Document [original]

CD40 Stimulation Activates ‘Post-Activated’ B Cells which are

Hyporesponsive to B Cell Receptor and Toll-like Receptor 9

Stimulation in Autoimmunity

vorgelegt von

M. Sc.

Sarah Yasmin Weißenberg

an der Fakultät III – Prozesswissenschaften

der Technischen Universität Berlin

zur Erlangung des akademischen Grades

Doctor rerum naturalium

- Dr. rer. nat. -

genehmigte Dissertation

Promotionsausschuss:

Vorsitzender: Prof. Dr. Juri Rappsilber

Gutachter: Prof. Dr. Roland Lauster

Gutachter: Prof. Dr. Thomas Dörner

Tag der wissenschaftlichen Aussprache: 20.11.2020

Berlin 2021

Content

Abbreviations .......................................................................................................................................... 9

1 Zusammenfassung ....................................................................................................................... 15

2 Summary ...................................................................................................................................... 19

3 Introduction ................................................................................................................................... 21

3.1 The Immune System ............................................................................................................. 21

3.2 The B Cell Lineage – Development, Subsets and Tolerance Checkpoints .......................... 22

3.2.1 The Course of T Cell-Dependent and T Cell-Independent B Cell Responses ............. 22

3.2.2 Early Ontogeny of B-1 and B-2 B Cells ........................................................................ 22

3.2.3 B-1 B Cells Mainly Undergo T Cell-Independent B Cell Responses ............................ 23

3.2.4 B-2 B Cells Subdivide into MZ and FO B Cells in the Spleen ...................................... 23

3.2.5 MZ B Cells Screen the Blood for Antigens ................................................................... 24

3.2.6 FO B Cells Undergo TD Activation and Raise Antigen-Specific Immune Responses . 24

3.2.7 The Germinal Center Response of B Cells after TD Activation .................................... 25

3.2.8 Memory B and Long-Lived Plasma Cells Provide Long-Term Protection in Case of a

Secondary Immune Reaction ....................................................................................................... 26

3.3 The B Cell Receptor Signaling Pathway During Development, Tolerance Induction and

Receptor Crosstalk ........................................................................................................................... 27

3.3.1 The BCR and Immunoglobulin Subclasses .................................................................. 27

3.3.2 Proximal Regulation of the BCR Signaling Pathway .................................................... 28

3.3.3 BCR Signaling Strength During B Cell Development and Tolerance Induction ........... 28

3.3.4 BCR Crosstalk with TLR9 and CD40 in B Cells ........................................................... 29

3.4 Autoimmunity ........................................................................................................................ 30

3.4.1 Autoimmune Diseases (SLE, RA and pSS) .................................................................. 30

3.4.2 B cell Abnormalities in SLE, RA and pSS ..................................................................... 31

3.4.3 Mutations in BCR Signaling and Functional Consequences ........................................ 31

3.4.4 Altered BCR Signaling in Autoimmunity ....................................................................... 32

3.4.5 B Cell Directed Therapies in Autoimmune Diseases .................................................... 33

4 Hypothesis and Aim ...................................................................................................................... 35

5 Donors, Materials and Methods .................................................................................................... 37

5.1 Blood and Tissue Donors ..................................................................................................... 37

5.2 Materials ............................................................................................................................... 38

5.3 Quality Control of Flow Cytometry Staining ......................................................................... 42

5.4 Siglec-1 Expression as Surrogate Marker for In Vivo IFNα Activity ..................................... 43

5.5 Intracellular B Cell Phenotyping for BCR Downstream Kinase Expression and

Phosphorylation at Baseline ............................................................................................................. 43

5.6 Analysis of pERK1/2(T202/Y204) Expression as a Surrogate Marker for B Cell Anergy ........ 44

5.7 Isolation of Peripheral Blood Mononuclear Cells (PBMCs) from Human Blood Samples ... 45

5.8 Isolation of Mononuclear Cells (MNCs) from Human Spleen, Tonsil and Parotid ............... 45

5.9 Analysis of Ex Vivo PTP and PSP Activities within CD19+ B Cell and CD3+ T Cells .......... 46

5.10 Analysis of CD22/SHP-1 Co-Localization in CD19+ B Cells ................................................ 46

5.11 Functional Analysis of BCR Associated Signaling Kinases Upon Anti-IgG/IgM Stimulation 47

5.12 Anti-IgG/IgM Induced Syk(Y352) Phosphorylation Upon In Vitro Pre-Incubation with Cytokines

or CpG 47

5.13 Chronic BCR and TLR9 In Vitro Stimulation ........................................................................ 47

5.14 CD40 In Vitro Co-Stimulation Strategies .............................................................................. 48

5.14.1 B Cell Co-Stimulation by Anti-CD40 Coating ............................................................... 48

5.14.2 Co-Culturing System Using hCD40L Expressing Mouse Fibroblast Cell Line ............. 48

5.14.3 Co-Stimulation Using a CD40L Cross-Linking Kit ........................................................ 49

5.15 Analysis of CD19+ B Cell In Vitro Proliferation Using CFSE Staining .................................. 49

5.16 In Vitro Differentiation of B Cells into Antibody Secreting Cells (ASCs) .............................. 49

5.17 Cytokine Quantification in Human Sera Using BioPlex Technology .................................... 50

5.18 Meta-Analysis of Differentially Methylated CpGs in SLE, RA and pSS ............................... 51

5.19 Differential Gene Expression Analysis of RNA-Sequencing Data ....................................... 51

5.19.1 Analysis of Differential Phosphatase Expression from Publicly Available CD20+, CD4+

and CD8+ SLE Cells and CD19+ Multiple Sclerosis (MS) RNA-Sequencing Data Sets .............. 51

5.19.2 Analysis of Differential Phosphatase Expression from CD19+ SLE Cells After CD40L/IL-

4R Stimulation .............................................................................................................................. 52

5.20 Data Analysis and Statistics ................................................................................................. 52

6 Results .......................................................................................................................................... 55

6.1 Increased PTP and PSP Activities in SLE and Increased Co-Localization of CD22 with SHP-

1 in SLE, RA and pSS CD19+ B Cells .............................................................................................. 55

6.2 Comparable Syk, Btk, PLCγ2 and Akt Baseline Expression and Phosphorylation Between

SLE, pSS, RA and HDs in CD27- B Cells and CD27+ Memory B Cells ........................................... 56

6.3 Reduced Tyrosine Phosphorylation of Syk(Y352) and Btk(Y223) Upon Anti-IgG/IgM Stimulation

in B Cells From SLE, RA and pSS Patients ..................................................................................... 59

6.4 Anti-IgG/IgM Induced Serine Phosphorylation of Akt(S473) is Increased in SLE and

Comparable to HDs in RA and pSS ................................................................................................. 61

6.5 Reduced Anti-IgG/IgM Induced Syk(Y352) Phosphorylation in CD27+ Memory B Cells from ITP

Spleens ............................................................................................................................................. 63

6.6 Comparable ERK1/2(T202/Y204) Baseline Phosphorylation in B Cells from HDs, SLE and RA

Patients ............................................................................................................................................. 64

6.7 Reduced Anti-IgG/IgM Induced pSyk(Y352) in SLE, RA and pSS CD27+ Memory B Cells Does

Not Correlate with Siglec-1 or Cytokine Expression ......................................................................... 66

6.8 Common CpG Methylation Patterns Among SLE, RA, pSS and HD CD19+ B Cells ........... 67

6.9 Chronic Anti-IgG/IgM Stimulation Prevents Syk(Y352) Phosphorylation Upon IgG/IgM

Rechallange ...................................................................................................................................... 68

6.10 CD40 Co-Stimulation Increases Anti-IgG/IgM-Induced Syk(Y352) Phosphorylation ............. 70

6.10.1 Appropriate Activation of CD40 Using the CD40L Cross-Linking Kit ........................... 71

6.10.2 Increased Anti-IgG/IgM Induced Syk(Y352) Phosphorylation Upon CD40-Co-Stimulation

in SLE, RA, pSS and HD B cells .................................................................................................. 75

6.11 Reduced TLR9 Induced Differentiation into CD27+CD38+ ASCs of SLE, RA and pSS B Cells

6.12 Restored Proliferation of SLE, RA and pSS B Cells Upon Co-Stimulation with CD40L....... 80

6.13 CD40/IL-4R Co-Stimulation Decreases PTP Expression ..................................................... 82

6.14 Summary of Results ............................................................................................................. 83

7 Discussion .................................................................................................................................... 85

7.1 Reduced BCR Responsiveness is a Commonality Among Peripheral as Well as Tissue

Resident B Cells from Patients with Autoimmune Diseases ............................................................ 85

7.2 Impaired Responsiveness of SLE, RA and pSS Peripheral B Cells to BCR and TLR9 Stimuli

is Connected by Syk ......................................................................................................................... 86

7.3 Reduced BCR Responsiveness is Likely Caused by an Increase in Negative Feedback

Regulation Mediated by Protein Phosphatases ............................................................................... 86

