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Published: 24 January 2022

Clonally expanded B cells in multiple sclerosis bind EBV EBNA1 and GlialCAM

volume 603, pages 321–327 (2022)Cite this article

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Abstract

Multiple sclerosis (MS) is a heterogenous autoimmune disease in which autoreactive lymphocytes attack the myelin sheath of the central nervous system. B lymphocytes in the cerebrospinal fluid (CSF) of patients with MS contribute to inflammation and secrete oligoclonal immunoglobulins^1,2. Epstein–Barr virus (EBV) infection has been epidemiologically linked to MS, but its pathological role remains unclear³. Here we demonstrate high-affinity molecular mimicry between the EBV transcription factor EBV nuclear antigen 1 (EBNA1) and the central nervous system protein glial cell adhesion molecule (GlialCAM) and provide structural and in vivo functional evidence for its relevance. A cross-reactive CSF-derived antibody was initially identified by single-cell sequencing of the paired-chain B cell repertoire of MS blood and CSF, followed by protein microarray-based testing of recombinantly expressed CSF-derived antibodies against MS-associated viruses. Sequence analysis, affinity measurements and the crystal structure of the EBNA1–peptide epitope in complex with the autoreactive Fab fragment enabled tracking of the development of the naive EBNA1-restricted antibody to a mature EBNA1–GlialCAM cross-reactive antibody. Molecular mimicry is facilitated by a post-translational modification of GlialCAM. EBNA1 immunization exacerbates disease in a mouse model of MS, and anti-EBNA1 and anti-GlialCAM antibodies are prevalent in patients with MS. Our results provide a mechanistic link for the association between MS and EBV and could guide the development of new MS therapies.

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Main

The presence of oligoclonal bands (OCBs) in CSF and the efficacy of therapies that deplete B cells emphasize the importance of B cells in the pathobiology of MS². Antiviral antibodies against mumps, measles, varicella-zoster virus (VZV) and EBV are often present in MS^4,5, but their relevance is unclear. Anti-EBNA1 antibody titres can be detected in nearly 100% of patients with MS before the development of clinical symptoms, which providesevidence for an epidemiological link between MS and EBV⁶. Symptomatic infectious mononucleosis during EBV infection increases the risk for developing MS⁷. Molecular mimicry between virus and self-antigens is a potential mechanism that might explain this association⁸. Antibodies against certain EBNA1 regions have been found in patients with MS, including the region covering residues 365–426 (refs. ^5,9,10,11,12), which we describe here in our identification of molecular mimicry between EBNA1 and GlialCAM. The potential significance of this mimicry in the pathophysiology of MS is described in detail.

The B cell repertoire in MS CSF

CSF and blood samples were obtained from patients with MS during the onset of disease (clinically isolated syndrome, n = 5) or an acute episode of relapsing–remitting MS (n = 4). Patients with a CSF pleocytosis of >10 cells µl^–1 were selected (Extended Data Table 1, Supplementary Discussion). Single B cells were sorted by flow cytometry (Extended Data Fig. 1a, b). and characteristic phenotypic differences of B cells in blood and CSF were observed^13,14. These included high plasmablast (PB) counts in CSF compared to blood (Extended Data Fig. 1c, d), different expression levels of α4 integrin and HLA-DR in PBs but not in non-PB B cells (Extended Data Fig. 1e–j, Supplementary Table 1) and high abundance of immunoglobulin G (IgG) in CSF PBs (Fig. 1a, Extended Data Fig. 1k, l).

**Fig. 1: B cell repertoires in MS blood and CSF.**

We sorted PBs from blood and B cells from matched CSF samples by flow cytometry and sequenced their full-length paired heavy-chain (HC) and light-chain (LC) VDJ regions¹⁵. A total of 13,578 paired sequences from blood PBs and 1,689 from CSF B cells passed filter thresholds. The CSF repertoire was highly clonal (Fig. 1a, Extended Data Figs. 2a, 3), which suggests that antigen-specific proliferation of select clones occurs within the CSF. Notably, CSF repertoires in three individuals without MS but with neuroinflammatory conditions (Extended Data Table 1) did not exhibit such extensive clonality and high IgG use (Fig. 1a, b, Extended Data Fig. 2b–d). Although the amount of somatic hypermutation (SHM) in immunoglobulin HC-V (IGHV) and LC-V (IGLV) genes did not differ between PBs in blood and CSF (Extended Data Fig. 2e), the lengths of HC-complementarity determining region 3 (CDR3) were longer in CSF PBs than in blood. This suggests that there is ongoing intrathecal SHM in the CSF (Extended Data Fig. 2f). Consistent with previous reports^16,17,18,19, repertoires in the CSF were skewed towards the use of five IGHV genes (Fig. 1c, Extended Data Fig. 2g–i), which indicates that select autoantigens drive PB survival and proliferation in CSF.

CSF PBs produce oligoclonal IgG

Immunoglobulin levels are increased in the CSF of patients with MS, and the presence of a few highly abundant OCBs is a hallmark of the disease. To determine whether clonal PBs are the source of intrathecal immunoglobulins, we isolated immunoglobulins from CSF, characterized them by mass spectrometry and compared the spectra with their corresponding antibody repertoire sequence datasets. For 87% of the clonal sequences, peptides matching variable-chain sequences unique to the patient were identified, whereas this occurred for only 40% of singleton sequences (Fig. 1d). Highly abundant immunoglobulins, defined by the detection of ≥10 peptide-spectral matches, aligned almost exclusively to clonally expanded B cells (Extended Data Fig. 2j) and to PBs, which display more clonality than non-PB B cells (Extended Data Fig. 2k, l). This result indicates that clonally expanded PBs are the predominant source of CSF OCBs.

CSF B cell-encoded antibodies bind EBV

A total of 148 B cell receptor (BCR) sequences from MS CSF, each representative of a clonal expansion, were expressed as monoclonal antibodies (mAbs) (Extended Data Fig. 3). MS CSF mAbs showed low polyreactivity (polyreactive mAbs from patients with MS were 5.4% compared with 15.4% for controls) (Extended Data Figs. 4, 5b). To test for antiviral reactivities, mAbs were probed on protein microarrays containing 2 EBV viral lysates, 23 latent and lytic EBV proteins, 240 peptides spanning four prominent EBV proteins, and lysates of 7 other MS-associated viruses, including measles, rubella and VZV⁴ (Fig. 2a, b, Extended Data Figs. 5a, 6, 7a, Supplementary Tables 2, 3). One-third of the expressed mAbs bound to EBV proteins and peptides and about 20% to other viruses, in particular to VZV and cytomegalovirus (Fig. 2a). Notably, half of the VZV-reactive antibodies cross-reacted to cytomegalovirus and EBV, which indicates that there are conserved epitopes among herpesviruses.

**Fig. 2: MS CSF B cell mAb reactivity to EBV proteins and interaction of MS39p2w174 with EBNA1_AA386–405.**

We also found that mAbs from six out of nine patients with MS bound to the EBV transcription factor EBNA1 (Fig. 2a, Extended Data Fig. 5a), and mAbs that bound EBNA1 peptides were identified in eight out of nine patient samples (Fig. 2b, Extended Data Fig. 6). Anti-EBNA1 reactivity has been implicated in MS epidemiology²⁰, and the amino acid region AA365–425 is the target of stronger antibody responses in patients with MS than in non-affected individuals^5,9,10,11,12. Protein and peptide microarrays revealed that the mAb MS39p2w174 bound EBNA1 within this MS-associated region at AA386–405 (Fig. 2b, Extended Data Fig. 6). This epitope was confirmed by western blot analysis using full-length and truncated EBNA1 proteins (Fig. 2c) and by ELISA-based EBNA1 peptide scans (Fig. 2d). Alanine scanning identified the Pro/Arg-rich region AA394–399 as the central epitope for MS39p2w174 (Fig. 2e, Extended Data Fig. 7b).

Structure of the EBNA1–CSF Fab complex

Although the presence of antibodies against the broader EBNA1 region AA365–425 has been described in MS^5,9,10,11,12, their relevance remains elusive. We solved the crystal structure of EBNA1_AA386–405 in complex with the Fab region of MS39p2w174 at a resolution of 2.5 Å (Protein Data Bank (PDB) identifier 7K7R)²¹ (Fig. 2f–j, Extended Data Fig. 7c–e). Close interactions of the EBNA1 residues P394–P398 were observed with all CDRs except for LC-CDR2. Residues Tyr31 and Tyr38 on LC-CDR1 together with Trp38 on HC-CDR1 and with Pro108, Pro109 and Tyr114 on HC–CDR3 create a hydrophobic cage for the two N-terminal proline residues Pro394 and Pro395 and the proximal side chain of Arg396 of the peptide (Fig. 2h, i). The C-terminal end of the antibody-binding groove is wider, and Pro398 is carried by a large aromatic tryptophan residue (Trp114 in HC-CDR1) (Fig. 2g, h). The central arginine residues Arg395 and Arg396 form hydrogen bonds with residues on HC-CDR2, HC-CDR3 and HC framework region 2.

