. In order to isolate the effects of Kir4.1 on astrocyte Vm during neuronal activity, glutamate transporter activity was blocked with TFB-TBOA and responses to 10 stimuli at 100Hz were recorded before and after blockade of Kir4.1 with Ba2+. A) Average paired traces before (black) and after (red) inhibition of Kir4.1 with Ba2+, and B) the Ba2+-sensitive ΔVm. These recordings show that Kir4.1 depolarizes astrocyte soma during neuronal activity. C and D) Expanded time scale (dashed boxes in A & B) to show Vm during stimulus. N = 5 cells. All panels: Error bars = Standard error of the mean.

Extended Data Fig. 9 The effects of low Ca2+ on presynaptic release do not correlate with the effects on glutamate clearance and astrocyte depolarization.

Utilizing data from Figs. 6, 7, and Extended Data Fig. 10 we plotted the effects of Low Ca2+ aCSF on presynaptic release (x-axis) and glutamate clearance/astrocyte depolarization (y-axis) for 1, 5, and 10 stimuli at 100Hz. In each condition, Low Ca2+ is normalized to control. Dashed lines represent no change from control. Left of the dashed line on the x-axis represents a reduction in presynaptic release (as assayed by GTC, iGluSnFr, or NMDA peak amplitude). Beneath the dashed line represents an enhanced glutamate clearance/reduced depolarization (as assayed by GTC/iGluSnFr/NMDA decays and Arclight peaks). 1 Stim responses (grey) shows the largest change in presynaptic release, with the smallest effect on glutamate clearance/depolarization. 10 Stimuli at 100Hz (blue) shows the smallest presynaptic release effect with the largest glutamate clearance/depolarization effect.

Extended Data Fig. 10 Low Ca2+ Glutamate Transporter Currents.

Glutamate transporter currents were recorded from astrocytes with Control or Low Ca2+ aCSF, showing enhanced glutamate clearance following trains of stimulation. Two way repeated measures ANOVA * = p<0.05. n = 10 cells/3 mice, p = 0.046. All panels: Error bars = Standard error of the mean.

Supplementary information

Supplementary Information

Supplementary Figs. 1 and 2 (with legends) and Table 1.

Reporting Summary

Source data

Source Data Extended Data Fig. 7

Immunoblot source data.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Armbruster, M., Naskar, S., Garcia, J.P. et al. Neuronal activity drives pathway-specific depolarization of peripheral astrocyte processes. Nat Neurosci 25, 607–616 (2022). https://doi.org/10.1038/s41593-022-01049-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41593-022-01049-x

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