7.4 B Cells from Autoimmune Disease Patients Remain in a ‘Post-Activation’ State Common to

Anergy 87

7.5 Lymphocyte Hyporesponsiveness in Autoimmune Diseases is not Restricted to B Cells ... 89

7.6 Reduced BCR Signaling Can Play a Pathogenic Role in the Development, Maintenance and

Progression of Autoimmunity ........................................................................................................... 89

7.7 CD40 Co-Stimulation is a Critical Activator of ‘Post-Activated B Cells in SLE, RA and pSS ..

.............................................................................................................................................. 90

7.8 Implications for Therapeutic Approaches ............................................................................. 90

7.9 Outlook ................................................................................................................................. 91

8 Conclusion ..................................................................................................................................... 96

9 Literature ....................................................................................................................................... 99

10 Tables and Figures.................................................................................................................. 113

10.1 Table of Main Figures ........................................................................................................ 113

10.2 Table of Supplementary Figures ........................................................................................ 114

10.3 Table of Tables ................................................................................................................... 114

10.4 Table of Supplementary Tables ......................................................................................... 114

11 Appendix ................................................................................................................................. 115

12 Publications, Presentations and Poster .................................................................................. 127

13 Acknowledgements ................................................................................................................. 129

14 Eidesstattliche Erklärung ......................................................................................................... 131

Abbreviations

(ds)DNA

(Double stranded) deoxyribonucleic acid

(ds)RNA

(Double stranded) ribonucleic acid

(p)DC

(Peripheral) dendritic cell

Area

Abata

Abatacept

ACPA

Antibodies against citrullinated antigens

ACR

American College of Rheumatology

AECG

American-European Consensus Group

Alexa flour

AhR

Aryl hydrocarbon receptor

AID

Autoimmune disease

Akt(1)

Protein kinase B

ANA

Anti-nuclear antibodies

ANOVA

Analysis of variance

APC

Antigen presenting cell

APC

Allophycocyanin

applic.

Application

APRIL

A proliferation-inducing ligand

ASC

Antibody secreting cell

Aza

Azathioprine

BAFF

B cell-activating factor

BANK1

B cell scaffold protein with ankyrin repeats

BCAP

B cell receptor-associated protein

BCL6

B cell lymphoma 6 protein

BCR

B cell receptor

Bemab

Belimumab

BLK

B lymphocyte kinase

BLNK

B cell linker protein

BLyS

B lymphocyte stimulator

BMCT

Bonferroni test for multiple comparisons

Btk

Bruton’s tyrosine kinase

BTLA

B- and T-lymphocyte attenuator

Brilliant violet

Constant (region)

C1q

Complement component 1q

Ca2+

Calcium(II)-ion

CCL3

Chemokine (C-C motif) ligand 3

CFSE

Carboxyfluorescein succinimidyl ester

Confidence interval

c-Myc

Myc proto-oncogene protein

CpG

Cytosine-phosphodiester-guanine

CSR

Class switch recombination

CTLA-4

Cytotoxic T-lymphocyte-associated protein 4

CXCL

C-X-C chemokine ligand

CXCR

C-X-C chemokine receptor type

Cyanine

CyA

Cyclosporine A

Cyclo

Cyclophosphamide

Diversity (region)

DAPI

4',6-diamidino-2-phenylindole, dihydrochloride

DAS28

Disease activity score 28

DMARD

Disease-modifying antirheumatic drug

DMCT

Dunnett’s test for multiple comparisons

DMR

Differentially methylated regions

DMSO

Dimethyl sulfoxide (C

)

DOCK8

Dedicator of cytokinesis protein 8

DRFZ

Deutsches Rheumaforschungszentrum (German Rheumatology Research Center)

EBI2

Epstein-Barr virus-induced G-protein coupled receptor 2

EBV

Epstein-Barr virus

EDTA

Ethylenediaminetetraacetic acid

egl

Extraglandular

EIF2AK2

Eukaryotic translation initiation factor 2 alpha kinase 2

ERK

Extracellular-signal regulated kinase

ESSDAI

EULAR Sjögren's syndrome disease activity index

Eterna

Eternacept

EULAR

European league against rheumatism

EWAS

Epigenome-wide association studies

Female

Fas

Tumor necrosis factor receptor superfamily member 6

FBS

Fetal bovine serum

Flow cytometry

Fragment, crystallizable

binding receptors

FcγRIIb

fragment of IgG receptor IIb

FDC

Follicular dendritic cell

FDR

False discovery rate

FGF basic

Fibroblast growth factor 2

FITC

Fluorescein isothiocyanate

Follicular

FOXO

Forkhead box protein O

FSC

Forward scatter

Germinal center

GCRMA

Guanine cytosine robust multi-array analysis

G-CSF

Granulocyte colony-stimulating factor

Glandular

GM-CSF

Granulocyte-macrophage colony-stimulating factor

GWAS

Genome wide association studies

Height

Peroxide

HCQ

Hydroxychloroquine

Healthy donor

HRP

Heterophilic

HSC

Hematopoietic stem cell

ICOS(-L)

Inducible T cell co-stimulator (ligand)

IFI44L

Interferon induced protein 44 like

IFITM1

Interferon-induced transmembrane protein 1

IFNα/γ

Interferon α/γ

IgG/M/A/E/D

Immunoglobulin G/M/A/E/D

IgH/L

Ig heavy/light chain

Interleukin

ILC

Innate lymphoid cells

iNKT

Invariant NKT cells

IFNAR

Interferon alpha/beta receptor

IFNGR

Interferon gamma receptor

IP-10

C-X-C motif chemokine 10

IRAK-4

Interleukin-1 receptor-associated kinase 4

IRF3

Interferon regulatory factor 3

ITAM

Immunoreceptor tyrosine-based activation motif

ITIM

Immunoreceptor tyrosine-based inhibitory motif

ITP

Immune thrombocytopenia

Joining (region)

JAK

Janus kinase

LAT

Linker for activation of T cells

LFC

Linear fold change

LPS

Lipopolysaccharide

LTA

Lipoteichoic acid

Lyn

Tyrosine-protein kinase Lyn

Male

MAIT

Mucosal-associated invariant T cell

MALT

Mucosa-associated lymphoid tissue

MAPK

Mitogen-activated protein kinase

M-CLL

Mutated chronic lymphatic leukemia

MCP-1/MCAF

C-C motif chemokine 2

MFI

Median fluorescence intensity

MHC

Major histocompatibility complex

MIP-1a/b

Macrophage inflammatory protein 1-alpha/beta

MMF

Mycophenolatmofetil

MNC

Mononuclear cells

Multiple sclerosis

mTOR

Mechanistic target of rapamycin

MTX

Methotrexate

MX1

Myxoma resistance protein 1

MyD88

Myeloid differentiation primary response 88

Marginal zone

Number of donors

NAb

Natural antibody

NF-AT

Nuclear factor of activated T cells

NFκB

Nuclear factor 'kappa-light-chain-enhancer' of activated B cells

Natural killer

NOTCH2

Neurogenic locus notch homolog protein 2

NRPTP

Non-receptor-type protein tyrosine phosphatase

NSG

Non-obese diabetic scid gamma

P/S

Penicillin-Streptomycin

PALS

Periarteriolar lymphoid sheath

PAMP

Pathogen associated molecular pattern

Pacific blue

PBMC

Peripheral blood mononuclear cells

PBS

Phosphate buffered saline

PCA

Principal component analysis

PD-1

Programmed cell death protein

PDGF bb

Platelet-derived growth factor subunit B

Phycoerythrin

PerCP

Peridinin-chlorophyll-protein

PI3K

Phosphoinositide 3-kinase

PIP3

Phosphatidylinositol-3,4,5-triphosphate

PLCγ2

1-Phosphatidylinositol-4,5-bisphosphate phosphodiesterase gamma-2

Pacific orange

PP2

Serine/threonine-protein phosphatase 2

PP2A

Serine/threonine-protein phosphatase 2A

PPP2R3B

PP2A subunit B isoform PR48

PPP2R5D

PP2A B subunit isoform PR61-delta

Pred

Prednisolone

PRR

Pattern recognition receptors

PSP

Protein serine phosphatase

pSS

Primary Sjögren’s syndrome

PTEN

Phosphatase and tensin homolog

PTK

Protein tyrosine kinase

PTP

Protein tyrosine phosphatase

PTPN

Tyrosine-protein phosphatase non-receptor type

PTPRC

PTP receptor type C

PTPRN2

PTP receptor type N 2

PTPRO

PTP receptor type O

PYK2

Protein tyrosine kinase 2 beta

Pearson’s correlation coefficients

Coefficients of determination

Rheumatoid arthritis

RAG1/2

Recombination activating gene 1 or 2

RANTES

C-C motif chemokine 5

react.

