ARTICLE OPEN ACCESS

Clostridium bolteae is elevated in neuromyelitisoptica spectrum disorder in India and sharessequence similarity with AQP4Lekha Pandit MD DM PhD Laura M Cox PhD Chaithra Malli PhD Anitha DrsquoCunha PhD

Timothy Rooney MD PhD Hrishikesh Lokhande MSc Valerie Willocq BSc Shrishti Saxena MS and

Tanuja Chitnis MD

Neurol Neuroimmunol Neuroinflamm 20218e907 doi101212NXI0000000000000907

Correspondence

Dr Pandit

panditmnggmailcom

AbstractObjectiveTo understand the role of gut microbiome in influencing the pathogenesis of neuromyelitisoptica spectrum disorders (NMOSDs) among patients of south Indian origin

MethodsIn this case-control study stool and blood samples were collected from 39 patients withNMOSD including 17 with aquaporin 4 IgG antibodies (AQP4+) and 36 matched controls16S ribosomal RNA (rRNA) sequencing was used to investigate the gut microbiome Pe-ripheral CD4+ T cells were sorted in 12 healthy controls and in 12 patients with AQP4+NMOSD RNA was extracted and immune gene expression was analyzed using the NanoStringnCounter human immunology kit code set

ResultsMicrobiota community structure (beta diversity) differed between patients with AQP4+NMOSD and healthy controls (p lt 0001 pairwise PERMANOVA test) Linear discriminatoryanalysis effect size identified several members of the microbiota that were altered in patientswith NMOSD including an increase in Clostridium bolteae (effect size 423 p 000007) Cbolteae was significantly more prevalent (p = 002) among patients with AQP4-IgG+ NMOSD(n = 817 subjects) compared with seronegative patients (n = 322) and was absent amonghealthy stool samples C bolteae has a highly conserved glycerol uptake facilitator and relatedaquaporin protein (p59-71) that shares sequence homology with AQP4 peptide (p92-104)positioned within an immunodominant (AQP4 specific) T-cell epitope (p91-110) Presence ofC bolteae correlated with expression of inflammatory genes associated with both innate andadaptive immunities and particularly involved in plasma cell differentiation B cell chemotaxisand Th17 activation

ConclusionOur study described elevated levels of C bolteae associated with AQP4+ NMOSD amongIndian patients It is possible that this organism may be causally related to the immunopa-thogenesis of this disease in susceptible individuals

From the Nitte University (LP CM AD) Mangalore India and Ann Romney Center for Neurological Diseases (LMC TR HL VW SS TC) Brigham amp Womenrsquos HospitalHarvard Medical School Boston Massachusetts

Go to NeurologyorgNN for full disclosures Funding information is provided at the end of the article

The Article Processing Charge was funded by the authors

This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License 40 (CC BY-NC-ND) which permits downloadingand sharing the work provided it is properly cited The work cannot be changed in any way or used commercially without permission from the journal

Copyright copy 2020 The Author(s) Published by Wolters Kluwer Health Inc on behalf of the American Academy of Neurology 1

Neuromyelitis optica spectrum disorders1 (NMOSDs) area group of autoimmune inflammatory diseases that pre-dominantly target optic nerve and spinal cord A disease-specific serum autoantibody (aquaporin-4 (AQP4) IgG)targets AQP4 which is an important water channel proteinin the CNS2 The resulting cascade of events include ac-tivation of compliment produced locally by astrocytesincreased blood-brain permeability and a massive influx ofleukocytes (particularly neutrophils and eosinophils) anddeath of astrocytes oligodendrocytes and neurons3 Aninterleukin 6 (IL-6)ndashdependent B cell subpopulation playsan important role in NMOSD pathogenesis transforminginto AQP4-IgG synthesizing plasmablasts during an acuterelapse Hence NMOSD is primarily considered to be ahumorally mediated autoimmune disorder Evidence alsopoints to a pivotal role for T lymphocytes in NMOSDimmunopathogenesis45 AQP4-IgG belongs to the IgG1subclass which is T cell dependent for its activity Exper-imental models of NMOSD with passive transfer of AQP4-IgG requires a T cellndashmediated inflammation to be con-currently present Among T lymphocytes T-helper cell 17(Th17) cells and interleukin 17 (IL-17) secreting T cellsare increased in the sera of patients in acute relapse6 andNMOSD lesions have elevated levels of IL-17 suggesting aprominent role for Th17 cells7 Recently AQP4-specificT cells were identified in patients with NMOSD thatshowed a Th17 bias8

Globally demographic data suggest that NMOSD par-ticularly AQP4-IgGndashassociated NMOSD is likely tobe more prevalent among non-White populations9 Al-though genetic association suggests implication of humanleucocyte antigen Class 11 molecules10 very little is un-derstood about the environmental factors related to this dis-ease The intestinal microbiota is an important environmentalfactor that can play a role in the initiation and progression ofautoimmune disorders Few studies have looked at the asso-ciation of gut microbiome with NMOSD Cree et al11 found astrong association between AQP4-IgGndashassociated NMOSD andClostridium perfringens a Gram-positive commensal in the gut Thisstudy suggested that aquaporin-4ndashspecific T cells cross-react withan adenosine triphosphatendashbinding cassette (ABC) transporter ofC perfringens that shares sequence homology with AQP4812 An-other study of Chinese patients living in Asia showed an abundanceof Streptococcus associated with AQP4-IgGndashpositive NMOSD13

Our study investigated the gut microbiome among Indian patientswith NMOSD to explore the possibility that it may provide agreater understanding of the pathophysiology of disease among ourpatients

