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.

Phagocyte-mediated synapse removal in cortical neuroinflammation is promoted by local calcium accumulation

Abstract

Cortical pathology contributes to chronic cognitive impairment of patients suffering from the neuroinflammatory disease multiple sclerosis (MS). How such gray matter inflammation affects neuronal structure and function is not well understood. In the present study, we use functional and structural in vivo imaging in a mouse model of cortical MS to demonstrate that bouts of cortical inflammation disrupt cortical circuit activity coincident with a widespread, but transient, loss of dendritic spines. Spines destined for removal show local calcium accumulations and are subsequently removed by invading macrophages or activated microglia. Targeting phagocyte activation with a new antagonist of the colony-stimulating factor 1 receptor prevents cortical synapse loss. Overall, our study identifies synapse loss as a key pathological feature of inflammatory gray matter lesions that is amenable to immunomodulatory therapy.

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

Access options

Rent or buy this article

Prices vary by article type

from$1.95

to$39.95

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

Fig. 1: Projection neurons lose excitatory synaptic input in a model of c-MS.
Fig. 2: Neurons are silenced in a model of c-MS.
Fig. 3: Resilience of neuronal circuit structure in a model of c-MS.
Fig. 4: Local calcium accumulations prime spines for removal.
Fig. 5: Mononuclear phagocytes remove synapses.
Fig. 6: Blocking phagocyte entry and activation prevents synapse loss in the c-MS model.

Data availability

All data are available in the manuscript or the supplementary materials. Raw data are available upon reasonable request to the corresponding authors. The raw RNA-seq data have been deposited into the NCBI’s Gene Expression Omnibus repository under accession no. GSE161654. Source data are provided with this paper.

Code availability

The codes used to perform the cross-correlation analysis and the codes of the graphical user interface used to analyze the calcium events (Supplementary Software 1) are publicly available on the github repository: https://github.com/portugueslab/Jafari-et-al-2020. The codes used to reanalyze the snRNA-seq data (Supplementary Software 2) from Schirmer et al.49 are publicly available on the github repository: https://github.com/engelsdaniel/schirmer_reanalyzed.

References

  1. Reich, D. S., Lucchinetti, C. F. & Calabresi, P. A. Multiple sclerosis. N. Engl. J. Med. 378, 169–180 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Mahad, D. H., Trapp, B. D. & Lassmann, H. Pathological mechanisms in progressive multiple sclerosis. Lancet Neurol. 14, 183–193 (2015).

    Article  CAS  PubMed  Google Scholar 

  3. Damjanovic, D. et al. Hippocampal and deep gray matter nuclei atrophy is relevant for explaining cognitive impairment in MS: a multicenter study. Am. J. Neuroradiol. 38, 18–24 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Eshaghi, A. et al. Deep gray matter volume loss drives disability worsening in multiple sclerosis. Ann. Neurol. 83, 210–222 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Scalfari, A. et al. The cortical damage, early relapses, and onset of the progressive phase in multiple sclerosis. Neurology 90, e2099–e2106 (2018).

    Article  Google Scholar 

  6. Peterson, J. W., Bö, L., Mörk, S., Chang, A. & Trapp, B. D. Transected neurites, apoptotic neurons, and reduced inflammation in cortical multiple sclerosis lesions. Ann. Neurol. 50, 389–400 (2001).

    Article  CAS  PubMed  Google Scholar 

  7. Lagumersindez-Denis, N. et al. Differential contribution of immune effector mechanisms to cortical demyelination in multiple sclerosis. Acta Neuropathol. 134, 15–34 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Jürgens, T. et al. Reconstruction of single cortical projection neurons reveals primary spine loss in multiple sclerosis. Brain 139, 39–46 (2016).

    Article  PubMed  Google Scholar 

  9. Albert, M. et al. Synaptic pathology in the cerebellar dentate nucleus in chronic multiple sclerosis. Brain Pathol. 27, 737–747 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  10. Rose, T., Jaepel, J., Hübener, M. & Bonhoeffer, T. Cell-specific restoration of stimulus preference after monocular deprivation in the visual cortex. Science 352, 1319–1322 (2016).

    Article  CAS  PubMed  Google Scholar 

  11. Xu, T. et al. Rapid formation and selective stabilization of synapses for enduring motor memories. Nature 462, 915–919 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Kuchibhotla, K. V. et al. Aβ plaques lead to aberrant regulation of calcium homeostasis in vivo resulting in structural and functional disruption of neuronal networks. Neuron 59, 214–225 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Merlini, M. et al. Fibrinogen induces microglia-mediated spine elimination and cognitive impairment in an Alzheimer’s disease model. Neuron 101, 1099–1108.e6 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Merkler, D., Ernsting, T., Kerschensteiner, M., Brück, W. & Stadelmann, C. A new focal EAE model of cortical demyelination: multiple sclerosis-like lesions with rapid resolution of inflammation and extensive remyelination. Brain 129, 1972–1983 (2006).