Reactivity

rec

Recombinant

Rheumatoid factor

RKI

Robert Koch Institute

RPTP

Receptor-type protein tyrosine phosphatase

RRX

Rhodamine red-X

RSS

Recombination signal sequences

Room temperature

S or Ser

Serine

S1PR4

Sphingosine-1-phosphate receptor 4

Stimulation assay

Standard deviation

SH2

Src homology region 2

SHIP1

SH2 domain containing inositol polyphosphate 5-phosphatase 1

SHM

Somatic hyper mutation

SHP-1

SH2 domain-containing phosphatase-1

Siglec-1

Sialic acid-binding Ig-like lectin 1

SLAMF7

Signaling lymphocytic activation molecule family member 7

SLE

Systemic lupus erythematosus

SLEDAI

Systemic lupus erythematosus disease activity index

SLICC

Systemic lupus international collaborating clinics

SNP

Single nucleotide polymorphism

SS-A/B

Sjögren’s-syndrome-related antigen A/B

SSC

Sideward scatter

STAT5

Signal transducer and activator of transcription

Sulfa

Sulfasalazine

Syk

Spleen tyrosine kinase

T or Thr

Threonine

T-1, 2 or 3

Transitional-1, 2 or 3

TACI

Tumor necrosis factor receptor superfamily member 13B

TAK1

Nuclear receptor subfamily 2 group C member 2

Cytotoxic T cell

TCR

T cell receptor

T cell-dependent

T follicular helper cell

T helper cell

T cell independent

TLR

Toll-like receptor

TNF

Tumor necrosis factor

TNFR

Tumor necrosis factor receptor

Toci

Tocilizumab

‘Peripheral helper’ T cells

TRAF

TNF receptor-associated factor

TRIP6

Thyroid hormone receptor interactor 6

Tetanus toxin

Variable (region)

VEGF

Vascular endothelial growth factor A

Wild type

Y or Tyr

Tyrosine

ZAP-70

CD3ζ–zeta chain of TCR associated protein kinase 70

1 Zusammenfassung

Autoimmunität entsteht, wenn das Immunsystem körpereigene Strukturen (Autoantigene) erkennt. Dies

führt zur Zerstörung von Zellen und Geweben. Chronische Autoimmunerkrankungen wie z. B. der

Systemischer Lupus Erythematosus (SLE), Rheumatoide Arthritis (RA) und das primäre Sjögren

Syndrom (pSS), schränken zum einen die Lebensqualität der Patienten stark ein und zum anderen

können sie lebensbedrohliche Krankheitsverläufe wie z. B. eine Lupus-Nephritis entwickeln [1]. Die

Erkennung von Autoantigenen mittels des B-Zellrezeptors (B cell receptor, BCR), die Bildung eines

Autoimmungedächtnisses und die Wirksamkeit von B-Zell-gerichteten Therapiestrategien

unterstreichen die pathogene Rolle von B-Zellen bei der Entstehung und Progression von

Autoimmunerkrankungen [2-10]. Durch Genotypisierungs- und genomweite Assoziationsstudien

(GWAS) von B-Zellen aus Autoimmunpatienten, sowie durch funktionelle Untersuchungen von B-Zellen

in Menschen und Mäusen, konnten Zusammenhänge von veränderten BCR-Signalen und

Autoimmunität aufgezeigt werden [11-16].

Die Stärke des BCR-Signals zusammen mit Co-Signalen, wie z. B. toll-like Rezeptor (TLR)-Signalen

und Interaktionen mit T-Zellen, sind entscheidend für die Entwicklung von B-Zellen [17-21]. Bezüglich

der Qualität des BCR-Signals in Autoimmunerkrankungen, ob erhöht oder erniedrigt, gibt es

unterschiedliche Hinweise in der Literatur [14-16]. Kürzlich berichtete unserer Gruppe von einer BCR-

Dysbalance in B-Zellen von SLE Patienten, welche sich durch reduzierte Phosphorylierung der Protein

Tyrosinkinase (PTK) spleen tyrosine kinase (Syk) und folglich reduzierter Freisetzung von

intrazellulärem Ca2+ auszeichnet [14]. Des Weiteren gibt es Berichte über eine reduzierte Reaktivität

von SLE B-Zellen gegenüber TLR9-Signalen. Der TLR9 ist für die Erkennung von nukleären Antigenen

verantwortlich und bildet vermutlich zusammen mit dem BCR ein Schlüsselsignal für den Bruch der

Selbsttoleranz gegenüber nukleären Antigenen [22-25]. T-Zellhilfe via CD40/CD40-Ligand (CD40L)

Interaktion ist ein entscheidendes Signal für die Keimzellreaktion (germinal center (GC) reaction).

Dadurch wird die Entwicklung eines langzeitigen B-Zell-(Auto-)Immungedächtnisses initiiert und

verstärkt das BCR-Signal via Syk [26, 27].

Ziel dieser Studie war es, ein übergeordnetes Bild über die molekularen Prozesse während der

B-Zellaktivierung in der Autoimmunität zu erhalten. Zu diesem Zweck wurde eine vergleichende

Analyse von peripheren B-Zellen aus verschiedenen Autoimmunerkrankungen, insbesondere SLE, RA

und pSS, mit besonderem Schwerpunkt auf die BCR, TLR9 und CD40-Aktivierung durchgeführt.

Ex vivo Analysen der tonischen und anti-IgG/IgM-induzierten Tyrosin- (Y oder Tyr) oder Serin- (S oder

Ser) Phosphorylierung der Kinasen Syk, Bruton’s tyrosine kinase (Btk) und Protein Kinase B (Akt) in

konventionellen CD27- B-Zellen und CD27+ B-Gedächtniszellen lieferten eine Aussage über die

Qualität des BCR-Signals. Ergänzt wurden diese Untersuchungen mit Daten zur Protein-Tyrosin-

Phosphatase (PTP) und Protein-Serin/Threonin-Phosphatase- (PSP) Aktivität, sowie der Rekrutierung

von PTP Src homology region 2 (SH2) domain-containing phosphatase-1 (SHP-1). Die Relevanz von

Zytokinen, epigenetische Methylierung und chronische Stimulation von TRL9 und dem BCR wurde

ebenfalls analysiert. Des Weiteren wurde das Potenzial von TRL9 und gemeinsamer TLR9 und BCR-

Aktivierung hinsichtlich Proliferation und Differenzierung in Antikörper-sezernierende Zellen (antibody

secreting cell, ASC) untersucht. Abschließend wurde der Einfluss von CD40 mit und ohne Interleukin

(IL)-4 oder IL-21 Co-Stimulation auf die BCR-vermittelte Syk(Y352) Phosphorylierung und in vitro

Proliferation und Differenzierung von B-Zellen untersucht. Dies wurde ergänzt durch Expressionsdaten

von ausgesuchten PTPs und PSPs nach CD40/IL-4Co-Stimulation.

Es zeigte sich, dass periphere SLE, RA und pSS CD27+ B-Gedächtniszellen eine reduzierte

Phosphorylierung der PTKs Syk(Y352) und Btk(Y223) im Vergleich zu gesunden Spendern (healthy

donors, HD) aufwiesen. Bemerkenswerterweise war die Syk(Y352)-Phosphorylierung in peripheren

CD27- B-Zellen von SLE Patienten und in gewebeansässigen CD27+ B-Zellen von Patienten mit

Immunthrombozytopenie (ITP) und pSS, im Vergleich zu nicht-autoimmunen Patienten, ebenfalls

reduziert. Im Gegensatz dazu wurden erhöhte Akt(S473)-Phosphorylierungskinetiken in SLE CD27- B-

Zellen und CD27+ B-Gedächtniszellen gegenüber HDs gemessen. In pSS und RA CD27- B-Zellen

waren diese Kinetiken vergleichbar zu HDs.

Die PTP/PSP Aktivität in SLE, sowie die Rekrutierung von SHP-1 zum negativ Co-Rezeptor CD22 von

nicht stimulierten peripheren SLE, RA und pSS CD19+ B-Zellen war im Vergleich mit HDs erhöht. Diese

Veränderungen des BCR-Signals von SLE, RA und pSS B-Zellen standen nicht im Zusammenhang mit

der tonischen Phosphorylierung oder der Expression von Signalmolekülen (Syk, Btk, 1-

Phosphatidylinositol-4,5-bisphosphate phosphodiesterase gamma-2 (PLCγ2) und Akt),

Zytokinexpression/-stimulation und epigenetischer Programmierung. Jedoch führte die chronische

in vitro Stimulation des BCR von gesunden Kontrollen unter Re-Stimulation nach 24, 46 und 72 h, zu

einer reduzierten Syk(Y352)-Phosphorylierung. Die TLR9-induzierte Proliferation und Differenzierung zu

CD27+CD38+ ASCs von peripheren SLE, RA und pSS CD19+ B-Zellen war im Vergleich zu HDs

reduziert. Die kombinierte BCR und TLR9 Aktivierung erhöhte die Proliferation und Differenzierung von

SLE, RA und pSS CD19+ B-Zellen nur zu einem bestimmten Maße. In vitro Co-Stimulation von CD40

mit und ohne IL-4 oder IL-21 erhöhte die anti-IgG/IgM induzierte Syk(Y352)-Phosphorylierung in

peripheren SLE, RA, pSS und HD B-Zellen. Bemerkenswerterweise konnte die Syk(Y352)-

Phosphorylierung in SLE CD27- B-Zellen auf das Niveau von HDs erhöht werden. Des Weiteren führte

CD40-Co-Stimulation zu einer hohen Proliferation von SLE, RA, pSS und HD CD19+ B-Zellen. Die

Verbesserung der BCR Antwort durch CD40 Co-Stimulation steht dabei im Einklang zu der reduzierten

Expression von non-receptor-type PTPs (NRPTPs) wie z. B. tyrosine-protein phosphatase non-

receptor type 2 (PTPN2) und PTPN22, sowie weitere receptor-type PTPs (RPTPs) in HD und SLE

CD19+ B-Zellen nach CD40L/IL-4 Co-Stimulation.

