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Brain exposure to SARS-CoV-2 virions perturbs synaptic homeostasis

Abstract

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is associated with short- and long-term neurological complications. The variety of symptoms makes it difficult to unravel molecular mechanisms underlying neurological sequalae after coronavirus disease 2019 (COVID-19). Here we show that SARS-CoV-2 triggers the up-regulation of synaptic components and perturbs local electrical field potential. Using cerebral organoids, organotypic culture of human brain explants from individuals without COVID-19 and post-mortem brain samples from individuals with COVID-19, we find that neural cells are permissive to SARS-CoV-2 to a low extent. SARS-CoV-2 induces aberrant presynaptic morphology and increases expression of the synaptic components Bassoon, latrophilin-3 (LPHN3) and fibronectin leucine-rich transmembrane protein-3 (FLRT3). Furthermore, we find that LPHN3-agonist treatment with Stachel partially restored organoid electrical activity and reverted SARS-CoV-2-induced aberrant presynaptic morphology. Finally, we observe accumulation of relatively static virions at LPHN3–FLRT3 synapses, suggesting that local hindrance can contribute to synaptic perturbations. Together, our study provides molecular insights into SARS-CoV-2–brain interactions, which may contribute to COVID-19-related neurological disorders.

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Fig. 1: SARS-CoV-2 infection of cerebral organoids induces an increase in synapses protein expression.
Fig. 2: SARS-CoV-2 exposure increases the number of presynaptic structures in cerebral organoids.
Fig. 3: SARS-CoV-2 exposure increases presynaptic components in human brain samples.
Fig. 4: LPHN3 is up-regulated upon SARS-CoV-2 infection and is associated with synapses dysregulation.
Fig. 5: SARS-CoV-2 virions accumulate at LPHN3/FLRT3-containing synapse.

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Data availability

All data are available in the main text, extended data and Supplementary Information. The plasmid coding for N-mNeonGreen and N-mRuby3 from SARS-CoV-2 is available on Addgene (number 170467 and number 170466, respectively). The mass spectrometry proteomic data have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository72 with the dataset identifier PXD036485. Source data are provided with this paper.

Code availability

The algorithm to identify infected versus non-infected organoids is available through GitHub (https://github.com/WillyLutz/electrical-analysis-sars-cov-2)71 or upon request.

References

  1. Gavriatopoulou, M. et al. Organ-specific manifestations of COVID-19 infection. Clin. Exp. Med. 20, 493–506 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Salinas, S. & Simonin, Y. [Neurological damage linked to coronaviruses: SARS-CoV-2 and other human coronaviruses]. Med.Sci. (Paris) 36, 775–782 (2020).

    Article  PubMed  Google Scholar 

  3. Koralnik, I. J. & Tyler, K. L. COVID-19: a global threat to the nervous system. Ann. Neurol. 88, 1–11 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Iadecola, C., Anrather, J. & Kamel, H. Effects of COVID-19 on the nervous system. Cell 183, 16–27 e11 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Helms, J. et al. Delirium and encephalopathy in severe COVID-19: a cohort analysis of ICU patients. Crit. Care 24, 491 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  6. Varatharaj, A. et al. Neurological and neuropsychiatric complications of COVID-19 in 153 patients: a UK-wide surveillance study. Lancet Psychiatry 7, 875–882 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  7. Rogers, J. P. et al. Psychiatric and neuropsychiatric presentations associated with severe coronavirus infections: a systematic review and meta-analysis with comparison to the COVID-19 pandemic. Lancet Psychiatry 7, 611–627 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  8. Nagu, P., Parashar, A., Behl, T. & Mehta, V. CNS implications of COVID-19: a comprehensive review. Rev. Neurosci. 32, 219–234 (2021).

    Article  CAS  PubMed  Google Scholar 

  9. Baker, H. A., Safavynia, S. A. & Evered, L. A. The ‘third wave’: impending cognitive and functional decline in COVID-19 survivors. Br. J. Anaesth. 126, 44–47 (2021).

