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Single-cell transcriptomics and surface epitope detection in human brain epileptic lesions identifies pro-inflammatory signaling

Kumar, Pavanish, Lim, Amanda, Hazirah, Sharifah Nur, Chua, Camillus Jian Hui, Ngoh, Adeline, Poh, Su Li, Yeo, Tong Hong, Lim, Jocelyn, Ling, Simon, Sutamam, Nursyuhadah Binte, Petretto, Enrico, Low, David Chyi Yeu, Zeng, Li, Tan, Eng-King, Arkachaisri, Thaschawee, Yeo, Joo Guan, Ginhoux, Florent, Chan, Derrick, Albani, Salvatore·2022·Nature Neuroscience

Abstract

Epileptogenic triggers are multifactorial and not well understood. Here we aimed to address the hypothesis that inappropriate pro-inflammatory mechanisms contribute to the pathogenesis of refractory epilepsy (non-responsiveness to antiepileptic drugs) in human patients. We used single-cell cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq) to reveal the immunotranscriptome of surgically resected epileptic lesion tissues. Our approach uncovered a pro-inflammatory microenvironment, including extensive activation of microglia and infiltration of other pro-inflammatory immune cells. These findings were supported by ligand–receptor (LR) interactome analysis, which demonstrated potential mechanisms of infiltration and evidence of direct physical interactions between microglia and T cells. Together, these data provide insight into the immune microenvironment in epileptic tissue, which may aid the development of new therapeutics.