    Article  PubMed  Google Scholar 

  15. Gardner, C. et al. Cortical grey matter demyelination can be induced by elevated pro-inflammatory cytokines in the subarachnoid space of MOG-immunized rats. Brain 136, 3596–3608 (2013).

    Article  PubMed  Google Scholar 

  16. Lodygin, D. et al. β-Synuclein-reactive T cells induce autoimmune CNS grey matter degeneration. Nature 566, 503–508 (2019).

    Article  CAS  PubMed  Google Scholar 

  17. Magliozzi, R. et al. Inflammatory intrathecal profiles and cortical damage in multiple sclerosis. Ann. Neurol. 83, 739–755 (2018).

    Article  CAS  PubMed  Google Scholar 

  18. Lucchinetti, C. F. et al. Inflammatory cortical demyelination in early multiple sclerosis. N. Engl. J. Med. 365, 2188–2197 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Dana, H. et al. Thy1-GCaMP6 transgenic mice for neuronal population imaging in vivo. PLoS ONE 9, e108697 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  20. Schain, A. J., Hill, R. A. & Grutzendler, J. Label-free in vivo imaging of myelinated axons in health and disease with spectral confocal reflectance microscopy. Nat. Med. 20, 443–449 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Siffrin, V. et al. In vivo imaging of partially reversible Th17 cell-induced neuronal dysfunction in the course of encephalomyelitis. Immunity 33, 424–436 (2010).

    Article  CAS  PubMed  Google Scholar 

  22. Witte, M. E. et al. Calcium influx through plasma-membrane nanoruptures drives axon degeneration in a model of multiple sclerosis. Neuron 101, 615–624.e5 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Thestrup, T. et al. Optimized ratiometric calcium sensors for functional in vivo imaging of neurons and T lymphocytes. Nat. Methods 11, 175–182 (2014).

    Article  CAS  PubMed  Google Scholar 

  24. Yamasaki, R. et al. Differential roles of microglia and monocytes in the inflamed central nervous system. J. Exp. Med. 211, 1533–1549 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Hagan, N. et al. CSF1R signaling is a regulator of pathogenesis in progressive MS. Cell Death Dis. 11, 904 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Nissen, J. C., Thompson, K. K., West, B. L. & Tsirka, S. E. Csf1R inhibition attenuates experimental autoimmune encephalomyelitis and promotes recovery. Exp. Neurol. 307, 24–36 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Olmos-Alonso, A. et al. Pharmacological targeting of CSF1R inhibits microglial proliferation and prevents the progression of Alzheimer’s-like pathology. Brain 139, 891–907 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  28. Huang, D., Wang, J., Kivisakk, P., Rollins, B. J. & Ransohoff, R. M. Absence of monocyte chemoattractant protein 1 in mice leads to decreased local macrophage recruitment and antigen-specific T helper cell type 1 immune response in experimental autoimmune encephalomyelitis. J. Exp. Med. 193, 713–725 (2001).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Krasemann, S. et al. The TREM2-APOE pathway drives the transcriptional phenotype of dysfunctional microglia in neurodegenerative diseases. Immunity 47, 566–581.e9 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Calabrese, M. et al. Cortical lesion load associates with progression of disability in multiple sclerosis. Brain 135, 2952–2961 (2012).

    Article  PubMed  Google Scholar 

  31. Dutta, R. et al. Demyelination causes synaptic alterations in hippocampi from multiple sclerosis patients. Ann. Neurol. 69, 445–454 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Michailidou, I. et al. Complement C1q-C3-associated synaptic changes in multiple sclerosis hippocampus. Ann. Neurol. 77, 1007–1026 (2015).

    Article  CAS  PubMed  Google Scholar 

  33. Terry, R. D. et al. Physical basis of cognitive alterations in alzheimer’s disease: synapse loss is the major correlate of cognitive impairment. Ann. Neurol. 30, 572–580 (1991).

    Article  CAS  PubMed  Google Scholar 

  34. Busche, M. A. et al. Clusters of hyperactive neurons near amyloid plaques in a mouse model of Alzheimer’s disease. Science 321, 1686–1689 (2008).