Im Gegensatz zur generellen Annahme von hyperreaktiven B-Zellen in Autoimmunerkrankungen

konnte diese Arbeit zeigen, dass periphere und gewebeansässige B-Zellen von Autoimmunpatienten

funktionell beeinträchtigt sind. Dies zeigt sich unter anderem in einer reduzierten BCR- und TLR9-

Stimulierbarkeit aufgrund von erhöhter Negativregulation durch PTPs wie z. B. SHP-1. Der

ausgeprägteste Phänotyp wurde dabei in SLE B-Zellen beobachtet. Die beobachtete, reduzierte

Reaktionsfähigkeit könnte funktionell der Anergie entsprechen und spiegelt wahrscheinlich einen ‚post-

Aktivierungsstatus‘ auf Grund von chronischer B-Zellaktivierung und keine generelle Signalabnormität

wider. Diese Ergebnisse unterstreichen die Wichtigkeit der Kommunikation von B- und T-Zellen mittels

CD40/CD40L Interaktion. Zudem scheint diese Interaktion der Schlüssel für die Reaktivierung von

‚post-aktivierten‘ B-Zellen in Autoimmunerkrankungen via Modulation der PTPs zu sein. Folglich

könnten sich aus der Negativregulation von PTPs und B-Zellaktivierung via CD40 neue Perspektiven

für Therapiestrategien ergeben.

2 Summary

Autoimmunity arise when the immune system attacks self-antigens and destroys body’s own cells and

tissues. Chronic autoimmune diseases such as systemic lupus erythematosus (SLE), rheumatoid

arthritis (RA) and the primary Sjögren’s syndrome (pSS) decrease life quality of patients and can lead

to life threatening events such as lupus nephritis [1]. Recognition of self-antigens by the B cell receptor

(BCR), development of autoimmune memory and beneficial therapeutic approaches by targeting B cells

highlight the pathogenic role of B cells in development and maintenance of autoimmunity [2-10].

Genotyping and genome wide association studies (GWAS) of B cells from autoimmune patients and

functional studies in human and mice underline the role of altered BCR signaling and its contribution to

autoimmunity [11-16]. Strength of the BCR signal together with co-signals such as cytokines, toll-like

receptor (TLR) signaling and interaction with T cells determines cell fate [17-21]. However, the literature

is conflicting on whether BCR signaling is reduced or increased [14-16]. Recently, our group reported

unbalanced BCR signaling with significantly reduced phosphorylation of the protein tyrosine kinase

(PTK) spleen tyrosine kinase (Syk) and reduced intracellular Ca2+ release in SLE B cells [14]. Further

studies reported reduced responsiveness of SLE B cells to TLR9 stimulation which recognizes nuclear

antigens and is considered key in self-tolerance brake to nuclear antigens together with the BCR [22-

25]. T cell help by CD40-CD40L binding drives germinal center (GC) reaction and the development of

long term (auto)-immune B cell memory and is further known to augment BCR signaling via Syk [26,

27]. To draw a more general picture of B cell activation in autoimmunity, this study aimed at

comparatively analyzing the nature of peripheral B cell activation in different autoimmune diseases,

mainly SLE, RA and pSS, with emphasis on BCR, TLR9 and CD40 signaling. To do so, BCR signaling

quality was assessed in peripheral and tissue resident CD27- B cells and CD27+ memory B cells by

ex vivo analysis of tonic and anti-IgG/IgM induced tyrosine (Y or Tyr) or serine (S or Ser)

phosphorylation of the kinases Syk, Bruton’s tyrosine kinase (Btk) and protein kinase B (Akt). This was

supplemented by data on protein tyrosine phosphatase (PTP) and protein serine/threonine

phosphatase (PSP) activities and recruitment of the PTP Src homology region 2 (SH2) domain-

containing phosphatase-1 (SHP-1). The relevance of cytokines, epigenetic methylation and chronic

stimulation of TLR9 and the BCR was assessed. The potential of TLR9 and TLR9 together with BCR

activation to induce proliferation and differentiation into antibody secreting cells (ASCs) was

comparatively analyzed and finally, the impact of CD40/CD40L with and without interleukin (IL)-4 or IL-

21 interaction on BCR-induced Syk(Y352) phosphorylation and in vitro proliferation and differentiation of

B cells was determined. This was completed by expression data of selected PTPs and PSPs upon

CD40/IL-4 co-stimulation.

As a commonality, phosphorylation of the PTKs Syk(Y352) and Btk(Y223) was reduced in peripheral

CD27+ memory B cells from SLE, RA and pSS patients in comparison to healthy donor (HD) controls.

Notably, Syk(Y352) phosphorylation was diminished in peripheral SLE CD27- B cells compared to HD

controls and in tissue resident CD27+ B cells from patients with immune thrombocytopenia (ITP) and

pSS compared to non-autoimmune patients, too. However, Akt(S473) phosphorylation kinetics were

increased in SLE CD27- and CD27+ B cells and comparable to HDs in pSS and RA B cells. PTP/PSP

activities in SLE and overall baseline recruitment of SHP-1 to the negative co-receptor CD22 in SLE,

RA and pSS peripheral CD19+ B cells were increased compared to HDs. Signaling abnormalities of

SLE, RA and pSS B cells did not correlate to differences in tonic phosphorylation or baseline expression

of signaling molecules (Syk, Btk, 1-Phosphatidylinositol-4,5-bisphosphate phosphodiesterase gamma-

2 (PLCγ2) and Akt), cytokine expression/stimulation and epigenetic programming. However, chronic

in vitro stimulation of the BCR led to reduced Syk(Y352) phosphorylation upon re-stimulation after 24 h,

48 h and 72 h. Proliferation and differentiation into CD27+CD38+ ASCs of SLE, RA and pSS peripheral

CD19+ B cells was reduced upon in vitro TLR9 stimulation compared to HD controls. Combined BCR

and TLR9 activation enhanced proliferation and differentiation of SLE, RA and pSS CD19+ B cells only

to a certain degree. CD40 in vitro co-stimulation with and without IL-4 or IL-21 increased anti-IgG/IgM

induced Syk(Y352) phosphorylation in SLE, RA, pSS and HD peripheral B cells. Interestingly, SLE CD27-

B cells increased their Syk(Y352) phosphorylation to HD values. Furthermore, CD40 co-stimulation led

to high proliferation of SLE, RA, pSS and HD CD19+ B cells. Improvements of CD40 co-stimulation

correspond to reduced gene expression of non-receptor-type PTPs (NRPTPs) such as tyrosine-protein

phosphatase non-receptor type 2 (PTPN2) and PTPN22, and several receptor-type PTPs (RPTPs) in

HD as well as SLE CD19+ B cells upon CD40L/IL-4 co-stimulation.

Contrary to the general understanding of B cell hyperreactivity in autoimmune diseases, this study

found peripheral and tissue resident B cell from autoimmune patients being functionally impaired

towards BCR and TLR9 stimulation due to increased negative regulation by PTPs such as SHP-1.

However, the strongest phenotype was observed in SLE B cells. This reduced responsiveness may be

functionally related to B cell anergy and likely reflects a ‘post-activation’ status due to chronic B cell

activation rather than a general signaling abnormality. The results underline that communication of

B and T cells via CD40/CD40L interaction might be key for activating ‘post-activated’ B cells in

autoimmune diseases via downmodulation of PTPs. Therefore, new therapeutic approaches may target

B cell activation via CD40 or negative regulation of PTPs via the BCR.