    Article  CAS  PubMed  Google Scholar 

  10. Taquet, M., Geddes, J. R., Husain, M., Luciano, S. & Harrison, P. J. 6-month neurological and psychiatric outcomes in 236 379 survivors of COVID-19: a retrospective cohort study using electronic health records. Lancet Psychiatry 8, 416–427 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  11. Hellmuth, J. et al. Persistent COVID-19-associated neurocognitive symptoms in non-hospitalized patients. J. Neurovirol. 27, 191–195 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Douaud, G. et al. SARS-CoV-2 is associated with changes in brain structure in UK Biobank. Nature https://doi.org/10.1038/s41586-022-04569-5 (2022)

  13. Blazhenets, G. et al. Slow but evident recovery from neocortical dysfunction and cognitive impairment in a series of chronic COVID-19 patients. J. Nucl. Med. 62, 910–915 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Taquet, M. et al. Neurological and psychiatric risk trajectories after SARS-CoV-2 infection: an analysis of 2-year retrospective cohort studies including 1 284 437 patients. Lancet Psychiatry 9, 815–827 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  15. Monje, M. & Iwasaki, A. The neurobiology of long COVID. Neuron 110, 3484–3496 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Stein, S. R. et al. SARS-CoV-2 infection and persistence in the human body and brain at autopsy. Nature 612, 758–763 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Ramani, A., Pranty, A. I. & Gopalakrishnan, J. Neurotropic effects of SARS-CoV-2 modeled by the human brain organoids. Stem Cell Rep. 16, 373–384 (2021).

    Article  CAS  Google Scholar 

  18. Song, E. et al. Neuroinvasion of SARS-CoV-2 in human and mouse brain. J. Exp. Med. 218, e20202135 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Qian, X., Song, H. & Ming, G. L. Brain organoids: advances, applications and challenges. Development 146, dev166074 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Hodge, R. D. et al. Conserved cell types with divergent features in human versus mouse cortex. Nature 573, 61–68 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Brola, W. & Wilski, M. Neurological consequences of COVID-19. Pharmacol. Rep. 74, 1208–1222 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  22. Antony, A. R. & Haneef, Z. Systematic review of EEG findings in 617 patients diagnosed with COVID-19. Seizure 83, 234–241 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  23. Kubota, T., Gajera, P. K. & Kuroda, N. Meta-analysis of EEG findings in patients with COVID-19. Epilepsy Behav. https://doi.org/10.1016/j.yebeh.2020.107682 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  24. Lin, L. et al. Electroencephalographic abnormalities are common in COVID-19 and are associated with outcomes. Ann. Neurol. 89, 872–883 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Yang, A. C. et al. Dysregulation of brain and choroid plexus cell types in severe COVID-19. Nature 595, 565–571 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Samudyata et al. SARS-CoV-2 promotes microglial synapse elimination in human brain organoids. Mol. Psychiatry https://doi.org/10.1038/s41380-022-01786-2 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  27. Partiot, E. et al. Organotypic culture of human brain explants as a preclinical model for AI-driven antiviral studies. EMBO Mol. Med. https://doi.org/10.1038/s44321-024-00039-9 (2024).

    Article  PubMed  PubMed Central  Google Scholar 

  28. O’Sullivan, M. L. et al. FLRT proteins are endogenous latrophilin ligands and regulate excitatory synapse development. Neuron 73, 903–910 (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  29. Sando, R. & Sudhof, T. C. Latrophilin GPCR signaling mediates synapse formation. Elife 10, e65717 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Rothe, J. et al. Involvement of the adhesion GPCRs latrop–hilins in the regulation of insulin release. Cell Rep. 26, 1573–1584 e1575 (2019).