    Article  CAS  PubMed  Google Scholar 

  35. Šišková, Z. et al. Dendritic structural degeneration is functionally linked to cellular hyperexcitability in a mouse model of Alzheimer’s disease. Neuron 84, 1023–1033 (2014).

    Article  PubMed  Google Scholar 

  36. Marinković, P. et al. In vivo imaging reveals reduced activity of neuronal circuits in a mouse tauopathy model. Brain 142, 1051–1062 (2019).

    Article  PubMed  Google Scholar 

  37. Rocca, M. A. et al. Default-mode network dysfunction and cognitive impairment in progressive MS. Neurology 74, 1252–1259 (2010).

    Article  CAS  PubMed  Google Scholar 

  38. Kerschensteiner, M. et al. Remodeling of axonal connections contributes to recovery in an animal model of multiple sclerosis. J. Exp. Med. 200, 1027–1038 (2004).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Ellwardt, E. et al. Maladaptive cortical hyperactivity upon recovery from experimental autoimmune encephalomyelitis. Nat. Neurosci. 21, 1392–1403 (2018).

    Article  CAS  PubMed  Google Scholar 

  40. Jawaid, S. et al. Alterations in CA1 hippocampal synapses in a mouse model of fragile X syndrome. Glia 66, 789–800 (2018).

    Article  PubMed  Google Scholar 

  41. Vasek, M. J. et al. A complement-microglial axis drives synapse loss during virus-induced memory impairment. Nature 534, 538–543 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Di Liberto, G. et al. Neurons under T cell attack coordinate phagocyte-mediated synaptic stripping. Cell 175, 458–471.e19 (2018).

    Article  PubMed  Google Scholar 

  43. Murphy, K. L. et al. Synaptic alterations and immune response are sexually dimorphic in a non-pertussis toxin model of experimental autoimmune encephalomyelitis. Exp. Neurol. 323, 113061 (2020).

    Article  CAS  PubMed  Google Scholar 

  44. Hong, S. & Stevens, B. Microglia: phagocytosing to clear, sculpt, and eliminate. Dev. Cell 38, 126–128 (2016).

    Article  CAS  PubMed  Google Scholar 

  45. Hammond, J. W. et al. Complement-dependent synapse loss and microgliosis in a mouse model of multiple sclerosis. Brain Behav. Immun. 87, 739–750 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Werneburg, S. et al. Targeted complement inhibition at synapses prevents microglial synaptic engulfment and synapse loss in demyelinating disease. Immunity 52, 167–182.e7 (2020).

    Article  CAS  PubMed  Google Scholar 

  47. Tufail, Y. et al. Phosphatidylserine exposure controls viral innate immune responses by microglia. Neuron 93, 574–586.e8 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Andres, A. L. et al. NMDA receptor activation and calpain contribute to disruption of dendritic spines by the stress neuropeptide CRH. J. Neurosci. 33, 16945–16960 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Schirmer, L. et al. Neuronal vulnerability and multilineage diversity in multiple sclerosis. Nature 573, 75–82 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Tanabe, S., Saitoh, S., Miyajima, H., Itokazu, T. & Yamashita, T. Microglia suppress the secondary progression of autoimmune encephalomyelitis. Glia 67, 1694–1704 (2019).

    PubMed  Google Scholar 

  51. Holtmaat, A. et al. Long-term, high-resolution imaging in the mouse neocortex through a chronic cranial window. Nat. Protoc. 4, 1128–1144 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Schneider, C. A., Rasband, W. S. & Eliceiri, K. W. NIH Image to ImageJ: 25 years of image analysis. Nat. Methods 9, 671–675 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Rodriguez, A. et al. Automated reconstruction of three-dimensional neuronal morphology from laser scanning microscopy images. Methods 30, 94–105 (2003).

    Article  CAS  PubMed  Google Scholar 

  54. Wearne, S. L. et al. New techniques for imaging, digitization and analysis of three-dimensional neural morphology on multiple scales. Neuroscience 136, 661–680 (2005).

    Article  CAS  PubMed  Google Scholar 

  55. R Core Team. R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2014); https://www.R-project.org.

  56. Vogelstein, J. T. et al. Fast nonnegative deconvolution for spike train inference from population calcium imaging. J. Neurophysiol. 104, 3691–3704 (2010).

    Article  PubMed  PubMed Central  Google Scholar 

  57. Butler, A., Hoffman, P., Smibert, P., Papalexi, E. & Satija, R. Integrating single-cell transcriptomic data across different conditions, technologies, and species. Nat. Biotechnol. 36, 411–420 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. Mahmmoud, R. R. et al. Spatial and working memory is linked to spine density and mushroom spines. PLoS ONE 10, e0139739 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  59. Chen, J. L. et al. Pathway-specific reorganization of projection neurons in somatosensory cortex during learning. Nat. Neurosci. 18, 1101–1108 (2015).

