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Disease-specific oligodendrocyte lineage cells arise in multiple sclerosis


Multiple sclerosis (MS) is characterized by an immune system attack targeting myelin, which is produced by oligodendrocytes (OLs). We performed single-cell transcriptomic analysis of OL lineage cells from the spinal cord of mice induced with experimental autoimmune encephalomyelitis (EAE), which mimics several aspects of MS. We found unique OLs and OL precursor cells (OPCs) in EAE and uncovered several genes specifically alternatively spliced in these cells. Surprisingly, EAE-specific OL lineage populations expressed genes involved in antigen processing and presentation via major histocompatibility complex class I and II (MHC-I and -II), and in immunoprotection, suggesting alternative functions of these cells in a disease context. Importantly, we found that disease-specific oligodendroglia are also present in human MS brains and that a substantial number of genes known to be susceptibility genes for MS, so far mainly associated with immune cells, are expressed in the OL lineage cells. Finally, we demonstrate that OPCs can phagocytose and that MHC-II-expressing OPCs can activate memory and effector CD4-positive T cells. Our results suggest that OLs and OPCs are not passive targets but instead active immunomodulators in MS. The disease-specific OL lineage cells, for which we identify several biomarkers, may represent novel direct targets for immunomodulatory therapeutic approaches in MS.

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Fig. 1: Single-cell RNA sequencing of OL lineage cells in response to EAE uncovers new disease-specific populations and disease markers.
Fig. 2: Expression of immunoprotective and adaptive immunity genes in response to EAE.
Fig. 3: Expression of MHC class II and MS susceptibility genes in the OL lineage cells in response to EAE and in MS.
Fig. 4: OPCs express MHC-II in response to IFN-γ, exhibit phagocytic capacity and regulate T cell survival and proliferation.

Data availability

A web resource for browsing differential gene expression data for the single-cell data can be accessed at Raw data are deposited in GEO, accession number GSE113973.


  1. 1.

    Patsopoulos, al. The Multiple Sclerosis Genomic Map: Role of peripheral immune cells and resident microglia in susceptibility. Preprint at bioRxiv (2017)

  2. 2.

    Skene, N. G. & Grant, S. G. Identification of vulnerable cell types in major brain disorders using single cell transcriptomes and expression weighted cell type enrichment. Front. Neurosci. 10, 16 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  3. 3.

    Marques, S. et al. Transcriptional convergence of oligodendrocyte lineage progenitors during development. Dev. Cell 46, 504–517.e7 (2018).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  4. 4.

    Marques, S. et al. Oligodendrocyte heterogeneity in the mouse juvenile and adult central nervous system. Science 352, 1326–1329 (2016).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  5. 5.

    Picelli, S. et al. Smart-seq2 for sensitive full-length transcriptome profiling in single cells. Nat. Methods 10, 1096–1098 (2013).

    CAS  Article  Google Scholar 

  6. 6.

    Klinghoffer, R. A., Hamilton, T. G., Hoch, R. & Soriano, P. An allelic series at the PDGFalphaR locus indicates unequal contributions of distinct signaling pathways during development. Dev. Cell 2, 103–113 (2002).

    CAS  Article  PubMed  Google Scholar 

  7. 7.

    Kang, S. H., Fukaya, M., Yang, J. K., Rothstein, J. D. & Bergles, D. E. NG2+CNS glial progenitors remain committed to the oligodendrocyte lineage in postnatal life and following neurodegeneration. Neuron 68, 668–681 (2010).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  8. 8.

    Emery, B. et al. Myelin gene regulatory factor is a critical transcriptional regulator required for CNS myelination. Cell 138, 172–185 (2009).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  9. 9.

    Ogata, T. et al. Hes1 functions downstream of growth factors to maintain oligodendrocyte lineage cells in the early progenitor stage. Neuroscience 176, 132–141 (2011).

    CAS  Article  PubMed  Google Scholar 

  10. 10.

    Tripathi, R. B., Rivers, L. E., Young, K. M., Jamen, F. & Richardson, W. D. NG2 glia generate new oligodendrocytes but few astrocytes in a murine experimental autoimmune encephalomyelitis model of demyelinating disease. J. Neurosci. 30, 16383–16390 (2010).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  11. 11.

    Zawadzka, M. et al. CNS-resident glial progenitor/stem cells produce Schwann cells as well as oligodendrocytes during repair of CNS demyelination. Cell Stem Cell 6, 578–590 (2010).