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  1. Reynolds, E. H. The ILAE/IBE/WHO global campaign against epilepsy: bringing epilepsy “out of the shadows”. Epilepsy Behav. 1, S3–S8 (2000). · DOI
  2. Lerche, H. Drug-resistant epilepsy—time to target mechanisms. Nat. Rev. Neurol. 16, 595–596 (2020). · DOI
  3. Ravizza, T. et al. Innate and adaptive immunity during epileptogenesis and spontaneous seizures: evidence from experimental models and human temporal lobe epilepsy. Neurobiol. Dis. 29, 142–160 (2008). · DOI
  4. Auvin, S., Cilio, M. R. & Vezzani, A. Current understanding and neurobiology of epileptic encephalopathies. Neurobiol. Dis. 92, 72–89 (2016). · DOI
  5. Vezzani, A., Balosso, S. & Ravizza, T. Neuroinflammatory pathways as treatment targets and biomarkers in epilepsy. Nat. Rev. Neurol. 15, 459–472 (2019). · DOI
  6. Xu, D. et al. Peripherally derived T regulatory and γδ T cells have opposing roles in the pathogenesis of intractable pediatric epilepsy. J. Exp. Med. 215, 1169–1186 (2018). · DOI
  7. Kumar, P. et al. Pro-inflammatory, IL-17 pathways dominate the architecture of the immunome in pediatric refractory epilepsy. JCI Insight 5, e126337 (2019). · DOI
  8. You, S. J., Jung, D. E., Kim, H. D., Lee, H. S. & Kang, H. C. Efficacy and prognosis of a short course of prednisolone therapy for pediatric epilepsy. Eur. J. Paediatr. Neurol. 12, 314–320 (2008). · DOI
  9. Mehta, V., Ferrie, C. D., Cross, J. H. & Vadlamani, G. Corticosteroids including ACTH for childhood epilepsy other than epileptic spasms. Cochrane Database Syst. Rev. 2015, CD005222 (2015). · DOI
  10. Dubey, D. et al. Randomized placebo-controlled trial of intravenous immunoglobulin in autoimmune LGI1/CASPR2 epilepsy. Ann. Neurol. 87, 313–323 (2020). · DOI
  11. Lai, Y. C. et al. Anakinra usage in febrile infection related epilepsy syndrome: an international cohort. Ann. Clin. Transl. Neurol. 7, 2467–2474 (2020). · DOI
  12. Stoeckius, M. et al. Simultaneous epitope and transcriptome measurement in single cells. Nat. Methods 14, 865–868 (2017). · DOI · Paper page
  13. 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). · DOI · Paper page
  14. Stratoulias, V., Venero, J. L., Tremblay, M. E. & Joseph, B. Microglial subtypes: diversity within the microglial community. EMBO J. 38, e101997 (2019). · DOI
  15. Ravizza, T. et al. The IL-1β system in epilepsy-associated malformations of cortical development. Neurobiol. Dis. 24, 128–143 (2006). · DOI · Paper page
  16. Kim, H. J., Lin, Y., Geddes, T. A., Yang, J. Y. H. & Yang, P. CiteFuse enables multi-modal analysis of CITE-seq data. Bioinformatics 36, 4137–4143 (2020). · DOI
  17. Laroni, A. & Uccelli, A. CD56bright natural killer cells: a possible biomarker of different treatments in multiple sclerosis. J. Clin. Med. 9, 1450 (2020). · DOI
  18. Verbeek, M. M., Westphal, J. R., Ruiter, D. J. & de Waal, R. M. T lymphocyte adhesion to human brain pericytes is mediated via very late antigen-4/vascular cell adhesion molecule-1 interactions. J. Immunol. 154, 5876–5884 (1995). · DOI
  19. Proebstl, D. et al. Pericytes support neutrophil subendothelial cell crawling and breaching of venular walls in vivo. J. Exp. Med. 209, 1219–1234 (2012). · DOI
  20. Tigges, U., Boroujerdi, A., Welser-Alves, J. V. & Milner, R. TNF-α promotes cerebral pericyte remodeling in vitro, via a switch from α1 to α2 integrins. J. Neuroinflammation 10, 33 (2013). · DOI
  21. Jin, S. et al. Inference and analysis of cell–cell communication using CellChat. Nat. Commun. 12, 1088 (2021). · DOI · Paper page
  22. Srivastava, P. K. et al. A systems-level framework for drug discovery identifies Csf1R as an anti-epileptic drug target. Nat. Commun. 9, 3561 (2018). · DOI
  23. Giladi, A. et al. Dissecting cellular crosstalk by sequencing physically interacting cells. Nat. Biotechnol. 38, 629–637 (2020). · DOI
  24. Hafler, D. A. et al. Multiple sclerosis. Immunol. Rev. 204, 208–231 (2005). · DOI
  25. Yeo, J. G. et al. Publisher correction: the extended polydimensional immunome characterization (EPIC) web-based reference and discovery tool for cytometry data. Nat. Biotechnol. 38, 757 (2020). · DOI
  26. Badimon, A. et al. Negative feedback control of neuronal activity by microglia. Nature 586, 417–423 (2020). · DOI · Paper page
  27. Merlini, M. et al. Microglial Gi-dependent dynamics regulate brain network hyperexcitability. Nat. Neurosci. 24, 19–23 (2021). · DOI
  28. Brucklacher-Waldert, V., Stuerner, K., Kolster, M., Wolthausen, J. & Tolosa, E. Phenotypical and functional characterization of T helper 17 cells in multiple sclerosis. Brain 132, 3329–3341 (2009). · DOI
  29. van Langelaar, J. et al. T helper 17.1 cells associate with multiple sclerosis disease activity: perspectives for early intervention. Brain 141, 1334–1349 (2018). · DOI
  30. Fabene, P. F., Laudanna, C. & Constantin, G. Leukocyte trafficking mechanisms in epilepsy. Mol. Immunol. 55, 100–104 (2013). · DOI
  31. van Vliet, E. A., Aronica, E. & Gorter, J. A. Role of blood–brain barrier in temporal lobe epilepsy and pharmacoresistance. Neuroscience 277, 455–473 (2014). · DOI · Paper page
  32. Gorter, J. A., Aronica, E. & van Vliet, E. A. The roof is leaking and a storm is raging: repairing the blood–brain barrier in the fight against epilepsy. Epilepsy Curr. 19, 177–181 (2019). · DOI
  33. Sotgiu, S., Murrighile, M. R. & Constantin, G. Treatment of refractory epilepsy with natalizumab in a patient with multiple sclerosis. Case report. BMC Neurol. 10, 84 (2010). · DOI
  34. Polman, C. H. et al. A randomized, placebo-controlled trial of natalizumab for relapsing multiple sclerosis. N. Engl. J. Med. 354, 899–910 (2006). · DOI
  35. Miller, D. H. et al. MRI outcomes in a placebo-controlled trial of natalizumab in relapsing MS. Neurology 68, 1390–1401 (2007). · DOI
  36. Haider, L. et al. Oxidative damage in multiple sclerosis lesions. Brain 134, 1914–1924 (2011). · DOI
  37. Aronica, E., Ravizza, T., Zurolo, E. & Vezzani, A. Astrocyte immune responses in epilepsy. Glia 60, 1258–1268 (2012). · DOI
  38. Verhoog, Q. P., Holtman, L., Aronica, E. & van Vliet, E. A. Astrocytes as guardians of neuronal excitability: mechanisms underlying epileptogenesis. Front. Neurol. 11, 591690 (2020). · DOI
  39. Stack, E. C., Wang, C., Roman, K. A. & Hoyt, C. C. Multiplexed immunohistochemistry, imaging, and quantitation: a review, with an assessment of Tyramide signal amplification, multispectral imaging and multiplex analysis. Methods 70, 46–58 (2014). · DOI
  40. Lutge, A. et al. CellMixS: quantifying and visualizing batch effects in single-cell RNA-seq data. Life Sci. Alliance 4, e202001004 (2021). · DOI
  41. Baran, Y. et al. MetaCell: analysis of single-cell RNA-seq data using K-nn graph partitions. Genome Biol. 20, 206 (2019). · DOI

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Metadata

Authors
Kumar, P., Lim, A., Hazirah, S. N., Chua, C. J. H., Ngoh, A., Poh, S. L., Yeo, T. H., Lim, J., Ling, S., Sutamam, N. B., Petretto, E., Low, D. C. Y., Zeng, L., Tan, E.-K., Arkachaisri, T., Yeo, J. G., Ginhoux, F., Chan, D., & Albani, S.
Venue
Nature Neuroscience
Published
2022-06-23
Volume
25
Issue
7
Pages
956-966
ISSN
  • 1097-6256
  • 1546-1726
Cited by
142
References
6
Language
en

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