    Article  PubMed  Google Scholar 

  60. Bacmeister, C. M. et al. Motor learning promotes remyelination via new and surviving oligodendrocytes. Nat. Neurosci. 23, 819–831 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  61. Snaidero, N. et al. Myelin membrane wrapping of CNS axons by PI(3,4,5)P3-dependent polarized growth at the inner tongue. Cell 156, 277–290 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

We thank A. Schmalz, M. Adrian, L. Schödel, B. Fiedler and Y. Hufnagel for excellent technical assistance, and D. Matzek, B. Stahr, P. Apostolopoulos, N. and M. Budak for animal husbandry. We thank the Core Facility Flow Cytometry at the Biomedical Center, Ludwig-Maximilians University Munich, for providing equipment, services and expertise. This project was supported by the Deutsche Forschungsgemeinschaft (DFG) via TRR 274/1 2020 (project nos. B03, C02, C05, Z01, Z02—ID 408885537). Work in M.Kerschensteiner’s laboratory is further financed through grants from the DFG (TRR128, projects B10 and B13, the European Research Council (ERC) under the European Union’s Seventh Framework Program, FP/2007-2013; ERC grant agreement no. 310932), the German Federal Ministry of Research and Education (BMBF; Competence Network Multiple Sclerosis), the ‘Verein Therapieforschung für MS-Kranke e.V.’. Part of this work was further supported by a research grant from Sanofi to M.Kerschensteiner. Work in T.M.’s lab is supported by the DFG (CIPSM EXC114, CRC870, Mi 694/8-1 and Mi 694/9-1, FG Immunostroke 428663564), the German Center for Neurodegenerative Diseases (DZNE) and the European Research Council (FP/2007-2013; ERC Grant Agreement no. 616791). M.Kerschensteiner and T.M. are further supported by the DFG through a common grant (Ke 774/5-1/Mi 694/7-1) and, together with R.P., by the Munich Center for Systems Neurology (SyNergy EXC 2145; project ID 390857198). M.Kerschensteiner and M.J. were supported by a grant from the German National MS Society (DMSG). M.Kerschensteiner, D.M. and T.M. were supported through grants from the Gemeinnützige Hertie Stiftung. Work in D.M.’s laboratory is further supported by the Swiss National Science Foundation (nos. PP00P3_152928 and 310030_185321), the Klaus-Tschira Foundation, Helmut Horten Foundation and the Gebert-Rüf Foundation and ERC (grant agreement no. 865026). Work in F.W.’s laboratory was financed through the DFG (CRC1286, 889; SPP 2205), BMBF (01GQ0922), GIF (906-17.1/2006), VW foundation (ZN2632), BCCN (01GQ1005B), the Ministry for Science and Culture of Lower Saxony and the Max Planck Society. N.S. is supported by a DFG research grant (Sn 149/1-1; project ID 426715780) and the Hertie Network of Excellence in Clinical Neuroscience (P1200019). A-M.S. and T.N. were supported by the ‘Förderprogramm für Forschung und Lehre’ at Ludwig-Maximilians University Munich.

Author information

Authors and Affiliations

Authors

Contributions

M. Kerschensteiner, D.M. and T.M. conceived and designed the experiments. M.J., T.J., M. Kreutzfeldt and D.M. established and characterized the c-MS model. M.J., A-M.S., E.M.U.G., V.K.-J., I.W. and S.S.S. performed and evaluated cortical pathology in situ. A-M.S., T.N. and E.M.U.G. performed and evaluated in vivo calcium imaging of spines and dendrites. N.S., J.D.F.W. and F.W. performed and/or analyzed neuronal activity patterns in vivo. N.S. performed EM analysis. R.P. and J.G. performed data analysis. D.E. and E.B. performed bioinformatics analysis. M.J. and E.B. performed flow cytometry experiments. N.H., L.W. and D.O. developed and characterized the CSF1-R antagonist. M.J., A-M.S., N.S., D.M., T.M. and M. Kerschensteiner wrote the paper.

Corresponding authors

Correspondence to Doron Merkler, Thomas Misgeld or Martin Kerschensteiner.

Ethics declarations

Competing interests

Part of this work was supported by a research grant from Sanofi to M. Kerschensteiner, who has also received speaker fees and served on advisory boards for Sanofi. N.H., L.W., J.G. and D.O. are full-time employees of Sanofi. All other authors declare no competing interests.