    CAS  Article  PubMed  Google Scholar 

  12. 12.

    Gregory, A. P. et al. TNF receptor 1 genetic risk mirrors outcome of anti-TNF therapy in multiple sclerosis. Nature 488, 508–511 (2012).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  13. 13.

    Capello, E., Voskuhl, R. R., McFarland, H. F. & Raine, C. S. Multiple sclerosis: re-expression of a developmental gene in chronic lesions correlates with remyelination. Ann. Neurol. 41, 797–805 (1997).

    CAS  Article  PubMed  Google Scholar 

  14. 14.

    Enevold, C. et al. Multiple sclerosis and polymorphisms of innate pattern recognition receptors TLR1-10, NOD1-2, DDX58, and IFIH1. J. Neuroimmunol. 212, 125–131 (2009).

    CAS  Article  PubMed  Google Scholar 

  15. 15.

    Haile, Y. et al. Granzyme B-inhibitor serpina3n induces neuroprotection in vitro and in vivo. J. Neuroinflamm. 12, 157 (2015).

    Article  CAS  Google Scholar 

  16. 16.

    Lee, S. C. & Raine, C. S. Multiple sclerosis: oligodendrocytes in active lesions do not express class II major histocompatibility complex molecules. J. Neuroimmunol. 25, 261–266 (1989).

    CAS  Article  PubMed  Google Scholar 

  17. 17.

    Sibinga, N. E., Feinberg, M. W., Yang, H., Werner, F. & Jain, M. K. Macrophage-restricted and interferon gamma-inducible expression of the allograft inflammatory factor-1 gene requires Pu.1. J. Biol. Chem. 277, 16202–16210 (2002).

    CAS  Article  PubMed  Google Scholar 

  18. 18.

    Lin, W., Harding, H. P., Ron, D. & Popko, B. Endoplasmic reticulum stress modulates the response of myelinating oligodendrocytes to the immune cytokine interferon-gamma. J. Cell Biol. 169, 603–612 (2005).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  19. 19.

    Kobayashi, K. S. & van den Elsen, P. J. NLRC5: a key regulator of MHC class I-dependent immune responses. Nat. Rev. Immunol. 12, 813–820 (2012).

    CAS  Article  PubMed  Google Scholar 

  20. 20.

    Bergsteindottir, K., Brennan, A., Jessen, K. R. & Mirsky, R. In the presence of dexamethasone, gamma interferon induces rat oligodendrocytes to express major histocompatibility complex class II molecules. Proc. Natl Acad. Sci. USA 89, 9054–9058 (1992).

    CAS  Article  PubMed  Google Scholar 

  21. 21.

    Brosius Lutz, A. et al. Schwann cells use TAM receptor-mediated phagocytosis in addition to autophagy to clear myelin in a mouse model of nerve injury. Proc. Natl Acad. Sci. USA 114, E8072–E8080 (2017).

    Article  CAS  PubMed  Google Scholar 

  22. 22.

    Bettelli, E. et al. Myelin oligodendrocyte glycoprotein-specific T cell receptor transgenic mice develop spontaneous autoimmune optic neuritis. J. Exp. Med. 197, 1073–1081 (2003).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  23. 23.

    Zeis, T., Enz, L. & Schaeren-Wiemers, N. The immunomodulatory oligodendrocyte. Brain Res. 1641, 139–148 (2016).

    CAS  Article  PubMed  Google Scholar 

  24. 24.

    Peferoen, L., Kipp, M., van der Valk, P., van Noort, J. M. & Amor, S. Oligodendrocyte-microglia cross-talk in the central nervous system. Immunology 141, 302–313 (2014).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  25. 25.

    Zeis, T. & Schaeren-Wiemers, N. Lame ducks or fierce creatures? The role of oligodendrocytes in multiple sclerosis. J. Mol. Neurosci. 35, 91–100 (2008).

    CAS  Article  PubMed  Google Scholar 

  26. 26.

    Moyon, S. et al. Demyelination causes adult CNS progenitors to revert to an immature state and express immune cues that support their migration. J. Neurosci. 35, 4–20 (2015).

    Article  CAS  PubMed  Google Scholar 

  27. 27.

    Huynh, J. L. et al. Epigenome-wide differences in pathology-free regions of multiple sclerosis-affected brains. Nat. Neurosci. 17, 121–130 (2014).