    Article  PubMed  Google Scholar 

  31. Ramani, A. et al. SARS-CoV-2 targets neurons of 3D human brain organoids. EMBO J. 39, e106230 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Ferren, M. et al. Hamster organotypic modeling of SARS-CoV-2 lung and brainstem infection. Nat. Commun. 12, 5809 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Bauer, L. et al. The neuroinvasiveness, neurotropism, and neurovirulence of SARS-CoV-2. Trends Neurosci. 45, 358–368 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Zivaljic, M., et al. Poor sensitivity of iPSC-derived neural progenitors and glutamatergic neurons to SARS-CoV-2. Preprint at bioRxiv https://doi.org/10.1101/2022.07.25.501370 (2022)

  35. Koopmans, F. et al. SynGO: an evidence-based, expert-curated knowledge base for the synapse. Neuron 103, 217–234 e214 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Beckman, D. et al. SARS-CoV-2 infects neurons and induces neuroinflammation in a non-human primate model of COVID-19. Cell Rep. 41, 111573 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Xie, X. et al. An infectious cDNA clone of SARS-CoV-2. Cell Host Microbe 27, 841–848 e843 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Corman, V. M. et al. Detection of 2019 novel coronavirus (2019-nCoV) by real-time RT-PCR. Euro Surveill. 25, 2000045 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  39. Fernandez-Rodriguez, A. et al. Post-mortem microbiology in sudden death: sampling protocols proposed in different clinical settings. Clin. Microbiol. Infect. 25, 570–579 (2019).

    Article  CAS  PubMed  Google Scholar 

  40. Burbach, J. P. H. & Meijer, D. H. Latrophilin’s social protein network. Front. Neurosci. 13, 643 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  41. Sando, R., Jiang, X. & Sudhof, T. C. Latrophilin GPCRs direct synapse specificity by coincident binding of FLRTs and teneurins. Science 363, eaav7969 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Bielarz, V. et al. Susceptibility of neuroblastoma and glioblastoma cell lines to SARS-CoV-2 infection. Brain Res. 1758, 147344 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Fontes-Dantas, F. L. et al. SARS-CoV-2 spike protein induces TLR4-mediated long-term cognitive dysfunction recapitulating post-COVID-19 syndrome in mice. Cell Rep. 42, 112189 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. May, D. G. et al. A BioID-derived proximity interactome for SARS-CoV-2 proteins. Viruses https://doi.org/10.3390/v14030611 (2022).

  45. Bakhache, W., et al. Pharmacological perturbation of intracellular dynamics as a SARS-CoV-2 antiviral strategy. Preprint at bioRxiv https://doi.org/10.1101/2021.09.10.459410 (2021)

  46. Prasad, V. & Bartenschlager, R. A snapshot of protein trafficking in SARS-CoV-2 infection. Biol. Cell. https://doi.org/10.1111/boc.202200073 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  47. Jouvenet, N., Goujon, C. & Banerjee, A. Clash of the titans: interferons and SARS-CoV-2. Trends Immunol. 42, 1069–1072 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Silva, M. M. et al. MicroRNA-186-5p controls GluA2 surface expression and synaptic scaling in hippocampal neurons. Proc. Natl Acad. Sci. USA 116, 5727–5736 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Schanzenbacher, C. T., Langer, J. D. & Schuman, E. M. Time- and polarity-dependent proteomic changes associated with homeostatic scaling at central synapses. Elife 7, e33322 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  50. Dubes, S. et al. miR-124-dependent tagging of synapses by synaptopodin enables input-specific homeostatic plasticity. EMBO J. 41, e109012 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Sun, Z. et al. Mass spectrometry analysis of newly emerging coronavirus HCoV-19 spike protein and human ACE2 reveals camouflaging glycans and unique post-translational modifications. Engineering 7, 1441–1451 (2021).

    Article  CAS  PubMed  Google Scholar 

  52. Lorenzo, R. et al. Deamidation drives molecular aging of the SARS-CoV-2 spike protein receptor-binding motif. J. Biol. Chem. 297, 101175 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Zhao, J., Li, J., Xu, S. & Feng, P. Emerging roles of protein deamidation in innate immune signaling. J. Virol. 90, 4262–4268 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Arcos-Burgos, M. et al. A common variant of the latrophilin 3 gene, LPHN3, confers susceptibility to ADHD and predicts effectiveness of stimulant medication. Mol. Psychiatry 15, 1053–1066 (2010).