MethodsSeventeen AQP4-IgGndashpositive patients (AQP4+) 22 AQP4-IgGndashnegative patients (AQP4minus) and 36 healthy volunteersmatched for age and body mass index were included from ourregistry (table 1) All patients were in remission at the time ofsample collection had AQP4 IgG status confirmed by livecell-based assay and had given stool and blood samples OneAQP4-IgG+ patient and 6 seronegative patients were not ontreatment at the time of sample collection All others werereceiving immunosuppressants Patients and controls had notbeen on probiotics or antibiotics in the 3 months precedingstool collection Histories of bowl surgery inflammatorybowel disease and other autoimmune disorders were ex-cluded Vegetarian status among patients and healthy volun-teers was ascertained

Sample collectionStool samples were collected in containers provided to pa-tients They were delivered in person or by a relative on thesame day of collection over a median period of 3 hours (range1ndash5 hours) Stool samples were then immediately frozen atminus80degC until DNA extraction Peripheral blood mononuclearcells were isolated using ficoll hypaque gradient centrifugationand stored in liquid nitrogen until use

16S rRNA sequencing of the gut microbiotaDNA was extracted from stool using QIAampreg DNA Stoolextraction kit as per the manufacturerrsquos instructions DNAwas transported in dry ice from Nitte University to Brighamand Womenrsquos Hospital Boston USA for further analysisSamples were normalized and bacterial 16S ribosomal RNA(rRNA) gene was amplified using primers for amplificationof V4 region as per protocols described in the EarthMicrobiome Project14 Samples were sequenced by pairedend 250 base pair reads at the Harvard Medical SchoolBiopolymer facility using the Illumina MiSeq platformFastQC program (wwwbioinformaticsbabrahamacukprojectsfastqc) was used to evaluate sequence quality Weused Qualitative Insights into Microbial Ecology an opensource bioinformatics platform for downstream analysis15

Sequences were demultiplexed and denoised using DivisiveAmplicon Denoising Algorithm 2 Taxonomy was assignedusing reference database SILVA (arb-silvade) In additionwe used the EZ-Taxon (EzTaxonorg) to identify somespecies that could not be annotated by SILVA Alpha di-versity was calculated using Faithrsquos phylogenetic diversity(PD) observed operational taxonomic unit (OTU) andShannon diversity metrics Beta diversity was calculated

GlossaryASD = autism spectrum disorder ASV = amplicon sequence variant level KEGG = Kyoto encyclopedia of genes and genomeLDA = linear discriminant analysis LEfSe = Linear discriminatory analysis effect size NCBI = National Center forBiotechnology Information NMOSD = neuromyelitis optica spectrum disorder PD = phylogenetic diversity

2 Neurology Neuroimmunology amp Neuroinflammation | Volume 8 Number 1 | January 2021 NeurologyorgNN

using weighted and unweighted UniFrac distances16 Rela-tive abundance of individual species was calculated as therelative frequency in each samplesum of relative frequencyin all samples tested (n = 75) and expressed as percentage

We used linear discriminant analysis (LDA) effect size (LEfSe)on the Galaxy Browser huttenhowersphharvardedugalaxyto detect compositional changes in the microbiome in patientswith NMOSD and controls17 Accordingly a nonparametricfactorial Wilcoxon rank-sum test was used initially to detect

bacterial taxa with significant (α set at 001) differential abun-dance in patients with NMOSD vs healthy controls Thenestimate of the effect size of each differentially abundant featurewas calculated using LDA with a cutoff greater than 3

Gene expression studies and correlationwith microbiomeGene expression studies were performed at Nitte University Inbrief CD4 T cells were sorted from PBMC of patients withAQP4-IgG+ NMOSD (N = 12) and healthy controls (N = 12)using the Miltenyi Biotec positive selection kits Later mRNAextractionwas performed using RNeasymini kits (QIAGEN) andstored at minus80degC until further analysis All 24 samples were sub-jected to immune gene expression using a NanoString array(nCounter Gene expression code set human immunology kit)One patientrsquos sample failed to meet quality standards and wasremoved from the analysis Data were normalized using nSolverAnalysis software (nanostringcomproductsanalysis-softwarensolver) Significant differences between patient and controlsamples were analyzed by t tests and p-values were adjusted formultiple comparisons using Benjamini-Hochberg correctionCorrelation between microbiome abundance and immune geneexpressionwas determined using SpearmanRho correlation (IBMSPSS statistics 20) Kyoto encyclopedia of the genes and genomes(KEGGs) pathway analysis was performed using Enrichr webserver18 (amppharmmssmeduEnrichr) and the top canonicalpathways that had an activation score gt15minus15 were reported

Sequencehomology andphylogenetic placementSequence homology between AQP4 and other proteins wereaddressed using the Basic Local Alignment Search Tool(BLAST) from the National Center for Biotechnology In-formation (NCBI) and Clustal 21 multiple sequence align-ment tool from European Molecular Biology Laboratory-European Bioinformatics Institute (EMBL-EBI) Phylogeneticplacement of 16S rRNA sequences was completed usingPhylogenyfr(phylogenyfr)

Table 1 Demographic and clinical features of the studypopulation

NMOSDAQP4+ (17)

NMOSDAQP4-(22)

Control(36)

FM 143 1210 1422

Age

Mean 364 plusmn 86 353 plusmn 131 337 plusmn 83

Median 36 (25ndash56) 355(18ndash54) 34 (27ndash49)