The IGHV encoding gene of MS39p2w174 is IGHV3-7, one of the IGHV chains over-represented in CSF (Fig. 1c). Of note, all but two of the residues that directly interact with EBNA1 are unmutated germline residues (Extended Data Fig. 7f, g). We hypothesized that the unmutated ancestor of MS39p2w174 (germline) might have an innate propensity to bind EBNA1_AA386–405. Indeed, germline was significantly more polyreactive than MS39p2w174 (Extended Data Fig. 4), and bio-layer interferometry revealed that germline binds EBNA1 with almost the same affinity as MS39p2w174 (dissociation constant (K_d) values of 1.99 ± 0.63 nM (mean ± s.d.) for MS39p2w174 compared with 4.19 ± 0.76 nM for germline) (Fig. 2k, l), which indicates that SHM is not required for effective EBNA1 binding and that naive B cells have EBNA1 specificity.

Molecular mimicry of EBNA1 and GlialCAM

We probed the mAb MS39p2w174 on HuProt microarrays, which contained over 16,000 proteins spanning more than 80% of the human proteome²², and discovered that MS39p2w174 binds GlialCAM (Fig. 3a). GlialCAM is an immunoglobulin superfamily cell adhesion molecule expressed in the central nervous system (CNS) by astrocytes and oligodendrocytes^23,24,25,26. Earlier proteomics studies of MS brain lesions by our laboratory revealed that GlialCAM is expressed in chronic-active plaques²⁷. MS39p2w174 was also probed using a human proteome-wide phage display immunoprecipitation and sequencing (PhIP–seq) library²⁸. MS39p2w174 did not demonstrate high enrichment for any single peptide, which suggests that it has low affinity for multiple native peptides (Extended Data Table 2). Peptide motif analysis identified a common Pro/Arg-rich motif that closely resembles the central epitope in EBNA1 (AA395–399; Fig. 2e and Extended Data Fig. 8a). Comparing the PhIP–seq results with the HuProt results yielded two overlapping targets: the ubiquitously expressed actin filament associated protein 1 (AFAP1, which does not have the Pro/Arg-rich motif) and the CNS protein GlialCAM (encoded by HEPACAM). Binding of MS39p2w174 to the intracellular domain (ICD; AA262–416) of GlialCAM was confirmed by ELISA (Fig. 3b) and western blotting (Fig. 3c). MS39p2w174 showed distinct glial staining of mouse brain, including radial Bergmann glia in the cerebellum, the glia limitans, and perivascular glial cells in the hippocampus and the brainstem (Fig. 3d, and Extended Data Fig. 8b). MS39p2w174 stained rat oligodendrocytes and transgenic GlialCAM-expressing K562 cells, in which GlialCAM generated tight junctions (Extended Data Fig. 8c–e).

**Fig. 3: Molecular mimicry between EBNA1 and GlialCAM.**

Although we demonstrated that MS39p2w174 and its unmutated germline ancestor bound EBNA1 with similar affinity (Fig. 2k, l), their binding affinities to GlialCAM differed significantly. The affinity of MS39p2w174 to GlialCAM was increased by ≥10-fold (K_d of 1.99 ± 0.63 nM for EBNA1 compared with 190 ± 17 pM for GlialCAM). By contrast, germline bound GlialCAM with lower affinity (K_d of 4.19 ± 0.76 nM for EBNA1 compared with 10.46 ± 4.12 nM for GlialCAM) (Fig. 3e, f). Evidently, although germline harbours a propensity to bind to EBNA1, SHM of MS39p2w174 increased its affinity to the CNS mimic GlialCAM by an order of magnitude.

GlialCAM phosphorylation enables mimicry

The EBNA1 epitope AA386–405 is located between the long N-terminal Gly/Ala-rich low-complexity region (AA90–380) of the protein and its highly structured DNA-binding domain (AA461–607; PDB identifier 1B3T (ref. ²⁹)). The GlialCAM region AA337–385, identified by phage display (Extended Data Table 2), is located at the C-terminal end of the ICD and contains a Pro-rich region that resembles the central epitope of EBNA1 (Fig. 3g). Intracellular B cell autoantigens have been described in several autoimmune diseases^30,31,32. MS39p2w174 reacted with both proteins on western blots under denaturing conditions (Figs. 2c, 3c), which suggests that both antibody-binding regions are linear epitopes. This result is consistent with predictions that both epitopes are located in intrinsically disordered regions of their respective proteins (Fig. 3h, i).

Nevertheless, although MS39p2w174 bound with similar affinity to both the EBNA1 protein and the EBNA1_AA386–405 peptide (K_d of 1.99 ± 0.63 nM for the protein and 2.67 ± 0.078 nM for the peptide), its binding affinity for the native peptide GlialCAM_AA370–389 was three orders of magnitude lower than for GlialCAM protein (K_d of 190 ± 17 pM for the protein and 302 ± 31 nM for the peptide). Part of this discrepancy could be due to multimerization of GlialCAM³³. Moreover, the ICD of GlialCAM is heavily phosphorylated^33,34,35 (Extended Data Fig. 8f and PhosophSite³⁶; https://www.phosphosite.org), and post-translational modifications (PTMs) often determine antibody–antigen interactions³⁷. We determined whether phosphorylation at one of the four serine residues surrounding the central epitope region (Ser376, Ser377, Ser383 and Ser384) could increase the binding affinity of MS39p2w174 to GlialCAM_AA370–389. Indeed, phosphorylation at Ser376 (pSer376) increased MS39p2w174 binding by about 50-fold (K_d of 302 ± 0.078 nM for the native peptide and 6.1 ± 0.27 nM for the pSer376 peptide), and additional phosphorylation of Ser377 further enhanced the binding affinity (K_d of 3.73 ± 0.15 nM for the pSer376/pSer377 peptide) (Fig. 3j–l). By contrast, citrullination of arginine residues Arg373, Arg380 and Arg387 did not alter binding to GlialCAM_AA370–389 (Extended Data Fig. 8g). The important residue Arg397 in EBNA1_AA386–405, which engages in two hydrogen bonds with Glu64 at HC-CDR2 (Fig. 2h, j), is replaced with alanine in GlialCAM_AA370–389 (Ala381) (Fig. 3g). This probably explains the differential binding affinity to EBNA1 and GlialCAM peptides. Phosphorylation at Ser376 probably promotes binding by providing new polar interactions to the proximal LC, possibly with Arg36, a positively charged residue that is mutated from asparagine in germline (Fig. 2h, Extended Data Fig. 7g). Together, our results show that post-translational phosphorylation enables cross-reactivity of anti-EBNA1 MS39p2w174 to GlialCAM.

Anti-GlialCAM IgG reactivity in MS

To determine whether the observed anti-GlialCAM reactivity of MS39p2w174 represents a broader phenomenon in MS, we tested the remaining 147 clonal MS mAbs for reactivity against GlialCAM protein and peptides spanning GlialCAM_AA315–395. Ten additional mAbs from seven patients bound the ICD and seven more from four patients bound the extracellular domain (ECD) (Fig. 3m), which demonstrates that MS PBs generate antibodies against multiple GlialCAM epitopes. We then tested plasma samples from patients with MS (n = 36) and from non-affected individuals (n = 20) for reactivity to EBNA1 and GlialCAM. As expected, all samples from patients with MS and the majority samples from healthy individuals exhibited plasma reactivity to EBNA1 protein (Fig. 3n). Reactivity to EBNA1_AA386–405 and to GlialCAM was significantly increased in patients with MS (Fig. 3o, p). Increased plasma IgG levels against EBNA1_AA386–405, GlialCAM_AA370-–389 and phosphorylated GlialCAM_{AA370–389 pSer376} were confirmed in a second independent patient cohort (MS, n = 71, controls, n = 50) (Extended Data Fig. 9a). Similarly, we detected increased plasma IgG levels against GlialCAM, GlialCAM_AA370–389 and phosphorylated GlialCAM_{AA370-389 pSer376} in a third cohort (MS, n = 67, controls, n = 31) (Extended Data Fig. 9b). We next addressed whether reactivity against EBNA1_AA386–405 could be blocked by GlialCAM. Inhibition of anti-EBNA1_AA386–405 reactivity by GlialCAM_{AA370–389 pSer376} in nine high-reactivity samples was observed (Fig. 3q, Extended Data Fig. 9c), which indicates that this molecular mimicry is prevalent in a subset of patients with MS.

EBNA1 immunization aggravates EAE

To assess the effect of an anti-EBNA1_AA386–405 immune response on neuroinflammation, we used mice with experimental autoimmune encephalomyelitis (EAE), the mouse model of MS. SJL/J mice were immunized with scrambled control peptide or EBNA1_AA386–405. Three weeks later, EAE was induced by a second immunization of the respective peptides mixed with proteolipid protein (PLP_AA139–151). Mice in the EBNA1_AA386–405 group generated robust antibody responses against both EBNA1_AA386–405 (Fig. 4a) and GlialCAM ICD (Fig. 4b). The antibody response to PLP_AA139–151 was unaltered in both groups (Extended Data Fig. 10a). In addition, EBNA1_AA386–405 immunization induced a strong CD4⁺ T cell response, whereas the T cell response against PLP_AA139–151 remained stable in both groups (Extended Data Fig. 10b). EBNA1_AA386–405 stimulated the secretion of B cell stimulatory T helper 1 cytokines, including interferon-γ (IFNγ), tumour necrosis factor and interleukin-12 (IL-12), as well as IL-6 and IL-10 (Extended Data Fig. 10c–g), but suppressed the key T helper 17 cytokine IL-17 (Extended Data Fig. 10h). Clinically, the EBNA1-treated group exhibited more severe paresis (Fig. 4c), with enhanced CNS immune cell infiltration (Fig. 4d, e) and demyelination (Extended Data Fig. 10i, j).