    Article  CAS  PubMed  Google Scholar 

  55. Lange, M. et al. The ADHD-susceptibility gene lphn3.1 modulates dopaminergic neuron formation and locomotor activity during zebrafish development. Mol. Psychiatry 17, 946–954 (2012).

    Article  CAS  PubMed  Google Scholar 

  56. Regan, S. L. et al. A novel role for the ADHD risk gene latrophilin-3 in learning and memory in Lphn3 knockout rats. Neurobiol. Dis. 158, 105456 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Domene, S. et al. Screening of human LPHN3 for variants with a potential impact on ADHD susceptibility. Am. J. Med. Genet. B 156B, 11–18 (2011).

    Article  Google Scholar 

  58. Orsini, C. A. et al. Behavioral and transcriptomic profiling of mice null for Lphn3, a gene implicated in ADHD and addiction. Mol. Genet. Genomic Med. 4, 322–343 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Wallis, D. et al. Initial characterization of mice null for Lphn3, a gene implicated in ADHD and addiction. Brain Res. 1463, 85–92 (2012).

    Article  CAS  PubMed  Google Scholar 

  60. Li, J. et al. Alternative splicing controls teneurin-latrophilin interaction and synapse specificity by a shape-shifting mechanism. Nat. Commun. 11, 2140 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  61. Giandomenico, S. L. et al. Cerebral organoids at the air–liquid interface generate diverse nerve tracts with functional output. Nat. Neurosci. 22, 669–679 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  62. Trujillo, C. A. et al. Complex oscillatory waves emerging from cortical organoids model early human brain network development. Cell Stem Cell 25, 558–569 e557 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  63. Chaumont, H. et al. Long-term outcomes after NeuroCOVID: a 6-month follow-up study on 60 patients. Rev. Neurol. 178, 137–143 (2022).

    Article  CAS  PubMed  Google Scholar 

  64. Coulter, M. E. et al. The ESCRT-III protein CHMP1A mediates secretion of sonic hedgehog on a distinctive subtype of extracellular vesicles. Cell Rep. 24, 973–986 e978 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  65. Gee, G. V., Manley, K. & Atwood, W. J. Derivation of a JC virus-resistant human glial cell line: implications for the identification of host cell factors that determine viral tropism. Virology 314, 101–109 (2003).

    Article  CAS  PubMed  Google Scholar 

  66. Rebendenne, A. et al. SARS-CoV-2 triggers an MDA-5-dependent interferon response which is unable to control replication in lung epithelial cells. J. Virol. 95, e02415–e02420 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  67. Bouyssie, D. et al. Proline: an efficient and user-friendly software suite for large-scale proteomics. Bioinformatics 36, 3148–3155 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  68. Wieczorek, S., Combes, F., Borges, H. & Burger, T. Protein-level statistical analysis of quantitative label-free proteomics data with ProStaR. Methods Mol. Biol. 1959, 225–246 (2019).

    Article  CAS  PubMed  Google Scholar 

  69. Hulstaert, N. et al. ThermoRawFileParser: modular, scalable, and cross-platform RAW file conversion. J. Proteome Res. 19, 537–542 (2020).

    Article  CAS  PubMed  Google Scholar 

  70. Degroeve, S., et al. ionbot: a novel, innovative and sensitive machine learning approach to LC-MS/MS peptide identification. Preprint at bioRxiv https://doi.org/10.1101/2021.07.02.450686 (2021).

  71. Lutz, W. WillyLutz/electrical-analysis-sars-cov-2. GitHub https://github.com/WillyLutz/electrical-analysis-sars-cov-2 (2024).

  72. Perez-Riverol, Y. et al. The PRIDE database resources in 2022: a hub for mass spectrometry-based proteomics evidences. Nucleic Acids Res. 50, D543–D552 (2022).