    CAS  Article  PubMed  Google Scholar 

  28. 28.

    Traka, M., Podojil, J. R., McCarthy, D. P., Miller, S. D. & Popko, B. Oligodendrocyte death results in immune-mediated CNS demyelination. Nat. Neurosci. 19, 65–74 (2016).

    CAS  Article  PubMed  Google Scholar 

  29. 29.

    Matsuoka, T. et al. Neural crest origins of the neck and shoulder. Nature 436, 347–355 (2005).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  30. 30.

    Martin, M. Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet.journal 17, 10–13 (2011).

    Article  Google Scholar 

  31. 31.

    Dobin, A. et al. STAR: ultrafast universal RNA-seq aligner. Bioinformatics 29, 15–21 (2013).

    CAS  Article  Google Scholar 

  32. 32.

    Norton, W. T. & Poduslo, S. E. Myelination in rat brain: method of myelin isolation. J. Neurochem. 21, 749–757 (1973).

    CAS  Article  PubMed  Google Scholar 

  33. 33.

    Larocca, J. N. & Norton, W. T. Isolation of myelin. Curr. Protoc. Cell Biol. 33, 3.25.1–3.25.19 (2007).

    Article  Google Scholar 

  34. 34.

    Zeisel, A., Yitzhaky, A., Bossel Ben-Moshe, N. & Domany, E. An accessible database for mouse and human whole transcriptome qPCR primers. Bioinformatics 29, 1355–1356 (2013).

    CAS  Article  PubMed  Google Scholar 

  35. 35.

    Angerer, P. et al. destiny: diffusion maps for large-scale single-cell data in R. Bioinformatics 32, 1241–1243 (2016).

    CAS  Article  PubMed  Google Scholar 

  36. 36.

    Bivand, R., Hauke, J. & Kossowski, T. Computing the Jacobian in Gaussian spatial autoregressive models: an illustrated comparison of available methods. Geogr. Anal. 45, 150–179 (2013).

    Article  Google Scholar 

  37. 37.

    Keren-Shaul, H. et al. A unique microglia type associated with restricting development of Alzheimer’s disease. Cell 169, 1276–1290.e17 (2017).

    CAS  Article  Google Scholar 

  38. 38.

    Finak, G. et al. MAST: a flexible statistical framework for assessing transcriptional changes and characterizing heterogeneity in single-cell RNA sequencing data. Genome Biol. 16, 278 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. 39.

    Yu, G., Wang, L. G., Han, Y. & He, Q. Y. clusterProfiler: an R package for comparing biological themes among gene clusters. OMICS 16, 284–287 (2012).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  40. 40.

    Killcoyne, S., Carter, G. W., Smith, J. & Boyle, J. in Protein Networks and Pathway Analysis (eds. Nikolsky, Y. & Bryant, J.) 219–239 (Humana Press, New York, 2009).

  41. 41.

    Bindea, G. et al. ClueGO: a Cytoscape plug-in to decipher functionally grouped gene ontology and pathway annotation networks. Bioinformatics 25, 1091–1093 (2009).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  42. 42.

    Wolfert, M. A. & Boons, G. J. Adaptive immune activation: glycosylation does matter. Nat. Chem. Biol. 9, 776–784 (2013).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  43. 43.

    Huang, Y. & Sanguinetti, G. BRIE: transcriptome-wide splicing quantification in single cells. Genome Biol. 18, 123 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. 44.

    Thorvaldsdóttir, H., Robinson, J. T. & Mesirov, J. P. Integrative genomics viewer (IGV): high-performance genomics data visualization and exploration. Brief. Bioinform. 14, 178–192 (2013).

    Article  CAS  Google Scholar 

  45. 45.

    Durinck, S., Spellman, P. T., Birney, E. & Huber, W. Mapping identifiers for the integration of genomic datasets with the R/Bioconductor package biomaRt. Nat. Protoc. 4, 1184–1191 (2009).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  46. 46.

    Quinlan, A. R. BEDTools: the Swiss-army tool for genome feature analysis. Curr. Protoc. Bioinformatics 47, 11.12.1–11.12.34 (2014).