**Fig. 4: Anti-EBNA1_AA386–405 immunization exacerbates autoimmune-mediated demyelination in vivo.**

To further assess T cell reactivity in humans, peripheral blood mononuclear cells (PBMCs) from patients with MS (n = 7) with increased anti-EBNA1 and anti-GlialCAM titres were stimulated with EBNA1 and GlialCAM proteins and peptides and compared with PBMCs from healthy individuals. The CD4⁺ T cells trended towards more IFNγ expression after stimulation with EBNA1_AA386–405 and GlialCAM ECD and ICD proteins, which resembled the CD4⁺ T cells in mice (Extended Data Fig. 10k, l). In CD8⁺ T cells, high expression of IFNγ and granzyme B indicated a robust CD8⁺ T cell response against EBNA1 in both groups, whereas only CD8⁺ T cells from patients with MS responded to GlialCAM ICD and GlialCAM ECD (Fig. 4f). One patient (MS16) (Fig. 3o, p) showed extraordinarily high counts of IFNγ⁺granzyme B⁺CD8⁺ T cells after stimulation with EBNA1, GlialCAM ICD and GlialCAM_AA370–389 (Extended Data Fig. 10m).

Together, these results show that anti-GlialCAM antibodies are generated in response to EBNA1_AA386–405 immunization. Furthermore, immunization of mice with both EBNA1_AA386–405 and PLP_AA139–151 enhanced CNS immune cell infiltration and demyelination, two prominent features of human MS pathology. In addition to anti-GlialCAM antibody titres, our human T cell data suggest an important role for CD8⁺ T cells in the immune response against GlialCAM.

Discussion

Viral triggers of MS and other autoimmune diseases have long been the subject of intense investigation, but evidence for their functional relevance is scarce⁸. By utilizing paired-chain BCR repertoire sequencing, rational selection of clonal antibody sequences and three independent high-throughput proteomics platforms, we identified a mAb from CSF of a patient with MS that binds the MS-associated epitope EBNA1_AA386–405 with high affinity and cross-reacts with GlialCAM. We demonstrated the presence of cross-reactive EBV EBNA1 and GlialCAM antibodies in 20–25% of patients with MS and showed that immunization of EAE mice with this EBNA1 epitope exacerbated autoimmune demyelination. Our findings demonstrate a mechanistic link between EBV infection and the pathobiology of MS.

Our analysis of the single-cell paired-chain BCR repertoire from blood and CSF of patients with MS revealed features of intrathecal oligoclonal expansion with ongoing SHM that were substantially different from CSF BCR repertoires in other neuroinflammatory diseases. PBs in the CSF of patients with MS are highly clonal, with long CDR3 regions and skew towards the use of five IGHV genes^{16,17,18,19,38,39}. IGHV3-7 has been previously observed in MS CSF and OCBs^{17,19,39,40,41}. The discovery that the IGHV3-7-based mAb MS39p2w174 cross-binds EBV EBNA1 and GlialCAM provides a direct link between IGHV3-7 and MS pathobiology.

Structural and binding data of MS39p2w174 from the CSF of a patient with MS and its unmutated germline ancestor showed that only germline bound EBNA1_AA486–405 with high affinity, and that SHM is required for high-affinity cross-reactivity with GlialCAM. Owing to the CNS-restricted expression of GlialCAM, it is likely that immature IGHV3-7-expressing B cells encoding a germline precursor of MS39p2w174 entered the CNS and CSF space, encountered GlialCAM antigen and then underwent affinity maturation that generated clones encoding high-affinity anti-GlialCAM antibodies. This is concordant with our BCR repertoire analysis, which revealed a highly clonal and skewed repertoire in CSF with low polyreactivity that is indicative of a select group of B cells undergoing SHM, probably driven by perpetual activation by CNS GlialCAM.

The crystallographic structure revealed that Arg397 in EBNA1_AA386–405 engages in two hydrogen bonds with HC-CDR2 and is probably responsible for a notable part of the high binding affinity between MS39p2w174 and EBNA1. We showed that phosphorylation of GlialCAM at Ser376 restores high affinity. Epitopes altered by PTMs have been described as targets for autoimmune responses, including citrullinated proteins in rheumatoid arthritis and phosphorylated Ro/La in systemic lupus erythematosus^37,42. Tissue-specific differences of PTMs could contribute to a lack of central tolerance. Several kinases have been described as risk genes for MS, including MERTK, MAPK1, MAPK3 and TYK2, which potentially contribute to alternative phosphorylation patterns in the CNS⁴³.

In addition, we showed that immunization of EAE mice with EBNA1_AA386–405 generates a robust B cell response against GlialCAM and aggravates EAE. Our finding of activated PBs in the CSF that express exceptionally high levels of HLA-DR suggest that these B cells present antigens and exchange inflammatory signals with T follicular helper cells.

In summary, we presented a detailed picture of the B cell repertoire in MS CSF and blood and demonstrated that activated intrathecal IgG⁺ PBs undergo affinity maturation. Analysis of a CSF-derived mAb that targets EBNA1_AA386–405 revealed molecular mimicry to GlialCAM. These findings provide a mechanistic link between EBV infection and the pathobiology of MS.

Methods

Study design and human participants

Patient samples were collected at Stanford University and the University of Heidelberg. Relapsing–remitting MS was diagnosed according to the current McDonald criteria^44,45. None of the patients met the diagnostic criteria for neuromyelitis optica spectrum disorder, in particular spinal lesions spanning ≥3 segments⁴⁶. Patients were tested for antibodies against aquaporin-4 and myelin oligodendrocyte glycoprotein and showed negative results. All included patients had increased CSF white blood cell counts (≥10 cells µl^–1), and blood-contaminated CSF samples were excluded by visual and microscopy inspection. Paired peripheral blood and CSF samples were obtained at the time of clinical onset (clinically isolated syndrome) or during an acute relapse. All but one patient had not received any MS-specific treatment before sample collection (Extended Data Table 1). As this study does not explore group differences, no specific randomization strategy has been applied for the selection of study participants. MS is a disease that predominantly affects women, which is reflected in our study cohort which contained paired CSF and blood samples from n = 8 female and n = 1 male MS patients. The study size is in line with prior repertoire studies investigating both, single-cell and bulk B cell repertoires in MS and other diseases¹³,¹⁶. All experimental protocols were approved by the institutional review board (IRB) of Stanford University (IRB number 34529) and the ethics committee of the medical faculty of the University of Heidelberg (IRB number S-466/2015). Written informed consent was obtained from each patient.

Cell preparation, antibody staining and flow cytometry cell sorting

CSF was centrifuged immediately after lumbar puncture and cells were counted. PBMCs were isolated from heparinized blood by density gradient centrifugation using Ficoll Plus medium (Cytiva). Cells were magnetically separated with anti-CD19 magnetic beads (Dynabeads CD19 Pan B cell isolation kit, Invitrogen), then stained according to standard protocols using antibodies against the following cell surface markers: CD20 (clone L27, dilution 1:10), CD38 (clone HB7, dilution 1:30) and IgD (clone IA6-2, dilution 1:20) from BD Biosciences); CD3 (clone OKT3, dilution 1:60), CD19 (clone HIB19, dilution 1:20), CD27 (clone O323, dilution 1:20), IgM (clone MHM-88, dilution 1:40), HLA-DR (clone L243, dilution 1:100) and α4 integrin (clone 9F10, dilution 1:100) from BioLegend; IgA (clone IS11-8E10, dilution 1:20) from Miltenyi Biotec; and Sytox blue (dilution 1:500) from ThermoFisher Scientific. Single cells were sorted using a FACSAria II cell sorter (BD Biosciences) with FACSDiva (v.8.0, BD Biosciences) into 96-well PCR plates (Bio-Rad). For single-cell repertoire sequencing, PBs were sorted from PBMCs (plasmablast gate (4.12%) in panel 5 in the representative flow cytometry plots shown in Extended Data Fig. 1a). All B cells were sorted from CSF (B cell gate (73.9%) in panel 4 in the representative flow cytometry plots shown in Extended Data Fig. 1b). FlowJo v.10.7.1 (BD) and R v.3.6.1 were used to evaluate flow cytometry data.

Single-cell BCR repertoire sequencing

BCR repertoire sequencing was carried out using our in-house developed plate-bound single-cell sequencing technology as previously described^15,47,48. In brief, reverse transcription with oligo-dT was carried out in separate wells, attaching unique well-ID barcodes by template switching activity of Maxima Reverse Transcriptase (ThermoFisher Scientific). Barcoded cDNA from each plate was pooled and amplified in three consecutive PCRs, including attaching plate-specific barcodes and sequencing adapters. PCRs were carried out separately for the HC of IgG, IgA and IgM, as well as for the κ-chain for λ-LC, and separate libraries were generated from each. Samples were then gel-purified, cleaned with Ampure XP beads (Beckman Coulter) and sequenced on an Illumina MiSeq (Illumina) with 2 × 330 paired-end reads.