BMI (mean plusmn SD) 22 plusmn 45 258 plusmn 63 234 plusmn 34

Diet

Nonvegetarian 15 20 21

Vegetarian 2 2 15

Treatment mdash

RTX 1 1

MMF 11 11

AZA 4 4

Untreated 1 6

Abbreviations AQP4 = aquaporin-4 AZA = azathioprine BMI = body massindex MMF = mycophenolate mofetil NMOSD = neuromyelitis opticaspectrum disorders RTX = rituximab

Figure 1 Beta diversity between AQP4+ and healthy controls

(A) 3D principal component analysis (PCoA) of weighted UniFrac distances of 16S rRNA genes showing significant beta diversity between AQP4+ patients(green) and healthy controls (red) (B) Results of pairwise PERMANOVA analysis showing a significant difference in beta diversity (p lt 0001 pairwisePERMANOVA test) between patients with AQP4-IgG+ NMOSD and healthy controls NMOSD = neuromyelitis optica spectrum disorder

NeurologyorgNN Neurology Neuroimmunology amp Neuroinflammation | Volume 8 Number 1 | January 2021 3

Figure 2 Differential bacterial composition at species level between patients and controls

(A) Taxa graph showing bacterial composition at thespecies levelmdashdifferential abundance (gt01 in anysample group) of microbes among patients withNMOSD and healthy controls (B) Cladogram based onLEfSe of bacterial communities showing differentiallyabundant microbes between patients with AQP4+NMOSD and controls and (C) showing differentialabundance between patients with AQP4- NMOSD andcontrols LEfSe = Linear discriminatory analysis effectsize NMOSD = neuromyelitis optica spectrumdisorder

4 Neurology Neuroimmunology amp Neuroinflammation | Volume 8 Number 1 | January 2021 NeurologyorgNN

Standard protocol approvals registrationsand patient consentsThis study was approved by the institutional ethics committeesat Nitte University (India) and Brigham andWomenrsquosHospital(USA) It was conducted in compliance with the Declaration ofHelsinki and national regulations A written informed consentwas obtained from all participants involved in the study

Data availabilityThe 16S rRNA sequencing data along with deidentifiedmetadata have been deposited at DRYAD (Pandit Lekha[2020] 16S rRNA sequences of gut microbiome and metadata Dryad Dataset doiorg105061dryadjsxksn075)

ResultsMicrobiota community structure differs inNMO patientsThere were 39 patients with NMOSD (17 were AQP4+) and36 healthy controls Details of the study population are out-lined in table 1 Measures of alpha and beta diversities werecalculated to determine the overall differences in the microbialcommunity among patients and controls Alpha diversity(microbial diversity within samples) was similar between allpatients with NMOSD and healthy controls including FaithPD and Shannon metric diversity The difference in beta di-versity (measurement of microbial community structure be-tween groups) was determined using unweighted andweightedUniFrac metric The 3-dimensional principal componentanalysis of weighted UniFrac distances of 16S rRNA genesshowed a shift in the microbiota community structure betweenAQP4+ patients and healthy controls (figure 1A) which wassignificant using the pairwise PERMANOVA analysis (adjustedp value = 0002) (figure 1B) Beta diversity also differed by diet(vegetariannonvegetarian) showing a trend for significance(pairwise PERMANOVA adjusted p value = 005)

Compositional differences in the gutmicrobiome in patients with NMOSDAt the phylum level Bacteroidetes Firmicutes and Proteobacteriawere dominant in both patients with NMOSD and healthycontrols (data not shown) with smaller contributions fromTenericutes and Actinobacteria A taxa graph (figure 2A) shows anoverview of the differential abundance of microbiota at the spe-cies level among patients with NMOSD and healthy controlsCircular cladograms (figure 2 B and C) reporting the LEfSeresults showed significant changes from the phylum to genuslevels between the 2 groups At the phylum level Proteobacteriawas significant in patients with AQP4+ NMOSD and Verruco-microbia in patients with AQP4-NMOSD At the genus levelClostridium Megamonas Streptococcus Enterobacteriaceae andBilophila were prominent in patients with AQP4+ NMOSDwhereas Bacteroides Megamonas Phascolarctobacterium andAkkermansia were prominent in patients with AQP4-NMOSD

At the species level there was a significant difference in microbialabundance between patients with AQP4+NMOSD and controls(table 2) and patients with AQP4-NMOSD and controls (table3)Microbial populations with an LDAgt3 and adjusted p value lt001 were considered significant Among patients with AQP4+NMOSD Clostridium bolteae (p = 000007) and Flavonifractorplautii (p = 000008) were the top hits whereas Megamonasfuniformis (p = 000003) and Clostridium ramosum (p = 00001)were the same for patients with AQP4-NMOSD Some organ-isms were significantly abundant among patients with both se-ropositive and seronegative NMOSD and includedM funiformisPhascolarctobacterium faecium F plautii and C ramosum

Lachnospiraceae was one of the significantly altered taxa Atthe amplicon sequence variant level (ASV) which is akin to thestrain level we found that Lachnospiraceae comprised 4 uniquesequence variants namely ASV_d5b22a367668019c66-d346e758f7a1ee ASV_f90fe5d03a1c66fbae34d7261fb134d9

Table 2 Differentially abundant microbes in patients with AQP4+ NMOSD compared with healthy controls

Taxa Group LDA p Value

K_BacteriaP_FirmicutesC_ClostridiaO_ClostridialesF_LachnospiraceaeG_Clostridium_g24S_Clostridium bolteae AQP4+ 42292 000007

K_BacteriaP_FirmicutesC_ClostridiaO_ClostridialesF_RuminococcaceaeG_PseudoflavonifractorS_FlavonifractorplautiiASV_d54e84e50addcb527e4290d59525524f