Additional information

Peer review information Nature Neuroscience thanks Staci Bilbo, Adema Ribic and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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

Extended data

Extended Data Fig. 1 Histopathological and clinical characterization of a mouse model of c-MS.

a, EAE score of the c-MS d3 and c-MS d14 mice. Black dots represent EAE scores before and orange dots EAE scores after cytokine injection (n = 17 mice from immunization to c-MS d3 timepoint and n = 9 mice plotted until c-MS d14;). b, Cortical spine density on d3 post cytokine injection does not show an obvious correlation with EAE score on d3 (n = 114 dendritic stretches from 17 mice; Pearson correlation, r = 0.1325, P = 0.1601). c, Spine density on d3 post cytokine injection does not correlate with average EAE score during the experiment (n = 114 dendritic stretches from 17 mice; Pearson correlation, r = 0.1192, P = 0.2066). d, Schematic of the experimental design to study histopathological changes (e-h) in the cortex of age-matched control (Ctr; black, n = 5), MOG immunized (brown, n = 5), only cytokine injected (violet, n = 6) and cortical MS model (c-MS d3, orange, n = 6) mice. e, Bielschowsky’s staining was used to analyze axonal density in each layer. Bielschowsky’s staining in layer I of Ctr and c-MS d3 mice, axonal density normalized to the Ctr group (right). f, MBP staining was used to analyze myelin density in each layer. MBP staining in layer I of Ctr and c-MS d3 mice, MBP density normalized to the Ctr group (right). g, CD3 staining was used to analyze T cells density in each layer. CD3 staining in layer I of Ctr and c-MS d3, CD3+ cell density (right). h, Mac-3 staining was used to analyze mononuclear phagocytes density in each layer. Mac-3 staining in layer I of Ctr and c-MS d3 mice, Mac-3+ cell density (right). Scale bars in e, 15 µm; f, 45 µm g and h, 25 µm. Data represented as mean and the error bars indicate s.e.m. in panels a and e-h. Data used in panels a-c are derived from Fig. 1h. RM two-way ANOVA followed by Bonferroni’s multiple comparisons test used in panels e-h. See Source Data file for individual data points and further statistical parameters. *** P < 0.001, **P < 0.01, *P < 0.05.

Source data

Extended Data Fig. 2 Cortical spine loss in c-MS mice compared to mice immunized only with MOG or injected only with cytokines.

a, Spine density along the apical dendrite of layer V pyramidal neurons in healthy control (Ctr) mice and MOG immunized animals without cytokine injection (n = 21 neurons from 7 and 8 mice in each group respectively; RM two-way ANOVA, P = 0.4907). b, Spine density along the apical dendrite of layer V pyramidal neurons in healthy control mice (n = 21 neurons from 7 mice) and non-immunized mice 3d after cytokine injection analysed ipsi- and contralateral to the injection site (n = 8 and 13 neurons from 10 mice respectively; RM two-way ANOVA, P = 0.1457). c, Spine density along the apical dendrite of layer V pyramidal neurons in healthy control (n = 21 neurons from 7 mice) and c-MS d3 animals analysed ipsi- and contralateral to the injection site (n = 17 and 11 neurons 8 mice respectively; RM two-way ANOVA, P < 0.0001, followed by Bonferroni’s multiple comparisons test, Ctr vs. c-MS ipsi: P < 0.0001, Ctr vs. c-MS contra P < 0.0001; data derived from Fig. 1g). The same Ctr group as in Fig. 1g replotted in all three graphs. Data represented as mean and the error bars indicate SEM. See Source Data file for individual data points and further statistical parameters. *** P < 0.001.

Source data

Extended Data Fig. 3 Layer V projection neurons are silenced in a model of c-MS.

a, Schematic of the experimental timeline to study longitudinal activity in apical dendrites of layer V projection neurons in the cortical MS model (c-MS) by in vivo imaging of Thy1-GCaMP6f x BiozziABH mice. b, In vivo multiphoton image of layer V apical dendrites over the course of c-MS through a cranial window; left, before cytokine injection (baseline MOG) and right 3 days (c-MS d3) post cytokine injection. Top: Merged GCaMP6f and autofluorescence channels allow the identification of apical dendrites (green only). Middle: GCaMP6f channel masked and color-coded for cytoplasmic Ca2+ events per minute. Bottom: Representative calcium activity traces displayed as delta f/f for the four apical dendrites marked in the middle panel. c, Cumulative plots representing activity for the entire population of apical dendrites for each selected time point over the course of the c-MS model. Insets: Mean activity normalized to baseline for MOG shown as mean + SEM (n = 3 c-MS mice, two-tailed paired t-test, P = 0.035). d, Heat map representation of ranked activities for single dendrites between baseline MOG and c-MS d3. e, Spine density of dendritic stretches of pyramidal layer V neurons from c-MS d3 mice used in b-d (imaged area was used for quantification) and control mice (n = 30 and n = 40 dendritic stretches from 3 and 4 mice respectively; mean + SEM, two-tailed unpaired t-test, P = 0.0038). Scale bar in b, 20 µm. See Source Data file for individual data points and further statistical parameters. **P < 0.01, *P < 0.05.