Sequence analysis

The MiSeq FASTQ workflow was used for Fastq generation and plate demultiplexing. R v.3.6.1 was used for custom analyses. Paired reads of sequences that passed quality thresholds were stitched and separated by plate and well IDs. Similar reads sharing the same plate and well IDs were clustered into operational taxonomic units⁴⁹. Consensus sequences were aligned to germline variable-chain immunoglobulin sequences with IMGT HighV-QUEST (v.1.3.1)⁵⁰, which reports V, D and J germline genes, HC and LC CDR3 lengths, and non-silent mutation counts and locations. Clonal expansions were defined on the basis of sharing the same HC and LC V and J genes and exhibiting >70% amino acid identity within the HC and LC CDR3s. Per cent clonality represents the per cent of all sequences that fulfil these criteria. To calculate IGHV, IGLV, IGHJ and IGLJ gene usage, the per cent abundance of each particular gene was calculated in blood and CSF PBs of each patient, and means were calculated across patients. Genes that were present in fewer than three CSF samples were excluded from this analysis. Although our sequencing method preferentially captures PB sequences owing to higher amounts of immunoglobulin mRNA (Extended Data Fig. 2m), enough non-PB B cell sequences passed filter thresholds to compare the non-PB repertoire to the PB repertoire in seven patients (Extended Data Fig. 2a, b). For patient samples MS12 and C6, only PBs were captured (while gating on all B cells), and for MS39, only PBs were sorted. For phylogenetic analysis, sequences were binned according to their HC V-gene family and V gene. Concatenated LC and HC were then aligned with Muscle⁵¹ and clustered with PhyML⁵² using maximum-likelihood clustering. Each tree-partition was rooted by their HC V-gene. Phylogenetic trees were drawn in Python using the ETE 3 toolkit⁵³.

Peptide identification by mass spectrometry

Immunoglobulins were purified from 1.5 ml of CSF samples with Protein A (ThermoFisher Scientific). The purified IgG samples were reduced with 0.02 M dithiothreitol at 57 °C for 1 h, alkylated with 0.05 M iodoacetamide at room temperature (RT) in the dark, and digested with trypsin overnight at RT. Peptides were extracted and desalted as previously described⁵⁴. An aliquot of the peptide mixtures was loaded onto an Acclaim PepMap 100 precolumn (75 μm × 2 cm, C18, 3 μm, 100 Å) in-line with an EASY-Spray, PepMap column (75 μm × 50 cm, C18, 2 μm, 100 Å) with a 5-μm emitter using the autosampler of an EASY-nLC 1000 (ThermoFisher Scientific). The peptides were gradient eluted into a Lumos Fusion Tribrid (ThermoFisher Scientific) mass spectrometer using a 120-min gradient from 5% to 35% solvent B (90% acetonitrile, 0.5% acetic acid), followed by 10 min from 35% to 45% solvent B and 10 min from 45% to 100%. High-resolution full mass spectrometry spectra were acquired with a resolution of 120,000, an AGC target of 4 × 10⁵, a maximum ion time of 50 ms and a scan range of 400–1,800 m/z. Following each full mass spectrometry scan, as many data-dependent HCD tandem mass spectrometry spectra were acquired in the orbitrap as possible in a 3-s cycle time. Monoisotopic precursor selection (MIPS) was set to peptide, precursors with a charge state of 2–7 and minimum intensity of 5 × 10⁴ were selected for tandem mass spectrometry. Dynamic exclusion was set to 60 s after a single selection. All tandem mass spectrometry spectra were collected using the following instrument parameters: resolution of 30,000, an AGC target of 10⁵, maximum ion time of 120 ms, 2 microscans, 1.6 m/z isolation window and normalized collision energy of 32.

The tandem mass spectrometry spectra were searched against the respective peptide-specific database, including common contaminant proteins, using the search engine Byonic⁵⁴. The search parameters were set to trypsin allowing two missed cleavages, fixed modification of carbamidomethyl on cysteine, variable modification of oxidation on methionine and deamidation on glutamine and asparagine. Peptides mapping to variable regions of IgG were manually verified. To include only sequence-specific peptides, peptides that aligned to non-immunoglobulin or constant-region sequences were excluded from the analysis, as were peptides that aligned to the repertoire of multiple patient samples. Included were peptides that aligned to one variable sequence in a single patient. Peptides that aligned to more than one variable sequence in a single patient were included if all matching sequences were exact matches or clonally related, in which case the peptide was counted as representative for all matches. Counts of identical or non-identical peptide-spectral matches per sequence were tallied for each sequence. Sequences that had >1 or >10 matching peptides were presented as a percentage of all sequences (Fig. 1d and Extended Data Fig. 2j, k). The mass spectrometry files are accessible at MassIVE (https://massive.ucsd.edu) under accession number MSV000086842.

Selection and recombinant expression of mAbs

Representative antibodies from the largest clonal B cell expansions in the CSF of each patient were selected for recombinant expression. In patients with more than 10 large clonal expansions, sequences were preferentially chosen based on their usage of one of the 11 most abundant IGHV genes in the CSF (Extended Data Fig. 3). HC and LC variable sequences were custom-generated (IDT) and cloned into pFuse vectors (Invivogen) that contained human IgG constant region or kappa or lambda constant regions, respectively. Fab HC was expressed in in-house plasmids that contained the HC constant-region C1 up to Cys103. Plasmids were transfected into Expi293T cells using Expifectamine (ThermoFisher Scientific). Authenticity of 293T cell lines were certified by the supplier. Cell cultures were tested regularly for mycoplasma contamination. Culture medium was collected after 4 days and 7 days after transfection. mAbs and Fabs were purified with protein A and protein G resins, respectively (ThermoFisher Scientific). Antibody concentrations were measured with a nanodrop spectrophotometer (ThermoFisher Scientific) and hIgG quantitation ELISAs (Bethyl Laboratories) and checked for purity on SDS protein gels with Coomassie staining.

Protein expression and purification

The following EBNA1 proteins and peptides were obtained: full-length AA1–641 (Abcam), AA328–641 (Virion Serion) and AA408–641 (ProspecBio). The following GlialCAM proteins and peptides were obtained: full-length AA34–416 (OriGene) and ECD AA34–234 (Novoprotein). GlialCAM ICD AA262–416 was expressed in Escherichia coli with an N-terminal His-Tag. In brief, the codon-optimized sequence was cloned into a pet30(+) vector, expressed in BL21 chemically competent E. coli (Sigma Aldrich) to an optical density of 600 nm, and induced with IPTG (Sigma Aldrich) for 3 h at 37 °C. Cell pellets were disrupted by sonication, and proteins were purified with complete His-Tag purification resins (Roche Life Science), followed by size-exclusion purification (Cytiva). For all other used peptides and proteins see Supplementary Tables 2–4.

Planar protein microarrays

Protein microarrays were generated as previously described^55,56 (https://web.stanford.edu/group/antigenarrays/). In brief, peptides, recombinant proteins and lysates were diluted at the indicated concentrations in a 1:1 solution of PBS/water and protein printing buffer (ArrayIt) (Supplementary Tables 2–4), aliquoted into 384-well plates and printed on SuperEpoxy slides using a NanoPrint LM210 system (ArrayIt). Two independent quadruplicates of each analyte were spotted, and some proteins were used in several versions/preparations from different sources (Supplementary Table 2). Ready-made HuProt Arrays v.3.1 were obtained from CDI Labs. Arrays were circumscribed with a hydrophobic marker, blocked overnight at 4 °C in PBS containing 3% FCS and 0.1% Tween-20, and incubated with individual mAbs at a concentration of 1 µg ml^–1 for 1 h at 4 °C, then washed twice for 20 min each in blocking buffer on a rotating shaker. Arrays were then incubated with Cy-3-conjugated secondary goat anti-human IgG (0.8 μg ml^–1; Jackson ImmunoResearch) for 1 h at 4 °C, then washed twice for 30 min each in blocking buffer, twice for 30 min each in PBS, and twice for 15 s each in water. Arrays were spun dry and scanned with a GenePix 4000B scanner (Molecular Devices). Median pixel intensities for each fluorescent spot were determined with GenePix Pro-3.0 software (Molecular Devices). Z-scores for each row of antigens were calculated for viral antigens, whereas raw intensities were analysed for GlialCAM arrays. Heatmaps were generated with Morpheus software (The Broad Institute; https://software.broadinstitute.org/morpheus).

PhIP–seq

PhIP–seq was performed using a human proteome-wide library, expressing overlapping 49-amino-acid peptides with a 24-amino-acid sliding window approach starting at the N terminus. In brief, 2 μl (1 μg ml^–1) of substrate antibody was diluted 1:100 in blocking buffer for two sequential rounds of immunoprecipitation. After the second round of immunoprecipitation and amplification in E. coli, next-generation sequencing libraries were prepared for paired-end 150 base next-generation DNA sequencing on the Illumina Hi-Seq platform as previously described^28,57. After alignment of the reads to the reference peptide sequences, quality control was performed, and only reads present at an abundance of fewer than ten reads per hundred thousand were carried forward. The number of reads mapping to each peptide were then counted and individually scored as a percentage of the total.