    Article  Google Scholar 

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We would like to thank A. Nanni, A. Moshref, Tony Jimenez-Beristain and J. Söderlund for laboratory management and support. We thank Eukaryotic Single Cell Genomics Facility, WABI Long Term Bioinformatic Support (Leif Wigge) at SciLifeLab, the FACS facilities at CMB (B. Panagel), Science for Life Laboratory, the National Genomics Infrastructure and Uppmax for providing assistance in massive parallel sequencing and computational infrastructure. We wish to acknowledge A. G. Rothfuchs for advice and reagents, M. Jagodic for advice, M. Bartosovic for assistance, R. Berglund and M. N’diaye for providing the tools to perform the phagocytosis experiments. The bioinformatics computations were performed on resources provided by the Swedish National Infrastructure for Computing at UPPMAX, Uppsala University. Postmortem MS tissue used for IHC was provided via a UK prospective donor scheme with full ethical approval from the UK Multiple Sclerosis Tissue Bank (MREC/02/02/39). D.P.V. would like to acknowledge the University of Sydney HPC service for providing HPC resources that have contributed to the research reported in this paper. This work was supported in part by a University of Sydney HPC Grand Challenge Award. D.P.V. was supported in part by a Boehringer Ingelheim Travel Grant. C.f.-C. is funded by a Wellcome Trust Investigator award. A.W. is funded by UK Multiple Sclerosis Society. S.J. is funded by European Union, Horizon 2020, Marie-Skłodowska Curie Actions (grant no. EC 789492); A.M.F. by the European Committee for Treatment and Research of Multiple Sclerosis (ECTRIMS). E.A. is funded by European Union, Horizon 2020, Marie-Skłodowska Curie Actions (grant no. SOLO 794689). Work in G.C.-B.’s research group was supported by Swedish Research Council (grant no. 2015-03558), European Union (Horizon 2020 Research and Innovation Programme/European Research Council Consolidator Grant EPIScOPE, grant agreement 681893), Swedish Brain Foundation (grant no. FO2017-0075), Ming Wai Lau Centre for Reparative Medicine, Petrus och Augusta Hedlunds Foundation (grant nos. M-2014-0041 and M-2016-0428) and Karolinska Institutet.

Author information




A.M.F., D.V.B and G.C.-B. conceived the project, designed the study and interpreted results. A.M.F., S.M. and A.O.G-C. performed EAE model and A.M.F and S.M. collected single cells to generate single-cell sequencing data. D.V.B and E.A. performed computational analyses. A.M.F. and M.M. designed, performed and analyzed most in vitro OPC experiments and S. performed the phagocytosis experiments together with A.M.F. A.O.G-C. and A.M.F. designed, performed and analyzed all experiments involving co-cultures with immune cells. S.J., A.W. and C.f.-C. provided the human postmortem MS brain tissue and performed the human IHC analysis. D.P.V. provided support for computational analysis. E.M.F. provided RNAscope ISH expertise and performed all videos. A.M.F, D.V.B and G.C.-B. wrote the manuscript with feedback from all authors.

Corresponding authors

Correspondence to Ana Mendanha Falcão or Gonçalo Castelo-Branco.

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Competing interests

The G.C.-B., A.W. and C.f.-C. research groups have received funding from F. Hoffmann–La Roche, Ltd. for other research projects in this area.

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Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–9

Reporting Summary

Supplementary Video 1

MOL2 cells express MHC-II genes

Supplementary Video 2

OPCs express MHC-II genes

Supplementary Video 3

OL lineage cells express MHC-II genes

Supplementary Video 4

OL lineage cells express MHC-II genes

Supplementary Video 5

OL lineage cells express MHC-II genes and few Aif1 molecules

Supplementary Video 6

OL lineage cells express MHC-II genes

Supplementary Video 7

Microglia processes touch OL lineage cells

Supplementary Video 8

MHC-II positive cells surround OL lineage cells in human MS patient samples

Supplementary Video 9

OL lineage cells from human MS patient samples express MHC-II genes

Supplementary Table 1

Differential gene expression and gene module association

Supplementary Table 2

Splicing events and exon inclusion or exclusion events

Supplementary Table 3

Differential gene expression between CTRL and EAE in MOLs and OPCs

Supplementary Table 4

Non-MHC MS susceptibility genes expressed in microglia and OPCs in EAE and CTRL and significant differential expression of these genes across the major level 1 cluster

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Falcão, A.M., van Bruggen, D., Marques, S. et al. Disease-specific oligodendrocyte lineage cells arise in multiple sclerosis. Nat Med 24, 1837–1844 (2018).

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