Source data

Extended Data Fig. 4 Recording the activity of single cortical neurons over time in the cytokine-injected gray matter.

a, Top: Schematic of experimental design for longitudinal in vivo imaging of Ca2+ transients in layer II/III somatosensory neurons upon injection of cytokines in healthy animals, using the GCaMP6s Ca2+ indicator delivered via viral gene transfer (AAV1.hSyn1.mRuby2.GCaMP6s). Middle, Bottom: Longitudinal in vivo multiphoton images of the same layer II/III neurons before and after cytokine injection; from left to right respectively: baseline, 3 days, 10 days and 17 days post cytokine injection. Middle: Grayscale images of GCaMP6s channel masked and color-coded for cytoplasmic Ca2+ events per minute. Bottom: Representative Ca2+ activity traces displayed as delta f/f for the neurons marked in the left panel. b, Cumulative plots of the neuronal activity for the entire population of neurons investigated at different timepoints after cytokine injection in healthy animals. Inset: Mean neuronal activity normalized to baseline for each time point shown as mean + s.e.m. (n = 4 cytokine injected mice, tested with Shapiro-Wilk test and one-way ANOVA). c, Heat map representation of the single neurons’ activities before and after cytokine injection. Scale bar in a, 20 µm. See Source Data file for individual data points and further statistical parameters.

Source data

Extended Data Fig. 5 Myelination recovers more slowly than neuronal activity.

a-c, Top: Schematic of experimental design for longitudinal in vivo SCoRe imaging of myelin within the top 50 µm of layer I in the somatosensory cortex of sham injected mice (a), c-MS mice (b) and in cytokine injected non-immunized mice (c). a-c, Bottom: Longitudinal in vivo SCoRe images of the same layer I area. From left to right respectively: (a) baseline, 3 days, 10 days and 17 days post sham injection. (b), MOG baseline, 3 days, 10 days and 17 days post cytokine injection. (c) baseline, 3 days, 10 days and 17 days post cytokines injection. d, Percentage of SCoRe signal compared to baselines for sham and cytokine only injection and to baseline MOG for the c-MS model, 3 days, 10 days and 17 days post injection shown as mean ± s.e.m. (n = 3 for sham, cytokine only and c-MS mice, Shapiro-Wilk test and one-way ANOVA followed by Tukey’s multiple comparisons test has been performed). e, Electron micrographs of the cortical layer I of sham injected (left) and c-MS mice (right) showing myelin sheath (black arrowheads) 3 days post injection. f, Myelin sheath density in layer I of somatosensory cortex in sham injected and c-MS mice at 3 days and 10 days post injection shown as mean ± SEM (tested in n = 4 sham injected and n = 4 c-MS mice for day 3 and n = 5 sham injected and n = 3 c-MS mice for day 10, Shapiro-Wilk test and unpaired two tailed t-test). See Source Data file for individual data points and further statistical parameters. Scale bar in a, b, c, 20 µm; e, 1 µm. ***P < 0.001, *P < 0.05.

Source data

Extended Data Fig. 6 Ratiometric imaging of calcium levels in the somata and dendrites of cortical neurons.