AQP4+ 33088 000008

K_BacteriaP_FirmicutesC_ErysipelotrichiO_ErysipelotrichalesF_ErysipelotrichaceaeG_Clostridium_g6S_Clostridium ramosumASV_55275c7900d36914bcebfaf9cdd89063

AQP4+ 30992 00002

K_BacteriaP_BacteroidetesC_BacteroidiaO_BacteroidalesF_PrevotellaceaeG_PrevotellaS_PAC001304_sASV_16e30e0be625f6adfcc7626984d8fa70

Control 45274 0003

K_BacteriaP_ActinobacteriaC_Actinobacteria_cO_BifidobacterialesF_BifidobacteriaceaeG_BifidobacteriumS_BifidobacteriumlongumASV_8517ed72f5e84cdc5d3bcebd03a7e2cb

Control 34730 0003

K_BacteriaP_FirmicutesC_ClostridiaO_ClostridialesF_RuminococcaceaeG_Ruminococcus_g2S_RuminococcusbromiiASV_0881804b168c0b7d1bf1b601b1513990

Control 33809 0004

Abbreviations AQP4 = aquaporin 4 ASV = amplicon sequence variant level LDA = linear discriminate analysis NMOSD = neuromyelitis optica spectrumdisorderLDA (linear discriminant analysis) gt 3 and p value lt001 was considered as significant

NeurologyorgNN Neurology Neuroimmunology amp Neuroinflammation | Volume 8 Number 1 | January 2021 5

ASV_aa2eeeb505ac76273e49ca4ac4c973c1 and ASV_5796684ced9efadf36da73862ae01df3 The maximum per-centage prevalence of Lachnoclostridium was 844 510and 274 respectively for patients with AQP4+ NMOSDpatients with seronegative NMOSD and healthy controlsrespectively (figure 3A) Using the EZ-taxon database weidentified ASV_d5b22a367668019c66d346e758f7a1ee as Cbolteae with a 100 homology to the type strain WAL1631T(ATCC (T)-BAA-613T CCUG (T)-46953T Total abun-dance of C bolteae in patients with AQP4+ NMOSD (406)was more than double (figure 3 B and C) than that in patientswith AQP4-NMOSD (204) Clostridium bolteae was absentamong control samples It was detected in 471 (817) ofpatients with AQP4+ NMOSD and 136 (322) patientswith AQP4-NMOSD (p 002) It is worth noting that thesingle untreated patient in the AQP4-IgG+ group and 2 of 6untreated patients in the seronegative group harbored Cbolteae The remaining 3 non annotated species were evenlydistributed among seropositive and negative patients but wassignificantly more abundant among patients (p lt 0001) thanhealthy controls Clostridium bolteae showed phylogeneticdissimilarity from the other Lachnoclostridium species isolatedin this study (figure e-1 linkslwwcomNXIA334)

C bolteae has partial protein homologyto AQP4Sequence homology analysis (figure 4 A and B) showed thatC bolteae peptide 59ndash71 (NCBI protein referencemdashTaxidID208479) aligned with AQP4 peptide (p) 92ndash104

Topology (uniportorg) shows that AQP4 peptide sequence92ndash104 is predominantly cytoplasmic (figure e-2 linkslwwcomNXIA335) and likely to be highly reactive to AQP4specific T cells18 We identified a 62 homology (62identity 76 positive and 0 gap) in the 13 aminoacid se-quence 59ndash71 that falls within the highly conserveddomainmdashglycerol uptake facilitator and related aquaporins(GlpF) It belongs to the major intrinsic proteins (MIP) re-sponsible for carbohydrate transport and metabolism in themicrobial cell

Gene expression studies in peripheralCD4+ lymphocytesThe NanoString Immunology Panel was used to measure theexpression of 568 immune-related genes from peripheral bloodderived CD4+ T cells from a subset of patients with AQP4+NMOSD (n = 11) and healthy controls (n = 12) BecauseC bolteae was significantly elevated in AQP4-IgG+ patientssamples were selected based on the presence (n = 5) or absenceof the same (n = 6) Demographic features of both groups werecomparable (table e-1 linkslwwcomNXIA337) The top listof genes upregulated (figure e-3 linkslwwcomNXIA336) in-cluded those related to both innate and adaptive immunities Thepresence of C bolteae correlated positively (Rho ge 05 p lt 005)with transcriptomes of CD4+T cells implicated in inflammatoryresponse particularly CD70 IFI35 (interferon induced protein35) MAPK11 (mitogen activated protein kinase 11) TAP2(transporter 2) CCR10 (chemokine receptor 10) KLRAP1(killer cell lectin like receptor A1) PML (promyelocyte

Table 3 Differentially abundant microbes in patients with AQP4- NMOSD compared with healthy controls

Taxa Group LDA p Value

K_BacteriaP_FirmicutesC_NegativicutesO_SelenomonadalesF_SelenomonadaceaeG_MegamonasS_MegamonasfuniformisASV_43303b616239cfb4ac93969fa8511f38

AQP4-ve 3681 000003

K_BacteriaP_FirmicutesC_ErysipelotrichiO_ErysipelotrichalesF_ErysipelotrichaceaeG_Clostridium_g6S_ClostridiumramosumASV_55275c7900d36914bcebfaf9cdd89063

AQP4-ve 3093 00001

K_BacteriaP_FirmicutesC_NegativicutesO_AcidaminococcalesF_AcidaminococcaceaeG_PhascolarctobacteriumS_PhascolarctobacteriumfaeciumASV_26d5c4614643a0b9609257f324bbcaae