    Article  CAS  PubMed  Google Scholar 

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Acknowledgements

Image acquisitions in BSL-2 environment were performed at the MRI imaging facility (CNRS, Univ Montpellier), which also provided advice and training. All infections and live cell imaging using replication-competent SARS-CoV-2 were performed at the Center for the study of infectious diseases and anti-infectious pharmacology (CEMIPAI) BSL-3 facility (CNRS, Univ Montpellier). We acknowledge S. van der Werf (Institut Pasteur) for providing us very early with the wild-type SARS-CoV-2 strains. We also acknowledge the World Reference Center for Emerging Viruses and Arboviruses and University of Texas Medical Branch (UTMB) investigator P. Y. Shi for providing the SARS-CoV-2 mNeonGreen and NanoLuc reporter viruses. We thank C. Bernou for participating in the preparation of OPAB (IRIM, CNRS), S. Lebrun (IRIM, CNRS) and D. Brychka (IRIM, CNRS) for contributing to cerebral organoid production for the revision stage of this article, and all the members of the Gaudin Lab for helpful discussions. Funders: CNRS INSB (R.G.), Agence Nationale de la Recherche ANR-20-CE15-0019-01 (R.G.), Agence Nationale de la Recherche ANR-21-CE33-0007-03 (R.G., S.C. and G.G.), Agence Nationale de la Recherche ANR-22-CE15-0007-01 (R.G.), Health, Biology and Chemical Sciences (CBS2) Montpellier doctoral school (E.P.), Agence Nationale de la Recherche ANR-10-INBS-08-03; Proteomics French Infrastructure (ProFI) FR2048 (C.C.), Isite MUSE (Montpellier University of Excellence) (B.C.), European Union’s Horizon 2020 Programme (H2020-INFRAIA-2018-1) (823839) (L.M.), Research Foundation Flanders (FWO) (G028821N) (L.M.), Research Foundation Flanders (FWO) (1S57123N) (T.C.), Ghent University Concerted Research Action (BOF21/GOA/033) (L.M.), Fondation pour la Recherche Médicale, MIE202207016212 (E.P., R.G.), Fondation pour la Recherche Médicale, SPF202110014043 (Y.B.), Labex NUMEV–SATIS Project (B.G.). The funders had no role in the study design, data collection and analysis, decision to publish or preparation of the manuscript.

Author information

Authors and Affiliations

Authors

Contributions

Conceptualization: E.P. and R.G. Methodology: E.P., A.H., W.L., T.C., F.D., M.S.D., Y.B., J.R.E.R., B.G., J.B., L.M., F.M.J.J., B.C., C.C., S.C., G.G. and R.G. Investigation: E.P., A.H., F.D., W.L., M.S.D., Y.B., J.R.E.R., J.B., D.C., L.A., M.L., C.C., S.C., G.G. and R.G. Analysis: E.P., A.H., F.D., W.L., T.C., L.M., M.S.D., Y.B., J.B., D.C., L.A., M.L., V.R., C.C., S.C., G.G. and R.G. Supervision: L.M., C.C., S.C., G.G., R.G. Writing—original draft: R.G. Writing—review and editing: E.P., A.H., T.C., L.M., M.S.D., D.C., C.C., S.C., G.G. and R.G.

Corresponding author

Correspondence to Raphael Gaudin.

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Extended data

Extended Data Fig. 1 Characterization of SARS-CoV-2-exposed cerebral organoids.