a, In vivo multiphoton projection images of layer II/III neuronal somata and their Ca2+ levels in c-MS mice. Neurons were labelled using the viral vector AAV1.hSyn.mRuby2.GCaMPs (see Methods), allowing for ratiometric measurements (GCamp6s/mRuby) of baseline neuronal Ca2+ concentration. Grayscale images of GCamp6s channel (top), ratiometric (GCamp6s/mRuby) images masked and color-coded for cytoplasmic Ca2+ (bottom). b, In vivo multiphoton projection images of apical tuft dendrites and their Ca2+ levels in acute c-MS (d2/d3) mice, labelled with AAV1.hSyn1.Twitch2b. Grayscale images of YFP channel (top), ratiometric (YFP/CFP) images masked and color-coded for cytoplasmic Ca2+ (bottom). Example of a high Ca2+ dendrite exhibiting swellings (arrowheads). c, Ca2+ concentration of single somata in control (sham injection, ‘Ctr’) and c-MS (d3) mice, plotted as GCamp6s/mRuby channel ratios normalized to control mean. 95% confidence interval 0.99-1.01 for control mean and 0.86-0.89 for c-MS mean. Top: Percentage of somata per animal with Ca2+ concentration > 3 s.d. above control mean, shown as mean ± s.e.m. (n = 2 control and n = 3 c-MS mice). d, Ca2+ concentration of single dendrites in healthy control (‘Ctr’) and c-MS d3 animals, plotted as YFP/CFP channel ratios normalized to control mean. 95% confidence interval 0.74-0.78 for control mean and 0.75-0.80 for c-MS mean. Top: Percentage of dendrites per animal with Ca2+ concentration >3 s.d. above control mean, shown as mean ± s.e.m. (tested per animal in n = 8 control and n = 17 c-MS mice, two-tailed Mann-Whitney test after Shapiro-Wilk test indicated non-normal distribution, P = 0.1751). Scale bars in a, b, 10 µm. See Source Data file for individual data points and further statistical parameters.

Source data

Extended Data Fig. 7 Temporal and spatial characteristics of monocyte infiltration and microglial activation in the c-MS model.

a,b, Confocal projection images of cortex in healthy control (Ctr, left) and c-MS d3 (c-MS d3, right) CX3CR-1GFP x Ccr2RFP x BiozziABH mice. a, Immunostaining for MHCII (red), as a marker of microglial activation, overlayed on the GFP signal of resident microglia (greyscale). b, RFP signal of infiltrating phagocytes shown in red. c, Left: Percentages of activated microglia (% MHCII positive/ all CX3CR-1GFP cells) in healthy control (Ctr), only immunized (MOG), only cytokine injected (Cyto) and c-MS d3 mice. Middle: Time course of microglial activation (in %) 3 days, 7 days and 21 days after induction of cortical MS model (d3, d7, d21). Right: Distribution of microglial activation (in %) within the layers of the cortical column (Layer I, Layer II-IV and Layer V) and between injected (ipsilateral, ‘ipsi’) and non-injected hemisphere (contralateral, ‘contra’). c-MS d3 data plotted in all 3 panels. Shown as mean + s.e.m. where applicable (n = 2 control, n = 2 MOG, n = 3 Cyto, n = 3 c-MS d3 mice; one-way ANOVA, P < 0.0001, followed by Bonferroni’s multiple comparisons test, P < 0.0001 for all comparisons). d, Left: Numbers of infiltrating phagocytes (Ccr2RFP cells) per standardized volume in healthy control (Ctr), only MOG immunized (MOG), only cytokine injected (Cyto) and c-MS d3 mice. Middle: Time course of phagocyte infiltration 3 days, 7 days and 21 days after induction of cortical MS model (d3, d7, d21). Right: Distribution of phagocyte infiltration within the layers of the cortical column (Layer I, Layer II-IV and Layer V) and between injected (ipsilateral) and non-injected hemisphere (contralateral). c-MS d3 data plotted in all 3 panels. Shown as mean + s.e.m. where applicable (n = 2 naive, n = 2 only MOG immunized, ‘MOG’, n = 3 only cytokine injected, ‘Cyto’, n = 3 c-MS d3 mice; one-way ANOVA, P < 0.0001, followed by Bonferroni’s multiple comparisons test, P < 0.0001 for d3 vs. d21 and d7 vs. d21, P = 0.0585 for d3 vs. d7). e, Color-coded spatial matrix (11 × 9 squares) representing microglial activation (in %) of healthy control (Ctr, n = 3, left) and c-MS d3 mice (n = 3, right) mice ipsi- and contralateral to the cytokine injection site. f, Color-coded matrix showing numbers of infiltrating phagocytes (Iba-1+, CX3CR-1GFP-negative cells) in healthy control (Ctr, n = 3, left) and c-MS d3 mice (n = 3, right) ipsi- and contralateral to injection site. Scale bar in a (applies also to b) 100 µm. See Source Data file for individual data points and further statistical parameters.***P < 0.001.