ELISA

The following cytokine ELISA kits were used according to the manufacturers’ instructions: mouse IL-6, IL-10, IL-12, IFNγ and TNF (BD Biosciences), and IL-17A (ThermoFisher Scientific). For protein and peptide ELISAs, MaxiSorp 384-well plates (ThermoFisher Scientific) were coated with 1 µg ml^–1 peptide or protein in carbonate-bicarbonate buffer at 4 °C overnight, then washed 6 times with PBST (PBS + 0.05 % Tween20), blocked with blocking buffer (PBS + 1% BSA) for 1 h, and mAbs were applied at 1 µg ml^–1 in blocking buffer. Human and mouse plasma samples were diluted 1:100 and T cell supernatants 1:4 in blocking buffer. After overnight incubation at 4 °C, plates were washed again 6 times with PBST and then secondary antibody HRP-conjugated goat anti-human IgG (Jackson ImmunoResearch) was applied for 1 h at RT. After six additional washes with PBST, plates were developed with TMB substrate (ThermoFisher Scientific), stopped with 1 N sulfuric acid and read on a SpectraMax Paradigm Microplate Reader (Molecular Devices). For plasma ELISAs with blocking of plasma IgG, MaxiSorp 384-well plates were coated with 2 µg ml^–1 recombinant Protein G (Acro Biosystems) at 4 °C overnight, then washed six times with PBST and incubated with 1:100 diluted plasma at 4 °C overnight. Plates were again washed 6 times with PBST, then incubated with the respective blocking peptides at 10 µg ml^–1 for 2 h at room temperature. Biotinylated EBNA1_AA385–405 was added at 1 µg ml^–1 and incubated for 1 h at room temperature. Plates were washed again six times with PBST, incubated with HRP-conjugated streptavidin (BioLegend) for 1 h at room temperature and developed with TMB substrate as described above.

Western blotting

Western blots were run according to standard protocols. In brief, purified proteins were boiled in Laemmli buffer with 10% β-mercaptoethanol for 5 min, run on 4–12% Criterion XT Bis-Tris protein Gels (Bio-Rad) and then transferred onto a nitrocellulose membrane using a Trans-Blot Turbo semi-dry transfer system (Bio-Rad). The blots were stained with MS39p2w174 at 10 µg ml^–1 or with mouse anti-EBNA1 antibody (Biorbyt) or mouse anti-GlialCAM antibody (R&D Systems) followed by secondary HRP-conjugated goat anti-human IgG and anti-mouse IgG (Jackson ImmunoResearch). The western blots in Figs. 2c and 3c were performed on separate membranes. Coomassie gels were run concomitantly, fixed with 10% methanol and 7% acetic acid, and stained according to standard protocols. Uncropped western blot and Coomassie images are available in Supplementary Fig. 1.

Fluorescent immunohistochemistry on mouse brain slices and immunofluorescence on primary cultured rat oligodendrocytes

An adult mouse (F₁ generation of FVB × C57BL/6 cross) was transcardially perfused with 4% paraformaldehyde (PFA) and post-fixed in 4% PFA overnight at 4 °C. After sucrose equilibration, the brain was blocked in OCT and sectioned at 12 µm on a standard cryostat. Sections were permeabilized and blocked in PBS containing 10% lamb serum and 0.1% Triton X-100. Sections were immunostained with concomitantly expressed control mAb anti-DSG3 (Acc: HQ338093.1 and HQ338094.1; 18 µg ml^–1), MS39p2w174 (18 µg ml^–1) or PBS in blocking buffer overnight at 4 °C. Sections were washed five times with PBS over 1 h and counterstained with anti-human IgG for 1 h at room temperature (2 µg ml^–1 Alexa Fluor 488, Jackson ImmunoResearch). Nuclei were stained with DAPI at 1:2,000 for 5 min at room temperature. Rat oligodendrocyte precursor cells were prepared from rat embryos followed by panning and in vitro differentiation into primary rat oligodendrocytes⁵⁸. Cells on coverslips were permeabilized with ice-cold 100% methanol for 10 min, blocked with 10% donkey serum for 1 h at room temperature and then stained with isotype control (anti-DSG3) or MS39p2w174 at 10 µg ml^–1 in 1% donkey serum for 1 h at RT, before incubation with secondary Alexa Fluor 647 donkey anti-human IgG antibody (Jackson ImmunoResearch) for 1 h at RT. Confocal images were taken with a Zeiss LSM 880 confocal microscope using Zen software (Zeiss).

Bio-layer interferometry

Association and dissociation constants of mAbs to proteins and peptides were measured using bio-layer interferometry on an Octet QK device (Fortebio/Sartorius) according to standard protocols. For peptide kinetics, biotinylated peptides were bound to high-precision streptavidin (SAX) biosensors (peptide concentration in solution of 100 nM), and the mAbs MS39p2w174 and germline were probed as analytes in concentrations ranging from 10 to 270 nM. For protein kinetics, mAbs were bound to anti-hIgG Fc capture (AHC) biosensors (mAb concentration in solution of 20 nM), and proteins were probed as analytes in concentrations ranging from 1.56 to 125 nM. Data were analysed with bio-layer interferometry analysis software (Fortebio/Sartorius, v.7.1) and GraphPad prism (v.8.4). Buffer controls were subtracted, and curves were fitted globally for each group consisting of all concentrations of the same ligand. K_d values ± s.d. as well as association–dissociation curves are reported and plotted with GraphPad prism (v.8.4). K_d, K_on and K_off values are shown in Supplementary Table 6. K_d values reported in Figs. 2k and 3e, k are mean ± s.d. values from at least three serial dilutions from one representative out of three independent experiments.

Prediction of protein disorder

Order and disorder along the amino acid sequences of EBNA1 and GlialCAM were analysed using predictor of natural disordered regions (PONDR; WSU Research Foundation)⁵⁹ with the VSL2 algorithm.

Crystallization of antibody–antigen complexes

EBNA1_AA386–405 20mer peptides (>98% purity) (Sigma Aldrich) were mixed with MS39p2w174-Fab (15 mg ml^–1) in a 7.5:1 molar ratio and incubated overnight. Crystals for MS39p2w174-Fab and EBNA1_AA386–405 grew in 0.48 M sodium citrate, 0.72M sodium/potassium phosphate and 3% MPD (v/v) in 0.1 M HEPES, pH 6.9 (Extended Data Fig. 7c). Crystals were collected, cryo-protected with a quick dip in a cryo-solution containing the well solution with 25% glycerol and flash-cooled in liquid nitrogen. Data were collected at beamline SSRL 12-2 at the Stanford Synchrotron Radiation Lightsource, SLAC National Accelerator Laboratory, and processed and scaled using XDS/aimless and Staraniso^60,61. Crystals belonged to space group I222 (a = 119.66 Å, b = 137.56 Å, c = 179.00 Å, α = β = γ = 90°) and contained two Fab–peptide complexes per asymmetric unit (Extended Data Fig. 7d). Phaser was used for molecular replacement⁶² with the model structure 4LRI (PDB)⁶³ stripped of all CDR loops. Loops were reconstructed with Coot⁶⁴ and structures were refined with phenix.refine⁶⁵,⁶⁶ in iterations with Coot. Measurements and figure design were performed using Pymol (v.2.1)⁶⁷. The structure was deposited in PDB (https://www.rcsb.org)²¹ with the PDB identifier 7K7R.

Mouse immunization, EAE and histology

All animal experiments were performed in accordance with state and federal guidelines and regulations, and approved by the Stanford Institutional Animal Care and use Committee. Eight-week-old female SJL/J and FVB × C57BL/6 mice were purchased from The Jackson Laboratory. The mice were housed in recyclable individually ventilated cages, with a 12-h light/dark cycle, at a temperature of 21 °C and with 50% humidity. Mice were immunized subcutaneously with 200 µg per mouse of EBNA1_AA386–405 (peptide sequence: SQSSSSGSPPRRPPPGRRPF) or scrambled control peptide (peptide sequence: SPSRPGRSRSRGSPFPQPSP) (10 mice per group), mixed with 100 µg per mouse of CpG (ODN1826, Invivogen) in 100 µl per mouse incomplete Freund’s adjuvant (BD Difco). Three weeks later, EAE was induced by subcutaneous immunization with 200 µg per mouse of PLP_AA139–151, mixed with the same peptides used in the first immunization, in 100 µl of incomplete Freund’s adjuvant, supplemented with 200 µg per mouse of mycobacterium tuberculosis (strain H37 RA, BD Difco). Serum samples were obtained by retro-orbital blood draws 3 days before the first and second immunizations (day –24 and day –3), and at the termination of the experiment (day 50). Mice were weighed every day, and disease severity was assessed in a blinded manner according to a 5-point standard scoring system: 0, no clinical signs; 1, loss of tail tone; 2, hindlimb weakness; 3, complete hindlimb paralysis; 4, hindlimb and forelimb paralysis; 5, moribund or dead. Mice were euthanized on day 50 after induction of EAE by deep anaesthesia with intraperitoneal injections of 0.01 ml g^–1 body weight 7.2% xylazine (Bayer Healthcare) and 10.8% ketamine (Pfizer). Lymph nodes and spleens were removed, and mice were then perfused with 10 ml PBS and 20 ml 4% PFA (Electron Microscopy Sciences). Brains and spinal cords were removed, stored in 4% PFA overnight followed by 30% sucrose in PBS. Tissues were embedded in paraffin, sectioned and stained for H&E as well as Luxol fast blue according to standard protocols. Infiltration of inflammatory cells into the spinal cord on H&E slides was assessed by a blinded investigator by counting lesions of infiltrating cells per slide, taking lesion size into account. The following scoring system was used: 1, small infiltrate (<10 cells); 2, medium infiltrate (<100 cells); 3, large infiltrate (>100 cells). Demyelination was assessed by a blinded investigator according to a histological score⁶⁸ as follows: 0.5, single demyelinated spot; 1, several spots; 2, confluent sites of demyelination; 3, extensive demyelination, less than half of a spinal cord; 4, demyelination of more than half of the spinal cord; and 5, extensive demyelination affecting >85% of the total white matter of the spinal cord.