(a) Three-dimensional imaging of a cerebral organoid differentiated for 45 days stained for neural progenitor (Pax6, green), and neurons (CTIP2, purple). (b–d) Cerebral organoids differentiated for 45 days were mock-infected or infected for 10 days (B) or at indicated time (C-D) with SARS-CoV-2 at 105 pfu/organoid in the presence or absence of 10 μM Remdesivir. RNA extraction and RT-qPCR were performed and the data corresponds to SARS-CoV-2 RNA levels using the N1 primers and normalized by RPL27 (C) from n of 2 organoids per condition in duplicates or to SARS-CoV-2 RNA levels using the sgRNA E primers and normalized by GAPDH (D) from n of 2 organoids per condition in duplicates. Data are presented as mean values +/− SD (C) or +/− SEM (D). (C) Two-tailed p value (Kruskal-Wallis test) was 0.0045 (**) or 0.3268 (ns). (D) Two-tailed p value from paired t test was< 0.0385 (*). (e–i) Cerebral organoids differentiated for 45 days were mock-infected or infected for 10 days with SARS-CoV-2 at 105 pfu/organoid. (E) The organoid supernatant or dissociated organoids were used for titration by plaque assay on Vero E6 cells. The labels pure to -6 correspond to log10 dilution factors. (f) LDH release was measured in the supernatant of the organoids. The data are from a n of two organoids per condition in duplicates and shows no toxicity in any condition, except for Ctrl, a positive control used to account for maximum cytotoxicity. Data are presented as mean values +/− SD. (g) Cerebral organoids were fixed, permeabilized and stained with the anti-cleaved Caspase 3 antibody (orange, a cell death marker, and Dapi (blue). The micrographs show marginal apoptotic staining in both conditions. (h) The organoid size was measured every 2 days for 10 days. Data are presented as mean values +/− SD and each dot corresponds to single organoids with n = 6 organoid per time point. No significant difference in size was found between mock and SARS-CoV-2 infected organoids over time. (i) Cerebral organoids differentiated for 45 days were and stain for Spike and the neuronal marker CTIP2. The micrograph and insets show CTIP2-positive infected cells. The pie chart made from 3 fields of view shows that ≈ 90% of the infected cells were positive for CTIP2.

Source data

Extended Data Fig. 2 Single-organoid proteomic analysis (associated to Supplementary Table 1 and 2).

Cerebral organoids differentiated for 45 days were mock-infected or infected for 10 days with SARS-CoV-2 at 105 pfu or 106 pfu per organoid and processed for single-organoid differential proteomics comparing infected organoids to their non-infected counterparts using nanoLC-MS/MS. (a) Protein network analysis using GSEA of the upregulated cellular component upon infection of cerebral organoids. (b–e) Patterns of differential post-translational modifications (PTM) in mock-infected (B), and SARS-CoV-2-infected samples at 105 pfu (C) or 106 pfu (D) were obtained by averaging relative quantifications.

Extended Data Fig. 3 SARS-CoV-2 infection of cerebral organoids containing infiltrated monocytes.

(a) Cerebral organoids differentiated for 45 days were cocultured for 7 days with human primary monocytes and stained for Iba-1 (orange) and Dapi (purple). The micrograph is representative of fields of views originating from 2 organoids. (b) Cerebral organoids differentiated for 45 days were cocultured for 7 days with human primary monocytes and Mock infected for 10 days. The organoids were stained for CD68, CD163 or CD206 (cyan) and Iba-1 (purple). Each staining panel represents one organoid. (c) Cerebral organoids differentiated for 45 days were cocultured for 7 days in the absence or presence of human primary monocytes, infected for 3 or 10 days with SARS-CoV-2 at 105 pfu and stained for Bassoon.

Extended Data Fig. 4 SARS-CoV-2 infection of human post mortem brain slices.

OPAB were mock-infected or infected with SARS-CoV-2 at 105 pfu/well. (a) Three-dimensional snapshots of a slice infected with a replication-competent SARS-CoV-2 mNeonGreen reporter virus. (b) RNA extraction and RT-qPCR were performed and the data corresponds to SARS-CoV-2 sgRNA levels normalized by GAPDH housekeeping gene from n of 3 OPAB from 2 donors. Data are presented as mean values +/− SEM. Two-tailed p value from unpaired t test was 0.0483 (*). (c-d) Infection kinetics of OPAB derived from the frontal lobe (C) and parietal lobe (D) using a replication-competent SARS-CoV-2 NanoLuciferase (NLuc) reporter virus. Each dot corresponds to a single slice and the symbols discriminate between the donors. Data are presented as mean values +/− SD, with n of 2 OPAB from 3 donors. (e) Cytotoxicity is measured for each condition from the parietal lobe from one donor using an LDH release luminescence assay. Data are presented as mean values +/− SD. nd: not determined. (f) Three-dimensional imaging of neurons (MAP2) from human brain slices exposed to SARS-CoV-2. The neurons from SARS-CoV-2-exposed brain slices retain densely aligned organization.