Source data

Extended Data Fig. 8 In vitro and in vivo effects of CSF1-R inhibitor treatment on CNS phagocytes.

a, Isolated primary murine microglia (untreated) show elevated MCP-1 (CCL2) after treatment with CSF-1. While adding DMSO does not change the levels of MCP-1, CSF1-R inhibitor treatment decreases the levels of MCP-1 in primary murine cells (n = 3 in all groups). b, Isolated primary murine microglia (untreated) show elevated Il-12p40 after treatment with LPS. While adding DMSO does not change the levels of Il-12p40, CSF1-R inhibitor decreases the levels of Il-12p40 in primary murine cells (n = 6 for untreated cells and n = 5 for the other groups). c-e, FACS analysis of cell populations in brains of healthy controls (Ctr), MOG immunized and acute c-MS model mice treated with vehicle or CSF1-R inhibitor (n = 3 mice were analyzed for healthy control and MOG immunized groups, n = 10 mice were analyzed in c-MS model groups): (c) shows the proportion of CD45int/ CD11bint cells (left) and their expression of CD40, MHCII and CD86 (right) (d) shows the proportion of CD45high/ CD11bhigh/ Ccr2neg cells (left) and their expression of CD40, MHCII and CD86 (right), (e) shows the proportion of CD45high/ CD11bhigh/ Ccr2pos cells (left) and their expression of CD40, MHCII and CD86 (right). f, Different doses of CSF1-R inhibitor show no decrease of the phagocytic activity of unstimulated primary mouse microglia, measured by uptake of pHrodo red-labeled synaptoneurosomes (n = 3 control wells, n = 4 wells for all other groups). g, CSF1 stimulation of primary mouse microglia leads to increased phagocytic activity. Treatment with 500 nM of CSF1-R inhibitor abrogated this effect (n = 4 wells per group). One-way ANOVA followed by Bonferroni’s multiple comparisons test in a-b; Data represented as mean and the error bars indicate s.e.m. One way ANOVA followed by Tukey’s multiple comparisons test in left panels and two-way ANOVA in right panels of c-e, two-way ANOVA in f-g. See Source Data file for individual data points and further statistical parameters.*** P < 0.001, ** P < 0.01, * P < 0.05.

Source data

Extended Data Fig. 9 Expression pattern of CSF1-R and its ligands in human brain tissue.

a, t-Stochastic neighbor embedding (t-SNE) with subsequent cluster analysis of single-nucleus RNA-sequencing results (48,919 single nucleus profiles) from cortical gray matter and adjacent white matter of 12 progressive MS tissue blocks and 9 control tissue blocks published in Schirmer et al49. Distinct clusters are color-coded. b, t-SNE plots with relative gene expression of CSF1R and its ligands CSF1 and interleukin 34 (IL34) highlighted in red. c, t-SNE plots with relative gene expression of marker genes for identification of cell-specific clusters (as used in Schirmer et al.) highlighted in red. d, Graphical representation of the expression of CSF1R, CSF1 and IL34 in selected cell clusters in MS and control samples. The diameter of each dot encodes the percentage of cells that express the respective gene within each cluster (the corresponding reference dots are shown in black on the bottom) and was calculated separately for cell clusters mapping to MS or control cases. The red color encodes the relative expression level of a given gene in all cells within the cluster.

Supplementary information

Supplementary Information

Supplementary Figs. 1–3.

Reporting Summary

Supplementary Video

Activity of single cortical neurons over the course of the c-MS model. Video generated using ImageJ software from 15-Hz recordings and displayed at 100 frames s−1 with a walking average of 3 (60-s recordings per timepoint).

Supplementary Software 1

The codes for the graphic user interface used to semiautomatically define the ROIs, and automatically detect the calcium events and generate the correlation matrices.

Supplementary Software 2

The codes for the reanalysis of the Schirmer et al.49 snRNA-seq data.

Source data

Source Data Fig. 1

Statistical source data.

Source Data Fig. 2

Statistical source data.

Source Data Fig. 3

Statistical source data.

Source Data Fig. 4

Statistical source data.

Source Data Fig. Fig. 5

Statistical source data.

Source Data Fig. Fig. 6

Statistical source data.

Source Data Extended Data Fig. 1

Statistical source data.

Source Data Extended Data Fig. 2

Statistical source data.

Source Data Extended Data Fig. 3

Statistical source data.

Source Data Extended Data Fig. 4

Statistical source data.

Source Data Extended Data Fig. 5

Statistical source data.

Source Data Extended Data Fig. 6

Statistical source data.

Source Data Extended Data Fig. 7

Statistical source data.

Source Data Extended Data Fig. 8

Statistical source data.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Jafari, M., Schumacher, AM., Snaidero, N. et al. Phagocyte-mediated synapse removal in cortical neuroinflammation is promoted by local calcium accumulation. Nat Neurosci 24, 355–367 (2021). https://doi.org/10.1038/s41593-020-00780-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41593-020-00780-7

This article is cited by

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