In vitro human T cell stimulation with proteins and peptides

Cryopreserved PBMCs were thawed and stabilized overnight at 37 °C. The cells were pre-incubated for 30 min at 37 °C, 5% CO₂ with polymyxin B (Sigma Aldrich) at a concentration of 10 μg ml^–1. The cells were then incubated for 16 h with 100 μM of each recombinant protein or peptide in the presence of 2 μg ml^–1 of anti-human CD28 (clone CD28.2, BD Biosciences) and anti-CD49d (clone 9F10, BioLegend) antibodies and IL-2 (50 IU ml^–1, Peprotech) and IL-7 (5 ng ml^–1, Peprotech). To detect intracellular staining, eBioscience Protein Transport Inhibitor cocktail (500X, ThermoFisher Scientific) was added during the final 5 h of culture. After 16 h, the cells were labelled with Fixable Viability Stain 510 (BD Biosciences) for live cell staining and fluorophore conjugated anti-CD3 (clone SK7, BD Biosciences), CD4 (clone RPA-T4, BD Biosciences), CD8 (clone RPA-T8, BD Biosciences), granzyme B (clone GB11, BD Biosciences), IFNγ (clone B27, BD Biosciences) and IL-17A (clone BL168, BD Biosciences) antibodies and detected using a BD LSR Fortessa.

Data analysis and statistics

The publicly available dataset from Han et al.²⁷ was searched for abundance of GlialCAM in MS lesions. The old NCBI Protein Database accession number Q8N7I3 was found, which was annotated in 2008 as unknown hypothetical protein and has since been replaced by accession number Q14CZ8. GlialCAM was identified with 2.5 mean spectral counts (MSCs) in control tissue, 1.3 MSCs in chronic plaques, 1.8 MSCs in acute plaques and 8 MSCs in chronic-active plaques.

GraphPad Prism v.8.4.1 and R v.3.6.1 were used for statistical analyses. Statistical tests used are indicated in the respective section of the Methods or in the figure legends.

Reporting summary

Further information on research design is available in the Nature Research Reporting Summary linked to this paper.

Data availability

The genomic datasets analysed during the study have been uploaded to the Sequence Read Archive (https://www.ncbi.nlm.nih.gov/sra) with accession number PRJNA780931. Mass spectrometry data are available at MassIVE (https://massive.ucsd.edu) with accession number MSV000086842. Structural data are available at PDB (https://www.rcsb.org) with the identifier 7K7R. Source data are provided with this paper.

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Acknowledgements

We thank W. Wick for support with sample collection; B. Bell for advice on crystallization; G. Harauz for insightful discussions on poly-proline motifs; and the staff at SSRL for assistance with data collection. This work was supported by NIH R01 AR063676 and U19 AI110491 to W.H.R., the Juvenile Diabetes Research Foundation and Lupus Research Alliance Funding to W.H.R. and T.V.L., the German Research Foundation (DFG, LA3657/1) to T.V.L., Atara to L.S. and P.P.H., and the German Research Foundation to M.P. (DFG, project 406052676; PL-315/5-1). The mass spectrometry experiments were in part supported by the NYU Grossman School of Medicine and a shared instrumentation grant (NIH 1S10OD010582-01A1). Use of the Stanford Synchrotron Radiation Lightsource, SLAC National Accelerator Laboratory, is supported by the US Department of Energy, Office of Science, Office of Basic Energy Sciences under contract number DE-AC02-76SF00515. The SSRL Structural Molecular Biology Program is supported by the DOE Office of Biological and Environmental Research, and by NIH GIGMS P30GM133894. C.M.B. is a Hanna H. Gray Fellow at the Howard Hughes Medical Institute. The contents of this publication are solely the responsibility of the authors and do not represent the official views of the NIGMS or the NIH.

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Authors and Affiliations

Division of Immunology and Rheumatology, Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
Tobias V. Lanz, R. Camille Brewer, Jae-Seung Moon, Alejandro M. Gomez, Gabriel-Stefan Nadj & William H. Robinson
Department of Neurology, Mannheim Center for Translational Neurosciences (MCTN), Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
Tobias V. Lanz & Michael Platten
Department of Neurology and National Center for Tumor Diseases, University Hospital Heidelberg, Heidelberg, Germany
Tobias V. Lanz & Michael Platten
The Geriatric Research, Education, and Clinical Center (GRECC), VA Palo Alto Health Care System, Palo Alto, CA, USA
Tobias V. Lanz, R. Camille Brewer, Jae-Seung Moon, Alejandro M. Gomez, Gabriel-Stefan Nadj & William H. Robinson
Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Beckman Center for Molecular Medicine, Stanford, CA, USA
Peggy P. Ho & Lawrence Steinman
Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Beckman Center for Molecular Medicine, Stanford, CA, USA
Kevin M. Jude, Ricardo A. Fernandes & K. Christopher Garcia
Macromolecular Structure Knowledge Center, Stanford ChEM-H Institute, Stanford, CA, USA
Daniel Fernandez
Weill Institute for Neurosciences, Department of Psychiatry and Behavioral Sciences, University of California San Francisco, San Francisco, CA, USA
Christopher M. Bartley
Weill Institute for Neurosciences, Department of Neurology, University of California San Francisco, San Francisco, CA, USA
Ryan D. Schubert, Isobel A. Hawes & Michael R. Wilson
Department of Biochemistry and Biophysics, University of California San Francisco, San Francisco, CA, USA
Sara E. Vazquez & Joseph L. DeRisi
Department of Neurosurgery, Stanford University School of Medicine, Stanford, CA, USA
Manasi Iyer & J. Bradley Zuchero
Institute of Experimental Immunology, Euroimmun AG, Lubeck, Germany
Bianca Teegen
Division of Neuroimmunology, Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, USA
Jeffrey E. Dunn, Christopher B. Lock & Lucas B. Kipp
Department of Biochemistry and Molecular Pharmacology, NYU Perlmutter Cancer Center, NYU School of Medicine, New York, NY, USA
Victoria C. Cotham & Beatrix M. Ueberheide
NYU Langone Health Proteomics Laboratory, Division of Advanced Research Technologies, NYU School of Medicine, New York, NY, USA
Victoria C. Cotham & Beatrix M. Ueberheide
Preclinical Science and Translational Medicine, Atara Biotherapeutics, South San Francisco, CA, USA
Blake T. Aftab
Department of Medicine, Diabetes Center, University of California San Francisco, San Francisco, CA, USA
Mark S. Anderson
Chan Zuckerberg Biohub, University of California San Francisco, San Francisco, CA, USA
Joseph L. DeRisi
Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
Rachael J. M. Bashford-Rogers
DKTK Clinical Cooperation Unit Neuroimmunology and Brain Tumor Immunology, German Cancer Research Center (DKFZ), Heidelberg, Germany
Michael Platten

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Tobias V. Lanz
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Contributions

Conceptualization: T.V.L., L.S. and W.H.R. Methodology: T.V.L., R.C.B., P.P.H., K.M.J., D.F., R.A.F., A.M.G., R.D.S., B.T., V.C.C., B.M.U., J.-S.M., M.I. and J.B.Z. Software: T.V.L., R.C.B., D.F., K.M.J. and V.C.C. Validation: T.V.L., R.C.B., K.M.J., B.M.U., R.J.M.B.-R., K.C.G., L.S. and W.H.R. Formal analysis: T.V.L., R.C.B., K.M.J., D.F., A.M.G., C.M.B., V.C.C. and B.M.U. Investigation: T.V.L., R.C.B., P.P.H., D.F., G.-S.N., C.M.B., R.D.S., I.A.H., S.E.V., B.T., V.C.C., J.-S.M. and M.I. Resources: T.V.L., P.P.H., D.F., B.T., J.E.D., C.B.L., L.B.K., B.M.U., M.R.W., M.S.A., J.L.D., M.P., K.C.G., L.S. and W.H.R. Data curation: T.V.L., R.C.B., K.M.J., D.F., V.C.C. and B.M.U. Writing (original draft): T.V.L. Writing (review and editing): T.V.L., R.C.B., P.P.H., L.S. and W.H.R. Visualization: T.V.L., R.C.B. and K.M.J. Supervision: T.V.L. and W.H.R. Project administration: T.V.L. and W.H.R. Funding acquisition, T.V.L., P.P.H., B.T.A., M.P., L.S. and W.H.R.