AQP4-ve 302 0002

K_BacteriaP_FirmicutesC_ClostridiaO_ClostridialesF_RuminococcaceaeG_PseudoflavonifractorS_FlavonifractorplautiiASV_d54e84e50addcb527e4290d59525524f

AQP4-ve 3178 0003

K_BacteriaP_FirmicutesC_ErysipelotrichiO_ErysipelotrichalesF_ErysipelotrichaceaeG_HoldemaniaS_HoldemaniamassiliensisASV_d1dd9f09e5374278dbe38fc473ae9f80

AQP4-ve 3101 0007

K_BacteriaP_BacteroidetesC_BacteroidiaO_BacteroidalesF_BacteroidaceaeG_Bacteroides AQP4-ve 4742 0009

K_BacteriaP_VerrucomicrobiaC_VerrucomicrobiaeO_VerrucomicrobialesF_AkkermansiaceaeG_AkkermansiaS_AkkermansiamuciniphilaASV_438fb020cf251f2c2f4e89552e4a78ff

AQP4-ve 3839 0011

K_BacteriaP_FirmicutesC_ClostridiaO_ClostridialesF_LachnospiraceaeG_RoseburiaS_Roseburia_unclassifiedASV_b8bff7baca856f5baba321a03beb073c

Control 3493 0001

K_BacteriaP_FirmicutesC_ClostridiaO_ClostridialesF_LachnospiraceaeG_LachnospiraS_Lachnospira_unclassifiedASV_bfec3f48be151947542d749f589a9792

Control 3254 0002

K_BacteriaP_BacteroidetesC_BacteroidiaO_BacteroidalesF_PrevotellaceaeG_PrevotellaS_PrevotellacopriASV_73430bc839451a90e446092bddb91416

Control 4678 0011

Abbreviations AQP4 = aquaporin- 4 ASV = amplicon sequence variant level LDA = linear discriminate analysis NMOSD = neuromyelitis optica spectrumdisorder

6 Neurology Neuroimmunology amp Neuroinflammation | Volume 8 Number 1 | January 2021 NeurologyorgNN

leukemia) and IKBE (NF-kappa-B inhibitor epsilon gene)(figure5A table e-2 linkslwwcomNXIA337) There was in additiona significant difference in gene upregulation among pa-tients with AQP4+ NMOSD who harbored F plautii(KLRAP1 and PML) P faecium (MAPK11) and Bacteroidesovatus (MAPK11) Conversely Prevotella Bifidobacteriumand Ruminococcus showed a negative correlation for the samegenes among patients and was similar to results in healthycontrols The KEGG pathway analysis (Enrichr)19 showedupregulation of pathways relevant to immunopathogenesisof AQP4-IgGndashassociated NMOSD (figure 5B) These in-cluded TH1 Th2 and Th17 differentiations TLR1 TNF-alpha and NFKB signaling pathways Pathways projected to

be upregulated in this study also shared similarity with otherB cell mediated disorders such as inflammatory bowel dis-ease and rheumatoid arthritis (RA)

DiscussionWe have for the first time studied gut microbiome associa-tions in Indian patients with NMOSD using high through-put sequencing of 16S rRNA There were significantalterations in beta diversity in gut microbiota among patientswith NMOSD when compared with healthy controls andparticularly in the AQP4+ NMOSD cohort The microbialcomposition at the genus level showed over expression ofLachnoclostridium species (Class Clostridia and familyLachnospiraceae) in patients with NMOSD as opposed tohealthy controls Among them C bolteae a gram positivespore-forming bacterium was detected exclusively in pa-tients but not in healthy controls There was also a signifi-cant difference in the relative prevalence (p = 002) whenpatients were stratified based on the presenceabsence ofAQP4-IgG Because most patients with NMOSD were ontreatment with immunosuppressants hypothetically it ispossible that treatment favored microbial overgrowth inpatients However the single untreated patient in the AQP4-IgG+ and 2 others in the seronegative group also harboredC bolteae

Profiling of peripheral CD4+ T cell transcriptomes showed apositive correlation with this species for most upregulatedgenes in this study and particularly relevant to gut dysbiosisand NMOSD pathogenesis The latter included CD70 atumor necrosis factor family ligand that binds to its receptorCD27 expressed on memory B cells and promotes plasmacell differentiation and immunoglobulin secretion20 Gutmicrobiota are known to activate the differentiation oflamina propria cells particularly CD70 into Th1721 Anotherupregulated gene in our study was MAPK11 MAPK sig-naling pathway activation is known to be associated with gutdysbiosis22 It is notable that CCR10 plays a role in theinduction of mucosal humoral immunity When stimulatedby toll-like receptor 2 (TLR2) it is expressed in circulatingB cells resulting in increased chemotaxis and B cell homingto the gastrointestinal tract23 Other genes linked to innateimmunity that were over expressed included PML KLRAP1and IFI35 IKBE gene an NF-kB regulator involved in IL-6gene transcription and TAP2 gene have been previouslylinked with susceptibility to RA24 In summary pathwaysupregulating B cell activation plasma cell differentiationB cell chemotaxis and Th17 activation were implicatedFurther support came in the form of KEGG pathway analysis(Enrichr) that projected upregulation of pathways relevantto immunopathogenesis of AQP4-IgG-associated NMOSDThese included Th1 Th2 and Th17 differentiation TLRTNF-alpha IL17 and NFKB signaling pathways Thesepathways are also common to other B cellndashmediated disor-ders such as inflammatory bowel disease and RA (figure 5B)

Figure 3 Distribution of Lachnoclostridium species amongpatients and controls

Lachnoclostridium distribution among (A) patients and control (B) distribu-tion of Lachnoclostridium species and (C) distribution of Clostridum bolteaed5b22a367668019c66d346e758f7a1ee among patients and controls