Source data

Extended Data Fig. 5 Characterization of the brain features of COVID-19 patients without neurological symptoms.

(a) RT-qPCR of the blood and cerebrospinal fluid (CSF) of 4 COVID-19 patients using two anti SARS-CoV-2 probe sets (IP2 and IP4). GAPDH was also acquired. Color coding shows blood in red and CSF in blue. ND: not determined. (b) Imaging of Hematoxylin and Eosin (H&E), GFAP and CD3 stainings of the frontal lobe of 6 COVID-19 patients using 10X magnification. (c) RT-qPCR from temporal lobe of 6 COVID-19 patient or 3 non-COVID-19 patients were performed in duplicates to evaluate the presence of astrocytes. The graph corresponds to GFAP mRNA expression normalized to GAPDH mRNA. Data are presented as mean values +/− SD. (d, e) Imaging of CD163 (D) and CD68 (E) staining of the frontal lobe of COVID-19 patients using 10X magnification. Scale bar = 100 µm. (f-g) RNA extraction and RT-qPCR from the temporal lobe of COVID-19 or individuals without COVID-19 (control) were performed and the data corresponds to the mRNA levels coding for GluA2 (F), or VTI1B (G) normalized by GAPDH. Each dot corresponds to an individual measurement obtained from at least two individual explants collected from 3 non-COVID-19 (control) and 6 COVID-19 patients in duplicates. Data are presented as mean values +/− SD. Two-tailed p value from unpaired t test was 0.026 (**) or 0.4584 (ns). (h) OPAB were mock-infected or infected with the original strain or the delta strain of SARS-CoV-2 at 105 pfu/well. The graph shows the distribution of Bassoon object volumes for each condition. Each dot corresponds to single Bassoon objects obtained from a n of 3 OPAB. Two-tailed p value from unpaired t test was < 0.0001 (****) or 0.1879 (ns).

Source data

Extended Data Fig. 6 RNA expression upregulation of synapse-coding genes in COVID-19 patients.

RT-qPCR from temporal lobe of 6 COVID-19 patient or 3 non-COVID-19 patient were performed and the data corresponds to the mRNA level normalized by GAPDH of Bassoon (a), PSD95 (b), GluA2 (c), VTI1B (d), LPHN3 (E) and FLRT3 (f). Data are presented as mean values +/− SD.

Source data

Extended Data Fig. 7 Characterization of the SVG-A ACE2 cell line.

(a) RNA extraction and qPCR of ACE-2 mRNA from SVGA stably expressing ACE-2 and normalized to GAPDH mRNA. Data are presented as mean values +/− SD from duplicates from one experiment. (b) SVG-A WT and SVG-A ACE-2 infected with SARS-CoV-2 mNeonGreen for 24 hours treated or not with 10µM Remdesivir. The graph represents the percentage of infected cells quantify by flow cytometry. Data are presented as mean values +/− SD from duplicates from one experiment. (c) SVG-A were treated with the concentration of Stachel peptide (agonist) or Scramble peptide (control) as indicated. The graph represents the amount of cAMP released after LPHN3 stimulation. Data are presented as mean values +/− SD from triplicates from one experiment. (d) SVGA-ACE2 were infected for 48 h with SARS-CoV-2 WT or SARS-CoV-2 N-mNeonGreen inactivated or not with UV-C (254 nm) as indicated. Cells were stained with Spike for Flow cytometry analysis. The bar graph represents the percentage of infected cells in each condition. Data are presented as mean values +/− SD from duplicates from one experiment. (e) Cerebral organoids were treated with Scramble or Stachel peptides. The graph represents the cAMP released after LPHN3 stimulation. Data are presented as mean values +/− SD from triplicates from one experiment. Two-tailed p value from unpaired t test was 0.001 (***).

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Extended Data Fig. 8 Impact of SARS-CoV-2 exposure on organoid electrical activity.