3 Introduction

3.1 The Immune System

The immune system is a complex network of physical barriers, lymphoid organs, specialized immune

cells, humoral factors and cytokines protecting from pathogens such as bacteria, viruses, parasites and

fungi, but also from toxins and cancer cells [28, 29]. As a first line of protection, epithelial cells restrain

pathogens from entering the body. Furthermore, physiologic mechanisms such as temperature, acidic

pH values, mucus secretion and movement of ciliated epithelium in respiratory and gastro intestinal

organs assist with the elimination of pathogens [28, 29]. Microbiota on the skin, in the gut and the lung

influences the quality of such barrier functions [30-32]. Lymphoid tissues are sites of lymphoid cell

development, maturation and homing. These lymphoid cells include B and T cells which originate from

primary lymphoid organs, namely thymus, bone marrow and the fetal liver. In secondary lymphoid

organs such as the spleen, lymph nodes and mucosa-associated lymphoid tissue (MALT), cells of the

immune system get activated upon pathogen recognition. Blood and lymphatic vessels connect

lymphoid tissues and transport cells and soluble immune factors through the body [28, 29].

The immune system can be subdivided into innate and adaptive immunity. Innate immunity is unspecific

and recognizes conserved pathogen associated molecular patterns (PAMPs) such as

lipopolysaccharides (LPS), lipoteichoic acid (LTA), mannans and double stranded ribonucleic acid

(dsRNA) among bacteria, viruses and other pathogens. Fast recognition of PAMPs by pattern

recognition receptors (PRRs) provokes an immune reaction within minutes to hours. Soluble factors

such as the complement system and germline encoded natural antibodies (NAb) assist with lysis,

opsonization and clearance of pathogens, immune complexes and dead cells by phagocytes

(macrophages and neutrophils). Mast cells, basophil, eosinophils, dendritic cells (DCs), natural killer

(NK) cells and innate lymphoid cells (ILCs) are further cells of innate immunity expressing their own

specific functions [28, 29].

The highly variable adaptive immune system identifies a possibly endless number of antigens and forms

an individual and specific memory allowing rapid and efficient secondary responses. Antigens are

recognized by the BCR and T cell receptor (TCR) expressed by B and T cells, respectively. The BCR

directly binds antigens by a 3-dimensional recognition. However, the TCR requires antigen presentation

by the expression of major histocompatibility complex (MHC) class I and class II on antigen presenting

cells (APC) and is restricted to linear recognition of amino acid sequences. CD8+ cytotoxic T (TC) cells

mediated cellular immunity whereas CD4+ T helper (TH) cells promote the development and maturation

of activated B cells into memory B cells, antibody secreting plasmablasts and plasma cells [28, 29].

Close interaction between B and TH cell takes place in GCs located in follicles of lymphatic tissues [33].

However, innate and adaptive immunity share certain features such as APC function, expression of Ig

crystallizable fragment (FC) binding receptors (FCR) or the expression of PRRs such as TLRs by B cells

[28]. Furthermore, B and T cell subsets such as invariant NKT (iNKT), γδ T, mucosal-associated

invariant T (MAIT), B-1 and marginal zone (MZ) B cells possessing innate functions [33-35]. The latter

two of them have overlapping functions by producing NAbs.

The immune system is crucial for pathogen defense and survival. However, if the anti-pathogenic

system accidently recognizes self-antigens, autoimmunity can arise, and the own immune system

combats self-targets. The spectrum of autoimmune diseases is diverse and depends on the specific

target organ. SLE patients are typically self-reactive against nuclear antigens such as double stranded

deoxyribonucleic acid (dsDNA) and ribonucleoproteins resulting in multiple organ damage [36, 37].

Inflammation of the skin and nephritis are often found among those patients. RA and pSS patients

suffer mainly from synovitis and dry eyes and mouth due to destruction of excretory glands, respectively

[38-43]. Breach of B cell self-tolerance induces the development of autoreactive ASCs producing high

titers of autoreactive antibodies targeting self-antigens [38-40, 44-47]. Chronic maintenance of self-

reactivity is thought to be related to a positive feed-forward loop resulting in chronic inflammation and

tissue damage [48]. Beneficial B cell directed therapeutic approaches underscore the pathogenic and

clinical relevance of B cells in the development, maintenance and treatment of autoimmunity [3-10].

3.2 The B Cell Lineage – Development, Subsets and Tolerance Checkpoints

3.2.1 The Course of T Cell-Dependent and T Cell-Independent B Cell Responses

During an immunologic challenge, different B cell subsets become active at different and partly

overlapping time points. Circulating NAbs, continuously produced by B-1 and MZ, detect the pathogen

within minutes or hours. This is followed by a T cell-independent (TI) response of B-1 and MZ B cells

within hours to days. At the same time follicular (FO) B cells develop into IgM secreting extrafollicular

plasma cells. Those antibodies form immune complexes with the pathogens to be phagocytized and

presented by APCs fueling T cell-dependent (TD) B cell responses by FO B cells which can take days

or weeks. The development of a constitutive humoral memory represented by antibody secreting

plasma cells and reactive humoral memory by memory B cells enables a fast secondary response with

greater magnitude, switched antibody isotypes and higher affinity compared to primary responses [33,

35]. Besides, the development and maintenance of humoral immunity, B cells fulfill further functions.

For example as professional APCs and effector cells producing cytokines such as tumor necrosis factor

(TNF), chemokine (C-C motif) ligand 3 (CCL3), interferon γ (IFNγ), granulocyte-macrophage colony-

stimulating factor (GM-CSF), IL-6, IL-17, IL-2 and expressing regulatory functions due to the secretion

of IL-10 and IL-35 [33, 49-51].

3.2.2 Early Ontogeny of B-1 and B-2 B Cells

B cell subsets differ in their function, localization and developmental state determined by the interplay

of subset-specific developmental programs, environmental factors and activation state. B-1, MZ and

FO B cells are the major B cell subsets, whereas MZ and FO B cells are summarized into B-2 B cells

as they share ontogeny which is distinct from B-1 B cells. All B cells develop from bone marrow and

fetal liver resident hematopoietic stem cells (HSC). Lymphoid-primed multipotent progenitors develop

from HSC daughter cells and generate common lymphoid progenitors which further develop into B cell

as well as T cells, NK cells and DCs [33]. The ‘induced differentiation’ model of B-1 and B-2 B cell

development describes a signal-dependent differentiation from common precursor cells, whereas the

‘dual linage model’ describes distinct progenitor cell for B-1 and B-2 B cells. Both models are not

mutually exclusive. However, the description of a specific B-1 progenitor cell in fetal liver supports linage

specific hypothesis. Accordingly, B-1 B cells arise mainly from fetal liver and are self-renewing, whereas

B-2 B cells are continuously produced from bone marrow during the whole life [52, 53].

3.2.3 B-1 B Cells Mainly Undergo T Cell-Independent B Cell Responses

B-1 B cells mainly reside in pleural and peritoneal cavities. Furthermore, they populate the spleen,

secondary lymphoid and mucosal tissues, the omentum, the blood and the bone marrow. B-1 B cells

are the main producer of NAbs. The repertoire of those germline encoded IgM antibodies is generated

in the absence of antigen exposure. NAbs are polyreactive and bind to antigens expressed by various

bacteria, viruses and parasites enabling an innate-like quick first line of defense response. Moreover,

binding of self-antigens and antigens expressed by apoptotic cells assists with tissue homeostasis and

clearance of apoptotic material. Expression of PRRs such as TLR3, 4, 7 and 9 facilitates the activation

of B-1 B cells. Activated B-1 B cells start producing high levels of NAbs. In addition, they can

accumulate locally in the regional lymph nodes, migrate to spleen or mucus tissue where they

differentiate into ASCs. B-1 B cells can undergo class switch recombination (CSR) into all Ig isotypes

in vitro with IgA as preferred Ig class. Poly-specific IgA produced by B-1 B cells is the major pool of

commensal-specific antibodies and plays a role in the homeostasis of the gastro-intestinal microflora.

Furthermore, it represents a first layer of defense in the gut mucosa and respiratory tract. B-1 B cells

further subdivide into B-1a and B-1b B cells with distinct roles in immunity. B-1a B cells spontaneously

produce NAbs upon activation whereas B-1b B cells produce antibodies after exposure to antigen and

develop into memory cells which accumulate in the peritoneal cavity. In mice CD5 is a typical marker

expressed by B-1a, but not by B-1b B cells [53]. The existence of B-1 B cells in humans has been

controversially discussed. However, human B cell populations functionally similar to B-1 B cells were

described with spontaneous IgM secretion, limited somatic hyper mutation (SHM) and germline Ig

repertoire [52].

3.2.4 B-2 B Cells Subdivide into MZ and FO B Cells in the Spleen

IgM expressing immature B-2 B cells leave the bone marrow after they passed through the pro- and

pre-B cell stages. Next, they pass through two sequential transitional stages called transitional-1 (T-1)

and T-2 and finalize their development in the spleen where they become IgM- or IgD-expressing mature

naive B cells [33]. MZ and FO B cells descend from those transitional B cells [33, 35]. The spleen

histologically divides into red and white pulp. The blood slowly passes through the red pulp where red

blood cell components are filtered and recycled [33, 54]. The white pulp contains lymphocytes and

functions as secondary lymphoid organ containing B cell follicles and T cell zones [33, 35]. T-1 B cells

reside in T cell rich areas known as periarteriolar lymphoid sheath (PALS) where they undergo negative

selection upon self-reactivity. T-2 B cells colonize the follicles where they require survival signals

transduced by the BCR and B cell-activating factor (BAFF) receptor. BCR signal strength may guide

the developmental fate into MZ or FO B cells. In contrast, B cell differentiation into MZ B cells depends

on neurogenic locus notch homolog protein 2 (NOTCH2) signaling which is independent of the BCR

[35].