NeurologyorgNN Neurology Neuroimmunology amp Neuroinflammation | Volume 8 Number 1 | January 2021 7

In our study Lachoclostridium species particularly C bolteaewas the most prominent microbe associated with gut dys-biosis among patients with AQP4+ NMOSD Clostridiumbolteae has gained attention in recent years because of itsclose association with autism spectrum disorders (ASD)The capsular polysaccharide of C bolteae comprising di-saccharide repeating blocks of mannose and rhamnose unitshas been identified to be immunogenic in animal models25

In children with ASD C bolteae association is known tocause the upregulation of inflammatory cytokines (particu-larly IL-6 and IL-17)2627 A study of gut microbiome inchildren with food allergy (an autoimmune mediated in-flammatory state) has shown increased C bolteae whencompared with nonallergic siblings and healthy controls28

There was abundance of other microbiota in patients withNMOSD which have been previously implicated in diseasestates which could have additionally contributed to gutdysbiosis among our patients These include Flavonifractorwhich was recently found over expressed in gut dysbiosisassociated with pemphigous vulgarismdashan autoimmunedisorder affecting the skin29 Flavonifractor and Lachno-clostrium species (unidentified) have been associated withgut dysbiosis in ASD among Chinese children26 There wasa reduction in the abundance of Prevotella species amongpatients which is similar to alterations in patients withMS30 Prevotella histicola can ameliorate disease severity inexperimental autoimmune encephalomyelitis the animalmodel for MS31 However Prevotella copri is elevated innew onset RA patients and can drive inflammation whentransferred to mice32 Thus further study on species-specific effects of Prevotella is warranted in NMOSD Pre-votella is the common species among vegetarians living inIndia and was most prominent in our control sample33

Bifidobacterium species was reduced in patients and this hasbeen previously reported with another autoimmune dis-order namely Crohnrsquos disease34 Clostridium bolteae wasalso increased in a small number of seronegative patientswith NMOSD A previous study has shown that C per-fringens was not only associated with patients with AQP4+NMOSD but was seen in a small number of MS patientsalso11 It is possible that proinflammatory Clostridia speciesmay be causally linked with more than one autoimmunedisease

The results of our study suggest that C bolteae plays a centralin the immunopathogenesis of patients with AQP4+NMOSD among our cohort of Indian patients and we haveidentified 2 potential mechanisms First high levels of Cbolteae may contribute to NMOSD by increasing Th17 andother inflammatory immune-mediated responses It is wellknown that Clostridium species which are prominent ane-robes in the human intestinal tract can influence the balancebetween Th17 and regulatory T cells3536

Second the sequence similarity between C bolteae peptide59-71 and AQP4 peptide 92-104 may have implications indisease pathogenesis Several extracellular membranousand cytoplasmic AQP4 epitope determinants have beenidentified (figure e-2 linkslwwcomNXIA335)818 Mat-suya et al18 have shown that AQP4-specific T cells exhibitsignificant reactivity to 2 intracellular AQP4 epitopes one ofwhich was AQP4p91-110 that overlaps with peptide se-quences identified in our study (the other wasp11-40) Inexperimental settings AQP4-specific T cells which wereCD4+ and MHC I I restricted showed a similar response tothis epitope in C57BL6 mice and in SJLJ mice37 In-terestingly in a separate study B cell antigenic linear

Figure 4 Determination of sequence homology between AQP4 peptides and C bolteae

Sequence homology between AQP4 P92-104 andC bolteae P59-71 peptides determined using (A) abasic local alignment tool (National Center forBiotechnology Information) (B) CLUSTAL 21(multiple sequence alignment tool fromEuropeanMolecular Biology Laboratory-European Bio-informatics Institute [EMBL-EBI])

8 Neurology Neuroimmunology amp Neuroinflammation | Volume 8 Number 1 | January 2021 NeurologyorgNN

Figure 5 Correlation between microbiota abundance and immune gene expression

(A) Heat map showing correlation (Spearman Rho) be-tween microbiota abundance and immune gene expres-sion in patients with AQP4+ NMOSD (n-11) and healthycontrols (n = 12) (B) KEGG pathway analysis (Enrichr)Top list of pathways upregulated by the set of genesidentified in the nanostring analysis were sorted by acombined score (log of p value obtained by the Fisherexact test multiplied by a Z score of the deviation fromexpected rank) Input genes are the rows and cells in thematrix indicate whether a gene is associated with a termKEGG = Kyoto encyclopedia of genes and genomeNMOSD = neuromyelitis optica spectrum disorder

NeurologyorgNN Neurology Neuroimmunology amp Neuroinflammation | Volume 8 Number 1 | January 2021 9

epitopes of AQP4 protein were found to be same as theT cell epitopes mentioned above38 This response to AQP4may be due to immunologic memory acquired through pastinfection with pathogens that share molecular similarity withAQP439 A potential link between infections and NMOSDpathogenesis has been studied before An E colindashderivedaquaporin-Z has been implicated in NMOSD in previousstudies40 In a more recent study an immunodominantAQP4 T cell epitope was identified (p63-76) which showed90 homology with p217-216 within a conserved ABCtransporter protein from strains of C perfringens5 expressedabundantly in patients with NMOSD11 In our study an-other member of the clostridial class namely C bolteae p59-71 showed partial sequence homology with a recognizedAQP4 specific T cell epitope within AQP4 p91-110 Thealigned protein sequence corresponded to a multispeciesaquaporin family protein a member of the major intrinsicprotein (MIP) superfamily ubiquitously present in eukary-otes bacteria and archaea It is therefore possible that mo-lecular mimicry the mechanism by which exogenous agentsincluding plant bacterial and viral proteins may triggerimmune responses against self or nonself antigens contrib-utes to the autoimmune response against AQP4 in NMOSD