Corresponding author

Correspondence to William H. Robinson.

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Competing interests

W.H.R. owns equity in, serves as a consultant to and is a member of the Board of Directors of Atreca, Inc. L.S. owns equity in and serves as a consultant to Atreca, Inc. Stanford University is in the process of applying for a patent, US Patent and Trademark Office Serial No. 63/131,581, covering anti-EBV antibodies generated by sequencing B cell repertoires, which lists T.V.L. and W.H.R. as inventors. The remaining authors declare no competing interests.

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Nature thanks Paul Farrell, George Georgiou, Hartmut Wekerle and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available.

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Extended data figures and tables

Extended Data Fig. 1 Analysis of B cell phenotypes in MS blood and CSF.

a–l, Flow cytometry data, a,b, representative flow cytometry plots are shown for a, blood and b, CSF. c, Plasmablasts as percent of all B cells in MS blood and CSF, means ± SD of n = 9 patient samples, **P = 0.004, two-tailed Mann-Whitney test. d, Non-plasmablast B cell subsets as percent of all B cells in blood (red) and CSF (blue), means ± SD of n = 8 patient samples, ***P = 0.0006, two-tailed Mann-Whitney test, Holm-Sidak corrected for multiple comparisons. e, Integrin alpha-4 expression in non-plasmablast B cells (red) and plasmablasts (blue), mean MFI ± SD of n = 9 patient samples, ****P < 0.0001, **P = 0.0013, two-way ANOVA, Tukey adjusted for multiple comparisons, f, representative histogram showing integrin alpha-4 expression in non-plasmablast B cells (red) and plasmablasts (blue) in blood (top panel) and CSF (lower panel), g, HLA-DR expression in non-plasmablast B cells (red) and plasmablasts (blue) in blood and CSF, mean MFI ± SD of n = 9 patient samples, ****P < 0.0001, ***P = 0.0002, two-way ANOVA, Tukey adjusted for multiple comparisons, and h, representative histogram showing HLA-DR expression in non-plasmablast B cells (red) and plasmablasts (blue) in blood (top panel), and CSF (lower panel). i, HLA-DR expression in patients carrying HLA-DRB1*15:01 (HLA-DR15, n = 5) vs. other HLA-genotypes (non-HLA-DR15, n = 4) in i, blood, and j, CSF, mean MFI ± SD, significance levels calculated with two-way ANOVA, k,l, Immunoglobulin classes in k, non-plasmablast B cells and l, plasmablasts in blood (red) and CSF (blue), mean MFI ± SD of n = 9 patient samples, ****P < 0.0001, two-way ANOVA, Holm-Sidak adjusted for multiple comparisons. Plasmablasts, PB; unswitched memory B cells, UM; switched memory B cells, SM; double negative B cells, DN.

Source data

Extended Data Fig. 2 Extended BCR repertoire data.

a–i, Single-cell BCR repertoire sequencing data, a, individual repertoires from all CSF B cells (top row) and subdivided into CSF plasmablasts (middle row) and non-plasmablast B cells (bottom row) of n = 9 MS patients. b, Individual repertoires of all CSF B cells (top row) and subdivided into CSF plasmablasts (middle row) and non-plasmablast B cells (bottom row) of n = 3 control patients. Numbers indicate number of sequences, inner circle: colored wedges represent clonal expansions and grey area represents singleton antibody sequences, outer circle: immunoglobulin classes, red: IgG, blue: IgA, green: IgM, sequence locations in outer circle correspond to inner circle. No non-plasmablast B cells were sorted for MS12 and C5. Only plasmablasts were sorted for MS39. c, Clonality, percent of clonal sequences in CSF B cells are shown, comparing BCR repertoires of control patients (n = 3) to MS patients (n = 9). Data corresponds to data shown in (Fig. 1b) and is separated into immunoglobulin classes IgG (left), IgA (center), and IgM (right). Means ± SD of individuals’ repertoires are shown. d, Immunoglobulin class distribution, percent of IgG (left), IgA (center), and IgM (right) of all CSF B cells are shown for n = 3 control patients and n = 9 MS patients. Means ± SD of individuals’ repertoires are shown. e, IGHV and IGLV cumulated mutation count in plasmablasts in blood (red) vs. CSF (blue), means ± SD of n = 9 patients samples. f, Mean HC CDR3 lengths (amino acid sequences) of plasmablasts in blood (red) vs. CSF (blue), means ± SD of n = 9 patient samples. g–i, Immunoglobulin gene distribution in blood vs. CSF plasmablasts for g, IGLV, IGKV1-33, ****P < 10⁻⁶, IGLV3-21, ****P = 3 x 10⁻⁶ according to unpaired two-tailed Student’s t tests, Holm-Sidak adjusted for multiple comparisons, h, IGHJ, and i, IGLJ. Each dot represents the usage of one gene across n = 9 MS patient repertoires in the respective compartments. Linear regression lines and 95% confidence intervals are shown. j, Mass spectrometry data of purified CSF immunoglobulins, showing variable chain sequences that could be uniquely identified in singleton BCR sequences vs. plasmablast sequences, peptide-spectral matches (PSM) cutoff ≥10, means ± SD of n = 9 MS patients, **P = 0.0012. k, l, Same mass spectrometry data set as in (j), showing variable chain sequences that could be uniquely identified in non-plasmablast BCR sequences vs. plasmablast sequences, means ± SD of n = 7 MS patients, k, PSM cutoff ≥1, **P = 0.007, l, PSM cutoff ≥10, *P = 0.037. m, Single-cell sequencing efficacy in non-plasmablast B cells (red) vs. plasmablasts (blue) in CSF. Fraction of sequences that passed filter thresholds are shown as percentages of the number of sorted cells in the respective group, means ± SD of n = 8 patient samples (no non-PB value for MS39). c, d, j–l, P according to unpaired two-tailed Mann-Whitney test. e–i, P according to unpaired two-sided Student’s t-test. Immunoglobulin heavy V gene, IGHV; Immunoglobulin heavy J gene, IGHJ; Immunoglobulin light V gene, IGLV; Immunoglobulin light J gene, IGLJ; peptide-spectral matches, PSM.

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Extended Data Fig. 3 Phylogenetic trees of B cells from MS blood and CSF.

Blood plasmablasts (top rows) and CSF B cells (bottom rows) of n = 9 MS patients and CSF B cells of n = 3 control patients are shown. Each node represents the full-length heavy chain and light chain sequence of a single B cell. Trees are binned according to their IGHV families and genes, then the concatenated heavy chain and light chain sequences are clustered. IgG (red), IgA (blue), IgM (green). Smaller brighter circles indicate singleton B cells, larger darker circles indicate clonal expansions. Arrows indicate sequences that were expressed as mAbs, numbers indicate V-gene mutation loads in heavy and light chains. Immunoglobulin heavy V gene, IGHV.

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Extended Data Fig. 4 Polyreactivity of recombinantly expressed antibodies.

a, ELISA data showing reactivity of recombinant mAbs against LPS (top), human insulin (middle), and dsDNA (bottom). Reactivity is represented in the order of decreasing reactivity to LPS in MS mAbs and control mAbs, respectively. Measurements were carried out in duplicates at 0.1, 1, and 10 µg/ml mAb concentrations and the area under the curve (AUC) for each mAb is shown from one experiment. Commercial anti-LPS antibody (cyan), MS39p2w174 (red), germline (orange), control mAbs (blue).

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Extended Data Fig. 5 MS CSF mAb reactivity to EBV and GlialCAM antigens.

a, mAb reactivities to EBV virus lysates and recombinant EBV proteins as well as to other virus lysates. Z-scores for each antigen are shown, measurement of one microarray experiment, measured in 8 technical replicates. b, mAb reactivities to LPS, Insulin, and dsDNA to assess polyreactivity. Z-scores of area under the curve (AUC) of ELISA measurements at antibody concentrations of 0.1, 1, and 10 µg/ml are shown, each measurement was carried out in duplicates. c, mAb reactivities to GlialCAM proteins, peptides, and phosphorylated or citrullinated peptides. Mean reactivities (mean fluorescence intensity counts) are shown from one microarray experiment, measured in 8 technical replicates. Immediate early latency stage protein, IE; early, E; late, L; intracellular domain, ICD; extracellular domain, ECD; phosphorylated Serine, pSer; citrulline residue, Cit; _B - _E: duplicate probes of same / similar lysates and proteins (different preparations or batches).

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Extended Data Fig. 6 MS CSF mAb reactivity to EBV peptides.

a, mAb reactivities to EBV peptides. Z-scores for each antigen are shown, measurement of one microarray experiment, measured in 8 technical replicates. Intracellular domain, ICD; extracellular domain, ECD; peptide mix, PM.