3.2.5 MZ B Cells Screen the Blood for Antigens

The MZ is a specialized micro-anatomic structure providing an interface between red and white pulp.

Cells leaving the blood stream transit through the MZ before they enter the white pulp which enables

MZ B cells to interact with circulating antigens for the clearance of blood-borne microorganisms and

apoptotic cells [35, 54]. The microscopic anatomy of humans and mice MZs differs. In mice, the

marginal sinus forms an inner border between the white pulps and surrounding MZ. Marginal

metallophilic macrophages populate the marginal sinus and expose native antigens to MZ B cells [35,

54, 55]. Humans completely lack the marginal sinus and marginal metallophilic macrophages [35, 55].

Here, MZ B cells are exposed to antigens within the perifollicular zone which contains neutrophils with

strong B cell helper function. Human MZ B cells can circulate and populate MZ-like zones in lymph

nodes, epithelium of tonsillar crypts and intestinal Peyer’s patches, whereas murine MZ B cells are

restricted to the MZ [35, 55]. Circulating human MZ B cells are characterized by IgM, IgD, and CD27

expression [56].

Like B-1 B cells, MZ B cells express innate-like functions with NAb production, recognition of blood-

borne type 1 TI antigens, such as LPS and type 2 TI antigens, such as polysaccharides. Furthermore,

they can bind self-antigens with low affinity [33, 35]. Activated MZ B cells develop into polyreactive low-

affinity IgM producing plasmablasts and APCs [33, 35, 54]. In contrast, TD-activated MZ B cells

differentiate into high-affinity antibody secreting long-lived plasma cells. Moreover, human and murine

MZ B cells can undergo CSR to IgA and IgG, but SHM is unique for human MZ B cells [33, 35].

Additionally, naïve CD4+ T follicular helper (TFH) cells activated by MZ B cells can stimulate FO B cells

in the white pulp [54].

3.2.6 FO B Cells Undergo TD Activation and Raise Antigen-Specific Immune Responses

Protein antigens are primarily recognized by FO B cells which represent the most prevalent B cell

subset within secondary lymphoid organs such as the white pulp of the spleen. Prior to activation,

resting naive FO B cells circulate or populate primary B cell follicles [33, 57]. Once pathogens entering

the lymph, proximal draining lymph nodes or the spleen via the blood stream they can be directly sensed

by BCRs on FO B cells, or the antigen is delivered by lymphoid organ homing DCs or activated MZ

B cells. B cell follicles are surrounded by a T cell zone, which enables close interaction of activated

B and T cells [57]. For TD activation, TH cells are activated by MHCII-antigen complexes on APCs [54,

58]. Meanwhile, activated FO B cells migrate to the T/B border guided by C-X-C chemokine receptor

type 4 (CXCR4), sphingosine-1-phosphate receptor 4 (S1PR4) and Epstein-Barr virus-induced

G-protein coupled receptor 2 (EBI2) expression, where they present antigen and receive cognate helper

signals by TH cells [58, 59]. Only B cell clones with appropriate or high antigen affinity are selected to

undergo the GC reaction. The more T cell help a B cell receives at the T/B border the more likely it is

that a B cell enters the GC and becomes a GC B cell. If there is a rather short contact of B and T cells

then a B cell is more likely to become a GC-independent memory B cell [26, 33, 57, 58]. However,

further signals by the infectious milieu, such as non-cognate bystander T cell help or TLR activation,

can affect B cell fate [58].

In the pre-GC phase, high affinity B cells directly differentiate into GC-independent extrafollicular short-

lived plasmablasts or memory B cells at the T/B border, whereas moderate affinity B cells seed GC

within the follicle [26, 58, 60]. In this phase CSR can occur, but not SHM. Therefore, many of those

short-lived plasmablasts secrete non-mutated low affinity IgM antibodies, but also IgG and IgA. Also,

GC-independent IgG+ and IgA+ memory B cells exist. These GC independent memory B cells display

a broad spectrum of antigen affinities and are able to rejoin the immune reaction at later time points

during primary infection [26, 58]. FO B cells within GC undergo proliferation, affinity maturation and

class switching into IgG+, IgA+ or IgE+ B cells. Upon this process FO B cells can differentiate into

memory B cells or long lived plasma cells expressing high affinity BCR or secrete high affinity

antibodies, respectively [26, 33, 54, 57, 58]. After antigen-specific differentiation of B cells into

plasmablasts, they migrate to the red pulp to provide rapid entry of antibodies to the blood stream [54].

3.2.7 The Germinal Center Response of B Cells after TD Activation

The GC is a specialized microenvironment within secondary follicles mainly populated by B cells, but

also FDCs, TFH cells and macrophages [57]. The GC can be subdivided into the dark and the light zone.

The dark zone is populated by B cells called centroblasts, undergoing rapid proliferation and SHM,

while the light zone harbors a class of B cells called centrocytes which compete for antigen to undergo

affinity selection [33, 57, 58]. FDCs present antigen to B cells and support the interaction of TFH cells

and centrocytes [58]. In addition to the important B cell stimulant CD40L, TFH cells also characteristically

express the inducible T cell co-stimulator (ICOS) and CXCR5 [61]. The interaction of centrocytes and

TFH cells determines whether B cells undergo another round of SHM and proliferation or leave the GC

reaction as memory B or plasma cell [57]. T/B cell interaction via CD40/CD40L ligation is of great

importance for the activation of naive FO B cells, promoting survival of GC B cells and priming for TFH

cytokine responsiveness [59]. CD40 together with cytokines such as IL-21 and IL-4 are required for GC

B cell differentiation [26, 62]. In this process, IL-21 is a key inducer of B cell lymphoma 6 protein (BCL6)

transcription factor for GC formation, maintenance, induction of SHM and CSR and plasma cell

differentiation, whereas CD40 ligation alone induced CSR, but not SHM in naive B cells [33, 59, 63,

64].

After entering the GC, B cells follow different fates depending on their BCR affinity [58]. They can exit

the GC as memory B cell or plasma cell, recycle or undergo apoptosis [58]. B cells with high affinity

BCRs exit the GC as plasma cells, whereas memory B cells preferentially originate from low affinity GC

B cell. Intermediate affinity B cells are prone to recycle and participate to another round of affinity

maturation by SHM [58]. In case of no affinity, GC B cells would not receive T cell help and undergo

tumor necrosis factor receptor superfamily member 6 (Fas) mediated apoptosis [60]. However, it is

published that memory B and plasma cells develop from GC in a temporal order. Memory B cells

appear rather early, whereas long-lived plasma cells develop rather late during GC reaction [65]. These

hypotheses are not mutually exclusive as developmental fate depends on B cell affinity and affinity

develops over time. Antigen affinity of the BCR is indirectly sensed by TFH cells via the quantity of

peptide-MHCII expression on the B cell surface. The higher the BCR affinity, the more antigen is

endocytosed and the more peptide-MHCII is presented to TFH cells inducing long lasting TFH cell help

to the B cell [26, 33, 58].

The expression of CD27 marks human post-GC memory B cells, which accumulate at the follicular

periphery outside the CD27- naive B cell region or circulate in the periphery [55, 66-68]. After CSR,

memory B cells can express IgG, IgA or IgE isotypes on the cell surface. However, CD27+IgM+,

CD27+IgM+IgD+ and CD27-IgG+ memory B cells are described [69-73], and B cell classification upon

CD27 and IgD expression distinguishes between CD27-IgD+ naive, CD27-IgD- double negative,

CD27+IgD- switched memory and CD27+IgD+ un-switched memory B cells as well as CD27++IgD-

plasmablasts [74-78]. Further surface markers such as CD38, CD21, CD24, CD19, B220, FCRH4 and

CD25 indicate additional heterogeneity among human memory B cells with individual subset-specific

functions [74].

3.2.8 Memory B and Long-Lived Plasma Cells Provide Long-Term Protection in Case of

a Secondary Immune Reaction

Memory B cells recirculate, populate at immunologically strategic sites of pathogen entry, such as IgA+

memory B cells on mucocutaneous surfaces, and can be secreted such as in breast milk [33, 58, 79].