There are several limitations to our study including thesmall sample size and the lack of sufficient number of un-treated patients available for the analysis Furthermoreevidence for a direct role for C bolteae in NMOSD patho-genesis needs to be established through invitro studieswhich include the localization of the immunodominantpeptide within the intracellular T cellndashspecific AQP4 epi-tope that we identified historically Animal studies that in-volve colonization of germ-free mice with fecal samplesfrom patients with NMOSD and individual bacterial speciessuch as C bolteae may help to further strengthen the asso-ciation between the gut microbiome and NMOSD

AcknowledgmentL Pandit was a Fulbright Nehru scholar at Harvard MedicalSchool during part of the study and was partially supported bythe United StatesndashIndia Educational Foundation (USIEF)

Study fundingNo targeted funding reported

DisclosureL Pandit L Cox C Malli A DrsquoCunha T Rooney HLokhande V Willocq and S Saxena report no conflicts ofinterest T Chitnis reports consulting fees from Biogen IdecNovartis Sanofi Bayer Celgene Genentech Grants fromNovartis Octane Bioscience EMD Serono Verily Life Sci-ences all outside the submitted work Go to NeurologyorgNN for full disclosures

Publication historyReceived by Neurology Neuroimmunology amp NeuroinflammationMay 18 2020 Accepted in final form September 16 2020

References1 Wingerchuk DM Banwell B Bennett JL et al International consensus diagnostic

criteria for neuromyelitis optica spectrum disorders Neurology 201585177ndash1892 Lennon VA Wingerchuk DM Kryzer TJ et al A serum autoantibody marker of Neu-

romyelitis optica distinction from multiplesclerosis Lancet 20043642106ndash21123 Jassiak ZM Lyszczarz AK Michalak S Kozubski W The immunology of neuro-

myelitis opticamdashcurrent knowledge clinical implications controversies and futureperspectives Int J Mol Sci 201617273

4 Papadopoulos MC Verkman AS Aquaporin 4 and neuromyelitis optica LancetNeurol 201211535ndash544

5 Bradl M Misu T Takahashi T et al Neuromyelitis optica pathogenicity of patientimmunoglobulin in vivo Ann Neurol 200966630ndash643

6 Wang HH Dai YQ Qiu W et al Interleukin-17-secretingTcellsinneuromyelitisopti-caandmultiplesclerosisduringrelapse J Clin Neurosci 2011181313ndash1317

7 Uzawa A Mori M Arai K et al Cytokine and chemokine profiles in neuromyelitisoptica significance of interleukin-6 Mult Scler 2010161443ndash1452

8 Varrin- Doyer M Spencer CM Topphoff SU et al Aquaporin 4-specific T cells inneuromyelitis optica exhibit a Th17 bias and recognize Clostridium ABC transporterAnn Neurol 20127253ndash64

9 Pandit L Asgari N Apiwattanakul M et al Demographic and clinical features ofneuromyelitis optica a review Mult Scler 201521845ndash853

10 Estrada K Whelan C Zhao F A whole-genome sequence study identifies genetic riskfactors for neuromyelitis optica Nat Comm 201891929

Appendix Authors

Name Location Contribution

LekhaPanditMD DMPhD

Nitte UniversityMangalore India

Conception design of thestudy acquisition analysis ofdata and drafting asignificant portion of themanuscript and figures

LauraMCox PhD

Ann Romney Center forNeurological DiseasesBrigham amp WomenrsquosHospital Harvard MedicalSchool

Conception design of thestudy acquisition analysis ofdata and drafting asignificant portion of themanuscript and figures

ChaithraMalli PhD

Nitte UniversityMangalore India

Acquisition analysis of thedata and draftinga significant portion of themanuscript and figures

AnithaDrsquoCunhaPhD

Nitte UniversityMangalore India

Acquisition analysis of thedata and draftinga significantportion of the figures

TimothyRooneyMD PhD

Ann Romney Center forNeurological DiseasesBrigham amp WomenrsquosHospital Harvard MedicalSchool

Acquisition and analysis ofthe data

HrishikeshLokhandeMSc

Ann Romney Center forNeurological DiseasesBrigham amp WomenrsquosHospital Harvard MedicalSchool

Acquisition and analysis ofthe data

ValerieWillocqBSc

Ann Romney Center forNeurological DiseasesBrigham amp WomenrsquosHospital Harvard MedicalSchool

Acquisition and analysis ofthe data

ShrishtiSaxenaMSc

Ann Romney Center forNeurological DiseasesBrigham amp WomenrsquosHospital Harvard MedicalSchool

Acquisition and analysis ofthe data

TanujaChitnisMD

Ann Romney Center forNeurological DiseasesBrigham amp WomenrsquosHospital Harvard MedicalSchool

Conception design of thestudy and draftinga significant portion of themanuscript or figures

10 Neurology Neuroimmunology amp Neuroinflammation | Volume 8 Number 1 | January 2021 NeurologyorgNN

11 Cree BA Spencer CM Varrin-Doyer M Baranzini SE Zamvil SS Gut MicrobiomeAnalysis in neuromyelitis optica reveals overabundance of Clostridium perfringensAnn Neurol 201680443ndash447

12 Zamvill SS Spencer CM Baranzini S Cree BA The gut microbiome in neuromyelitisoptica Neurotherapeutics 20181592ndash101