(a) Micrograph of an organoid on a 3D MEA electrode, representative of at least ten organoids. Scale bar = 30 µm. (b) Extracellular electrical trace of an electrode on which a SARS-CoV-2-exposed cerebral organoid was seeded. (c) Confusion matrix for time-wise testing. The model has been trained on recordings of infected and mock condition 24 hpi, and tested on 0 hpi, 0.5 hpi and 24 hpi for SARS-CoV-2 infected and mock conditions. CUP: Confidence Upon Prediction. (d) Confusion matrix for testing the impact of Spike. The rows represent the different outputs the RFC model has been trained to recognize. The columns represent the data we provided to the model for testing purposes. The model has been trained on recordings of infected and mock condition at 24 hpi, and tested on recordings of infected, mock, and Spike-treated infected condition at 24 hpi. CUP: Confidence Upon Prediction. (E) Principal component analysis fitted on mock and infected conditions at 24 hpi, then applied on the Spike-treated infected recordings 24 hpi. The ellipses represent the confidence for each condition.

Extended Data Fig. 9 Characterization of human neural progenitor cells.

(a) Mature neurons derived from hNPCs were incubated with recombinant Spike protein for 3 h and immunoprecipitation of Spike was performed using protein A-coupled agarose beads. Western blotting for ACE2, FLRT3 and Spike shows that pull-down of the Spike protein was efficient, and that neuronal ACE2 could be retrieved associated to Spike, while undetectable from the input. However, no FLRT3 could be enriched upon Spike pull-down using this method. The western blot is representative of two experiments. (b) NPCs were transduced with FLRT3 mCherry construct. The micrograph (left panel) and zoom-in (right panel) shows NPCs expressing fluorescent FLRT3 and positive for FLRT3 staining. The micrograph is representative at least 15 fields of view.

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Supplementary information

Reporting Summary

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Supplementary Data 1

Supplementary Tables 1–4.

Supplementary Video 1

Live cell imaging of an active SARS-CoV-2 virus on neurons expressing fluorescent FLRT3. A SARS-CoV-2 N-mNeonGreen particle (pink) was monitored on neurons differentiated from hNPCs and artificially expressing a fluorescent FLRT3 protein (green). Images were acquired every 30 s for 30 min using a spinning disk confocal microscope in a BSL-3 environment.

Supplementary Video 2

Live cell imaging of an active SARS-CoV-2 virus. A SARS-CoV-2 N-mNeonGreen particle (orange) was monitored on SynaptoRed-labelled neurons (cyan) differentiated from hNPCs. Images were acquired every 5 s for 20 min using a spinning disk confocal microscope in a BSL-3 environment.

Supplementary Video 3

Live cell imaging of a dwelling SARS-CoV-2 virus. A SARS-CoV-2 N-mNeonGreen particle (orange) was monitored on SynaptoRed-labelled neurons (cyan) differentiated from hNPCs. Images were acquired every 5 s for 20 min using a spinning disk confocal microscope in a BSL-3 environment.

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Source Data Fig. 1

Source data for Fig. 1c,e,f.

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Source data for Fig. 2b–g.

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Source data for Fig. 3b–d,f–h.

Source Data Fig. 4

Unprocessed western blots for Fig. 4b and source data for Fig. 4d–f,h.

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Source data for Fig. 5b,d–g,j–m.

Source Data Extended Data Fig. 1

Source data for Extended Data Fig. 1b–d,f,h,i.

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Source data for Extended Data Fig. 4b–e.

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Source data for Extended Data Fig. 5a,c,f–h.

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Source data for Extended Data Fig. 6a–f.

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Source data for Extended Data Fig. 7a–e.

Source Data Extended Data Fig. 9

Unprocessed western blots for Extended Data Fig. 9a.

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Partiot, E., Hirschler, A., Colomb, S. et al. Brain exposure to SARS-CoV-2 virions perturbs synaptic homeostasis. Nat Microbiol (2024). https://doi.org/10.1038/s41564-024-01657-2

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