Upon a secondary challenge, memory B cells form follicular and extrafollicular aggregates in lymphoid

tissues and differentiate into plasmablasts or re-enter the GC reaction for a diversified secondary

antibody response [26, 33, 80]. Furthermore, CXCR5+ and programmed cell death protein 1 (PD-1)+

memory TFH cells localize at the follicular T/B border to reactivate memory B cells [59]. Memory B cells

provide some cross-reactivity to related targets, which assist with the elimination of similar pathogens

upon their primary attack. This was recently demonstrated in a human vaccination study. In this study,

primary vaccination led to the activation of cross-reactive memory B cells, whereas the secondary

vaccination exclusively recruited specific memory B cells [81]. Long-lived plasma cells migrate into the

bone marrow where they find their specific niches provided by stroma cell secreting C-X-C chemokine

ligand 12 (CXCL12), IL-6 and a proliferation-inducing ligand (APRIL). Within the bone marrow, plasma

cells maintain the serological memory by continuous antigen-specific antibody production [33]. A subset

of bone marrow plasma cells lacking the expression of the B cell lineage marker CD19 has been

discovered indicating further or alternative developmental steps or functions [82]. Noteworthy,

alterations of B cell expression and subset distribution such as increased expression of circulating

CD20loCD27hi plasma cells/plasmablasts in SLE patients are associated with autoimmune diseases

[76, 77, 83-86]. This is further discussed in Section 3.4.2 “B Cell Abnormalities in SLE, RA and pSS”.

3.3 The B Cell Receptor Signaling Pathway During Development, Tolerance

Induction and Receptor Crosstalk

3.3.1 The BCR and Immunoglobulin Subclasses

The BCR is a surface-bound Ig with approximately 105 molecules being expressed on one B cell,

whereas soluble Igs (antibodies) are secreted by plasmablasts and plasma cells [33, 87]. Igs are

composed of two identical heavy (IgH) and two identical light (IgL) chains containing an N-terminal

variable (V) region, characterized by high sequence diversity, and a C-terminal constant (C) region,

respectively. The C-terminal regions of IgH are connected by disulfide bonds anchoring to the plasma

membrane and each IgH chains is connected to one IgL chain. The variable N-terminal sides of IgH

and IgL represent the antibody-specific antigen-binding side [33, 87]. Gene recombination of V, diversity

(D) and joining (J) genes (V(D)J recombination) upon recombination activating gene (RAG) 1 and

RAG2 binding to recombination signal sequences (RSS), next to V, D, and J gene segments, during

B cell development generates combinatorial diversity of IgH and IgL [87-89].

IgL genes are located within two separate gene loci, the κ and the λ locus, whereas IgH genes localize

within one single gene locus [87, 89]. Arrangement and expression of BCR genes together with BCR-

binding characteristics determine B cell development in the bone marrow. Functional IgM expressing

Immature B cells leave the bone marrow for further maturation [33, 87, 90]. Activated peripheral B cells

further diversify their V regions by SHM and can undergo CSR within GCs [87].

The C-terminal constant (FC) region of IgH determines the isotype: IgM (μ-chain), IgD (δ-chain), IgG (γ-

chain), IgA (α-chain) and IgE (ε-chain). Antibodies of those isotypes express specific effector functions

such as antigen neutralization, binding inhibitory or activating FCR on immune cells and activation of

the complement system by binding complement component 1q (C1q) [33, 87]. Furthermore, valency

and avidity are increased for multimer-forming antibodies by linking their FC portions via J chains. IgG

and IgE are monomeric, IgA is monomeric in serum, but forms dimers when secreted such as in in

tears, mucus and saliva, and IgM exists as a pentamer [33, 87]. IgD is mainly expressed as cell surface

receptor. IgG and IgA further subdivided into IgG1, IgG2, IgG3 and IgG4 and IgA1 and IgA2 subclasses

[33].

The half-life time of single antibody molecules depends on the isotype and ranges within hours and

days [33]. Murine IgM molecules survive two days, whereas IgG ranges between four and eight days.

IgE and polymeric IgA exhibit a half-life time of about 12 hours and 17 – 22 hours, respectively [91].

However, antibody titers against specific antigens can be detected over years ranging between 11 and

11,552 years half-life time for tetanus toxin (TT) and Epstein-Barr virus (EBV), respectively [92].

Continuous persistence of antibody titers, and therefore, humoral immunity are maintained by long-

lived plasma cell residing in the bone marrow [93, 94].

3.3.2 Proximal Regulation of the BCR Signaling Pathway

B cell fate is tightly regulated by intracellular BCR signaling strength transduced by post-transcriptional

changes to signaling proteins such as tyrosine, serine or threonine phosphorylation resulting in the

release of intracellular Ca2+ storages [17-20]. According to the dissociation activation model of BCRs,

antigen binding to the BCR opens auto-inhibited BCR oligomers to form clustered BCR monomers,

which makes the intracellular immunoreceptor tyrosine-based activation motifs (ITAMs) of the BCR

associated Igα (CD79a) and Igβ (CD79b) chains accessible for binding and phosphorylation of Syk [95-

98]. Upon binding to the ITAM region, Syk gets allosterically activated and further phosphorylates

downstream targets such as PLCγ2, Btk and Akt [95, 99]. Depending on the signaling strength,

developmental and environmental factors as well as further co-signals, Ca2+- and Akt-dependent

transcription factors get activated [100, 101].

Positive and negative BCR co-receptors such as CD19, CD21 and CD81 as well as CD22, CD72 and

FC fragment of IgG receptor IIb (FcγRIIb), respectively, regulate BCR signaling strength and shape

BCR-dependent Ca2+ flux [101-111]. As a negative feedback mechanism, immunoreceptor tyrosine-

based inhibitory motif (ITIM) containing co-receptors, such as CD22, CD72 and FcγRIIb recruit

phosphatases such as SHP-1 and SH2 domain containing inositol polyphosphate 5-phosphatase 1

(SHIP1) to the proximal signalosome [101, 105-111]. Upon BCR activation, the intracellular ITIM gets

phosphorylated by tyrosine-protein kinase Lyn (Lyn) leading to the recruitment of SHP-1 which

dephosphorylates PTKs such as Syk [105, 106]. The BCR-dependent balance of Syk and SHP-1

activities is essential for normal B cell development and function. [95, 112].

3.3.3 BCR Signaling Strength During B Cell Development and Tolerance Induction

BCR signaling amplitude, frequency and duration in dependence of the developmental B cell state, co-

signals and physical properties of the antigen determines cell fate by Ca2+-dependent gene expression

changes [101, 113-115]. Approximately 70 to 75 % of immature B cells display self-reactivity, and

therefore, need to undergo negative selection processes for tolerance maintenance before they leave

the bone marrow [87, 116, 117]. Mechanisms like receptor editing and clonal deletion are thought to

prevent the development of autoimmunity [118-123]. Immature B cells are most sensitive to BCR

signals [124-127]. A small induction of Ca2+ signaling can induce RAG1- and RAG2-dependent receptor

editing [121, 128, 129]. Upon deficient RAG expression or impaired BCR signaling, autoreactive B cells

accumulate and autoimmunity develops [130-132]. Low-avidity autoreactive cells can exit the bone

marrow and enter secondary lymphoid organs [87, 133]. In immature transitional stages, B cells are

sensitive to BCR-induced apoptosis at lower antigen concentrations than mature B cells [121, 134-137].

Highly self-reactive T-1 B cells undergo negative selection. However, less self-reactive cells can

proceed to the T-2 B cell stage and may cause autoimmunity [87, 138].

BCR affinity determines B cell fate within a GC reaction [20]. Besides the indirectly sensed BCR affinity

by TFH cells upon peptide-MHCII expression, differential activation of key transcription factors such as

nuclear factor of activated T cells (NF-AT) and nuclear factor 'kappa-light-chain-enhancer' of activated

B cells (NFκB) may alter GC outcome. Interestingly, both nuclear factors can be regulated via Ca2+

signaling. NF-AT is sensitive to Ca2+ signaling frequency and low Ca2+ elevation, whereas the peak

amplitude of the Ca2+ signal is relevant for NFκB regulation [139, 140]. As another potential mechanism

of tolerance induction, autoreactive B cells may acquire mutations that decrease BCR affinity away

from self-reactivity within a GC [58, 141, 142].

B cell anergy is a functionally non-reactive state of persisting autoreactive cells which escaped receptor

editing and clonal deletion [143-145]. Elevated basal Ca2+ concentrations, low BCR induced Ca2+

mobilization and phosphorylation, constitutive phosphorylation of extracellular-signal regulated kinase

(ERK), impaired proliferation, upregulation of activation marker and BCR induced Ig secretion are

characteristic for anergic B cells [125, 139, 146-148]. Human anergic B cells are mainly observed

among naive B cells such as mature naive IgD+/IgM- B cells which represent 2.5 % of total peripheral

B cells [149]. Furthermore, human T-3 peripheral B cells in lymph nodes and peripheral blood,

characterized as R123+CD38+CD24+IgD+CD27- B cells, are mainly anergic B cells that exited from T-2

or mature FO B cell subsets [150-152]. Additionally, anergy has been studied in a row of mouse models

and does not necessarily affect a distinct B cell population [153]. However, BCR hyperreactivity may

overcome B cell anergy and induce autoimmunity which has been studied in mice [13]. This is

discussed in more detail in Section 3.4.4 “Altered BCR Signaling in Autoimmunity”.