13 Gong J Qiu W Zeng Q et al Lack of short-chain fatty acids and overgrowth ofopportunistic pathogens define dysbiosis of neuromyelitis optica spectrum disordersa Chinese pilotstudy Mult Scler J 2018251316ndash1325

14 Caporaso J Lauber C Walters W et al Ultra-high-throughput microbial communityanalysis on the Illumina HiSeq and MiSeq platforms ISMEJ 201261621ndash1624

15 Bolven E Rideout JR Dilon MR et al QIIME 2 reproducible interactive scalableand extensible microbiome data science PeerJ Preprints 6e27295v2 107287peerjpreprints27295v2

16 Lozupone C Knight R UniFrac a new phylogenetic method for comparing microbialcommunities App Env Microbiol 2005718228ndash8235

17 Segata N Izard J Waldron L et al Metagenomic biomarker discovery and explana-tion Genome Biol 201112R60

18 Matsuya N Komori M Nomura K et al Increased T-cell immunity againstaquaporin-4 and proteolipid protein in neuromyelitis optica Int Immunol 201123565ndash573

19 Chen EYTan CMKou Y et al Enrichr interactive and collaborative HTML5 genelist enrichment analysis tool BMC Sci Rep 2016633566

20 Shaw J Wang YH Ito T Arima K Liu YJ Plasmacytoid dendritic cells regulate B-cellgrowth and differentiation via CD70 Blood 20101153051ndash3057

21 Atarashi K Nishimura J Shima T et al ATP drives lamina propria T(H)17 celldifferentiation Nature 2008455808ndash812

22 Smith PK Masilamani M Li XM Sampson HA The false alarm hypothesis foodallergy is associated with high dietary advanced glycation end-products and progly-cating dietary sugars that mimic alarmins J Allergy Clin Immunol 201739429ndash437

23 Liang Y Hasturk H Elliot J et al Toll-like receptor 2 induces mucosal homing receptorexpression and IgA production by human B cells Clin Immunol 201113833ndash40

24 Myouzen K Kochi Y Okada Y et al Functional variants in NFKBIE and RTKN2involved in activation of the NF-κB pathway are associated with rheumatoid arthritisin Japanese PLoS Genet 20128e1002949

25 Fattorusso A Di Genova L DellrsquoIsola GB Mencaroni E Esposito S Autism spectrumdisorders and the gut microbiota Nutrients 201911E521

26 Ma B Liang J Dai M et al Altered gut microbiotain Chinese children with autismspectrum disorders Front Cell Infect Microbiol 2019940

27 Kourosh A Luna RA Balderas M et al Fecal microbiome signatures are different infood-allergic children compared to siblings and healthy children Pediatr AllergyImmunol 201829545ndash554

28 Peguegnat B Monteiro MA Carbohydrate scaffolds for the study of the autismassociated bacterium Clostridium bolteae Curr Med Chem 2019266341ndash6348

29 SenHuang S Mao J Zhou L et al The imbalance of gut microbiota and its correlationwithplasma inflammatory cytokines in pemphigus vulgaris patients Scand J Immunol201918e12799

30 Jangi S Gandhi R Cox LM et al Alterations of the human gut microbiome inmultiplesclerosis Nat Commun 2016712015

31 Mangalam A Shahi SK Luckey D et al Human gut-derived commensal bacteria sup-press CNS inflammatory and demyelinating disease Cell Rep 2017201269ndash1277

32 Scher JU Sczesnak A Longman RS et al Expansion of intestinal Prevotella copricorrelates with enhanced susceptibility to arthritis Elife 20132e01202

33 Dhakan DB Maji A Sharma AK et al The unique composition of Indian gutmicrobiomegene catalogue and associated fecal metabolome deciphered using multi-omics approaches GigaScience 20198giz004

34 Wang W Chen L Zhou R et al Increased Proportions of Bifidobacterium and theLactobacillus Group and loss of Butyrate-Producing Bacteria in Inflammatory BowelDisease J Clin Microbiol 201452398ndash406

35 Atarashi K Tanoue T Oshima K et al Treg induction by a rationally selected mixtureof Clostridia strains from the humanmicrobiota Nature 2013500232ndash236

36 Atarashi K Tanoue T Ando M et al Th17 cell induction by adhesion of microbes tointestinal epithelial cells Cell 2015163367ndash380

37 Nelson PA Khodadoust M Prodhomme T et al Immunodominant T cell deter-minats of aquaporin-4 the autoantigen associated with neuromyelitis optica PLoSOne 20105e1505

38 Kampylafka EI Routsias JG Alexopoulos H et al Fine specificities of antibodies againstAQP4 epitope mapping reveals intracellular epitopes J Autoimmun 201136221

39 Benoist C Mathis D Autoimmunity provoked by infection how good is the case forT cellepitope mimicry Nat Immunol 20012797

40 Ren ZWang Y Duan T et al Cross-immunoreactivity between bacterial aquaporin-Zand human aquaporin-4 potential relevance to neuromyelitis optica J Immunol 20121894602ndash4611

NeurologyorgNN Neurology Neuroimmunology amp Neuroinflammation | Volume 8 Number 1 | January 2021 11

DOI 101212NXI000000000000090720218 Neurol Neuroimmunol Neuroinflamm

Lekha Pandit Laura M Cox Chaithra Malli et al shares sequence similarity with AQP4

is elevated in neuromyelitis optica spectrum disorder in India andClostridium bolteae

This information is current as of November 4 2020

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is an official journal of the American Academy of NeurologyNeurol Neuroimmunol Neuroinflamm