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Extended Data Fig. 7 mAb reactivity to EBV peptides and extended structural data for the EBNA1_AA386-405 / MS39p2w174-Fab complex.

a, mAb reactivities of selected reactive mAbs against the selected reactive peptide antigens. Z-scores for each antigen are shown, measurement of one microarray experiment, measured in 8 technical replicates. b, ELISA-based alanine-scan on EBNA1_AA386-405, corresponding to (Fig. 2e). Mean OD (450 nm) ± SD from three independent experiments, each carried out in triplicates. c, 20x image of protein crystals in hanging drop. d, Asymmetric unit containing two peptide-Fab complexes in a diagonal orientation, heavy chain (red/pink), light chain (blue/cyan), peptide (black/gray). e, EBNA1_AA386-405 peptide and its 2mFoDFc map (contoured at 1σ) are shown, depicted on heavy chain (cyan) and light chain (pink) in surface representation. f, g, Amino acid sequences of variable regions of f, mAb MS39p2w174 heavy chain and g, light chain. Bold font: CDR, regular font framework regions. Of the germline variable genes (bottom rows), only residues that differ from MS39p2w174 sequence are shown, red: residues that closely interact with EBNA1_AA386-405 according to crystal structure. dots: gaps introduced during IMGT GapAlign for alignment and numbering purposes, numbers: residue numbers according to IMGT unique numbering. Intracellular domain, ICD; extracellular domain, ECD; heavy chain, HC; light chain, LC; complementarity determining region, CDR; framework region, FR; germline, GL.

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Extended Data Fig. 8 Extended characteristics of GlialCAM_AA370-389 and immunofluorescence stainings with MS39p2w174.

a, Phage display PhiP-Seq data, showing alignment of Pro/Arg-rich region and adjacent residues of all phage display peptides enriched above 100 / 10⁵ reads. b, Immunofluorescence of mouse brain slices stained with (i) control antibody, and (ii-iv) MS39p2w174 (green) and DAPI (blue). (i,ii) full brain, scale bars: 2000 µm, (iii) magnification of hippocampus with prominent MS39p2w174 staining, scale bar: 400 µm, and (iv) olfactory bulb with prominent MS39p2w174 staining in the olfactory nerve (oln), glomerular (gl), and external plexiform layers (epl), but not the mitral (ml), internal plexiform (ipl), or granule cell (gcl) layers, scale bar: 100 µm. c, Immunofluorescence of primary rat oligodendrocytes with isotype control antibody (top panel) and MS39p2w174 (bottom panel). d, K562 cells in culture, wildtype (left) and transduced with full-length GlialCAM (right). e, Immunofluorescence with MS39p2w174 on WT K562 cells (top) and GlialCAM-tg K562 cells (center and bottom). White arrow: single K562 cell, orange arrow: high intensity MS39p2w174 staining on the cell border between transgenic K562 cells in bulks. c, e, Scale bars: 40 µm. b–e, representative micrographs of at least two experiments. f, Overview of phosphorylated residues in GlialCAM, identified by mass spectrometry (phosphoSite.org). The two phosphorylated serine residues of interest are indicated with arrows. g, ELISA, measuring binding of MS39p2w174 to native and citrullinated GlialCAM_AA370-389 peptides, means of n = 2 independent experiments, each carried out in triplicates. Wildtype, WT; extracellular domain, ECD; intracellular domain, ICD; phosphorylated serine, pSer; citrulline residue, Cit.

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Extended Data Fig. 9 Plasma reactivity against EBNA1 and GlialCAM proteins and peptides in healthy control individuals and MS patients.

a, ELISA measurement of antigen-specific IgG reactivity against peptides EBNA1_AA386-405, GlialCAM_AA370-389, phosphorylated GlialCAM_{AA370-389 pSer376}, 2x-phosphorylated GlialCAM_{AA370-389 pSer376 pSer377}, and scrambled peptide control in plasma samples of healthy control individuals (n = 50) and MS patients (n = 71). Means ± SD in each patient group is shown. Representative OD (450 nm) measurements of two independent experiments, each carried out in duplicates. **P < 0.01, ***P < 0.001 according to two-tailed Mann-Whitney test, Tukey corrected for multiple comparisons. b, ELISA measurements of antigen-specific IgG reactivity against GlialCAM full-length protein, GlialCAM_AA370-389, and phosphorylated GlialCAM_{AA370-389 pSer376} in plasma samples of a separate cohort of healthy control individuals (n = 31) and MS patients (n = 67). Means ± SD across patient groups are shown. Representative OD (450 nm) measurements of two independent experiments, each carried out in duplicates. *P < 0.05, **P < 0.01 according to two-tailed Mann-Whitney test, Tukey corrected for multiple comparisons. c, ELISA measurements of mAB MS39p2w174 binding to EBNA1_AA386-405, without interference as well as blocked with scrambled peptide control, EBNA1_AA386-405, and GlialCAM_{AA370-389 pSer376}, as a positive control to (Fig. 3q). Mean OD (450 nm) ± SD of quadruplicate measurements from n = 1 experiment are shown. *P < 0.05, **P < 0.01, ***P < 0.001 according to one-way ANOVA, Tukey corrected for multiple comparisons.

Source data

Extended Data Fig. 10 T cell response against EBNA_AA386-405.

a, ELISA data showing mouse plasma IgG responses against PLP_AA139-151 at the indicated timepoints pre and post EAE induction, for scrambled peptide immunized mice (blue, n = 10) and EBNA1_AA386-405 immunized mice (red, n = 10). Mean OD (450 nm) fold change ± SD, significance levels according to unpaired two-tailed Mann-Whitney test. Means ± SD, representative of three independent experiments, each carried out as triplicate measurements. b, T cell proliferation measurement by ³H-thymidine incorporation in splenocytes and lymph node cells of mice immunized with scrambled peptide (blue) and EBNA1_AA386-405 (red). Cells from n = 10 mice per group were pooled and mean counts per minute (cpm) ± SD of triplicate measurements are shown. P = 8.9 x 10⁻⁵, unpaired two-tailed Student’s t-test, Holm-Sidak corrected for multiple comparisons. c–h, ELISA measurements of cytokines in cell culture supernatant of mouse splenocytes and lymph node cells of mice immunized with scrambled peptide (blue) or EBNA1_AA386-405 (red) and re-stimulated with the indicated peptides. Cells from n = 10 mice per group were pooled and mean cpm ± SD of six replicate measurements are shown. c, IFN-γ, d, TNF, e, IL-12, f, IL-10, g, IL-6, h, IL-17, *P < 0.05, significance levels according to unpaired two-tailed Mann-Whitney test, Holm-Sidak corrected for multiple comparisons. i, Representative Luxol Fast Blue stained spinal cords from scrambled peptide group (top panel) and EBNA1_AA386-405 group (bottom panel). Scale bars left images: 200 μm, right images: 50 μm. j, Statistical evaluation of Luxol Fast Blue scores, means of at least 4 coronal spinal cord sections per mouse and means ± SD for each group (n = 9) are shown. ****P < 0.0001, unpaired two-tailed Mann-Whitney test. k, l, Flow cytometry data of PBMC from healthy control individuals (n = 6, blue) and MS patients (n = 7, red), showing percent of k, IFN-γ+ and l, IL-17+ CD4+ T cells in all CD4+ T cells. Mean MFI ± SEM are shown for the respective groups. Significance levels were assessed by two-way ANOVA, followed by FDR calculation using the two-stage step-up method of Benjamini, Krieger and Yekutieli, *Significat at FDR < 0.1. m, Flow cytometry data, representative dot plots are shown for two individuals from the data set presented in Fig. 4f. Healthy control individual (left) and MS patient MS16 (right). Expression levels of Granzyme-B (GZMB) and IFN-γ are presented under the indicated stimulations.

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Extended Data Table 1 Patient collective

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Extended Data Table 2 MS39p2w174 binding peptides identified by 49-mer phage display

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Supplementary information

Supplementary Information

This file contains Supplementary Tables 1–6, Supplementary Figs. 1 and 2, Supplementary Discussion and additional references.

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Lanz, T.V., Brewer, R.C., Ho, P.P. et al. Clonally expanded B cells in multiple sclerosis bind EBV EBNA1 and GlialCAM. Nature 603, 321–327 (2022). https://doi.org/10.1038/s41586-022-04432-7

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Received: 06 August 2021
Accepted: 14 January 2022
Published: 24 January 2022
Issue Date: 10 March 2022
DOI: https://doi.org/10.1038/s41586-022-04432-7

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Abstract

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Main

The B cell repertoire in MS CSF

CSF PBs produce oligoclonal IgG

CSF B cell-encoded antibodies bind EBV

Structure of the EBNA1–CSF Fab complex

Molecular mimicry of EBNA1 and GlialCAM

GlialCAM phosphorylation enables mimicry

Anti-GlialCAM IgG reactivity in MS

EBNA1 immunization aggravates EAE

Discussion

Methods

Study design and human participants

Cell preparation, antibody staining and flow cytometry cell sorting

Single-cell BCR repertoire sequencing

Sequence analysis

Peptide identification by mass spectrometry

Selection and recombinant expression of mAbs

Protein expression and purification

Planar protein microarrays

PhIP–seq

ELISA

Western blotting

Fluorescent immunohistochemistry on mouse brain slices and immunofluorescence on primary cultured rat oligodendrocytes

Bio-layer interferometry

Prediction of protein disorder

Crystallization of antibody–antigen complexes

Mouse immunization, EAE and histology

In vitro human T cell stimulation with proteins and peptides

Data analysis and statistics

Reporting summary

Data availability

References

Acknowledgements

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Contributions

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Competing interests

Peer review

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Additional information

Extended data figures and tables

Supplementary information

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