3.3.4 BCR Crosstalk with TLR9 and CD40 in B Cells

The interplay of the BCR with other receptors influences intracellular signals and shapes B cell activity

and fate. Aberrant activation or defective signaling by one or the other receptor may cause

autoimmunity by delivering wrong signals to auto-reactive cells, and therefore, let them pass through

tolerance mechanisms. In this context, BCR interactions with CD40 and TLRs such as TLR9 are of

great importance as they mediate peripheral B cell tolerance and development of TD and TI plasma

cells [13, 154-156]

Membrane-bound and soluble CD40 belongs to the tumor necrosis factor receptor (TNFR) superfamily

and is expressed by B cells, professional APCs, as well as non-immune cells and tumor cells [60]. GC

formation, CSR, SHM and the development of long-lived memory B and plasma cells requires CD40-

CD40L interaction after antigen binding to the BCR [60, 157]. Binding of CD40L to CD40 induces

clustering and conformational changes to CD40 exposing the intracellular docking side for TNF

receptor-associated factors (TRAFs) [60]. Differential recruitment of signaling molecules, such as

TRAF1, TRAF2, TRAF3, TRAF5 and TRAF6 can activate distinct downstream pathways such as

canonical and non-canonical NFκB signaling, mitogen-activated protein kinase (MAPK),

phosphoinositide 3-kinase (PI3K)/Akt, PLCγ2 and TRAF-independent Janus kinase 3 (JAK3)/signal

transducer and activator of transcription 5 (STAT5) pathway [60]. Besides CD40 activation, other

accessory signals such as cytokines may modify the responses [60]. Combined BCR and CD40

signaling via Syk induces optimal Myc proto-oncogene protein (c-Myc) expression, which is essential

for GC B cell recruitment and maintenance [27, 157].

Spontaneous TLR9 activation by the detection of dsDNA-containing antigens drives B cell activation to

become antibody secreting plasma cells by extrafollicular pathways, and therefore, plays an important

role in B cell responses against invading pathogens [156, 158-160]. Upon ligand binding, TLR9

monomers dimerize and recruit myeloid differentiation primary response 88 (MyD88) which binds

interleukin-1 receptor-associated kinase 4 (IRAK-4). Next, IRAK-4 auto-phosphorylates, associate with

IRAK1 and recruit ubiquitin ligase TRAF6. This complex translocates to the cytosol, where it activates

nuclear receptor subfamily 2 group C member 2 (TAK1). In a next step, TAK1 activates MAPK and

NFκB pathways, which in turn activates downstream transcription factors such as interferon regulatory

factor 3 (IRF3), IRF5 and IRF7 [25]. Furthermore, BCR and TLR9 signaling affects TLR9 expression,

subcellular localization, proliferation, as well as cytokine and (auto)-antibody production [25].

Patients with defective CD19 alleles have impaired upregulation of CD86, tumor necrosis factor

receptor superfamily member 13B (TACI) and CD23 after in vitro TLR9 activation which normally

induces CD19 phosphorylation through the MyD88/protein tyrosine kinase 2 beta (PYK2)/LYN complex

leading to the recruitment of PI3K, Btk and Akt [161]. Subsequently, inhibition of PI3K, Akt or Btk and

Btk deficiency results in TRL9 activation defects [161]. Furthermore, signaling molecules such as Lyn,

Syk, B cell receptor-associated protein (BCAP), B cell scaffold protein with ankyrin repeats (BANK1)

and dedicator of cytokinesis protein 8 (DOCK8) provide a link between the BCR and TLR9 pathways

[25, 162, 163].

3.4 Autoimmunity

3.4.1 Autoimmune Diseases (SLE, RA and pSS)

Development of autoimmunity is a multifactorial process including genetic factors, environmental and

stochastic events that involve innate and adaptive immunity and hormonal mechanisms [43, 133, 164].

Prevalence and incidence of autoimmune diseases depends on ethnicity, age and sex [43, 165, 166].

Disease pathology of B cell-dependent autoimmunity depends on the nature of secreted autoantibodies

such as activation or blocking of receptors, induction of altered signaling, thrombosis, cell death and

induction of inflammation [167]. The target organ of a specific disease and the associated autoantibody

profile, which are often used to classify and diagnose the diseases, differs.

Patients with SLE characteristically produce anti-nuclear antibodies (ANA) including anti-dsDNA

autoantibodies [44, 45]. The reduced clearance of immune complexes causes multiple and severe

organ damage such as vasculitis or glomerulonephritis [36, 37]. Whereas patients with RA suffer mainly

from synovitis which is accompanied by the production of rheumatoid factor (RF) and/or antibodies

against citrullinated antigens (ACPA) leading to cartilage and bone destruction [38-40]. In pSS, patients

show self-reactivity against excretory glands resulting into dry eyes and mouth and other mucosal

surfaces; in a substantial proportion of patients extraglandular manifestations occur [41-43]. Here,

autoantibodies against the ANA specificities Ro/ Sjögren’s-syndrome-related antigen A (SS-A) and

La/SS-B together with RF are typical findings [46, 47, 168]. Autoantibodies typically appear many years

before SLE disease onset while patients are still asymptomatic [45]. ANA+ healthy individuals differ

from ANA+ SLE patients in their cytokine expression by lacking the characteristically increased

expression of IFNs, B lymphocyte stimulator (BLyS), IL-12p40 and stem cell factor/c-Kit ligand

indicating that the cytokines may also play a role in the onset of the autoimmune diseases [169].

3.4.2 B cell Abnormalities in SLE, RA and pSS

B cell hyperreactivity and chronic activation of the B cell compartment is a hallmark of autoimmune

diseases such as SLE, RA and pSS. Typical findings in SLE are high frequencies of circulating

CD20loCD27hi plasma cells/plasmablasts and CD27-IgD-CD95+IgG+, IgA+ or IgM+ memory-like “double

negative” B cells in the peripheral blood [76, 77, 83-86]. This was found to correlate with disease activity

[83]. In RA patients circulating FcRL4 tissue-resident B cells have been reported [170]. Notably, CD19-

plasma cells were found in the synovium of RA patients [82]. Patients with pSS appear to have reduced

CD27+ memory B cells and increased soluble CD27 in peripheral blood which may correlate with

CXCR4 depended accumulation of memory B cells in salivatory glands of pSS patients [171-175].

Several studies concluded that defective tolerance checkpoints before and after antigen activation and

defects in peripheral and central selection permit the emergence and maintenance of autoreactive

B cells [2, 87, 176-183].

Negative and positive selection during B cell development is mainly driven by the BCR. However,

signals by other receptors such as TLRs and CD40 synergize with the BCR signal and may modulate

repertoire selection towards autoreactivity along TD and TI pathways [183-185]. In this line, TLR9

activation may govern the development of autoantibodies against dsDNA and ribonucleoproteins [186,

187]. Furthermore, immune complex containing DNA and ribonucleoproteins can activate autoreactive

B cells by dual-recognition via the BCR and TLR9 receptor resulting in tolerance break against nuclear

antigens [160, 188-190]. Those TRL9-driven B cell responses may be amplified by high activity of

peripheral DCs (pDCs) and high IFNα expression, which is a hallmark in SLE and is also described for

pSS [191-194]. Furthermore, autoreactive anergic cells can be reactivated by strong T cell help

provided by CD40L and IL-4 [183].

In this context, phenotypic and genetic studies of BCR gene rearrangements found abnormalities in the

memory B cell repertoire together with autoantibodies almost exclusively being encoded by SHM BCR

rearrangements [180, 195, 196]. In SLE patients selection of autoreactive B cells occurs upon ongoing

polyclonal activation and recruitment of naive B cells by extrafollicular and early GC pathways [197].

Recent studies of SLE B cells found that ANA+ plasma cells originate from extrafollicular as well as GC

pathways [198].

3.4.3 Mutations in BCR Signaling and Functional Consequences

Mutations of BCR-associated signaling molecules or co-receptors can have fatal impact on B cell

development, immunologic functions and health of affected individual. For example, patients with

X-linked agammaglobulinemia lack the expression of functional Btk which is an important mediator of

the BCR signaling cascade. B cell development is abrogated in these patients leading to a lack of

peripheral B cells and reduced antibody titers of all classes, making those patients highly susceptible

to infections [199].

Genotyping and GWAS indicated that defects in BCR signaling might be key for disturbed self-

recognition and hyperreactivity of B cells in autoimmune diseases such as SLE [11, 200]. Those studies

identified certain mutations of downstream scaffold proteins, PTKs or abnormal PTPs, such as Lyn,

B lymphocyte kinase (BLK), BANK1 and PTPN22, suggesting intrinsic BCR hyperactivity [11, 201-206].

Indeed, results of these GWAS suggested that certain risk genes might be connected to aberrant BCR

signaling in autoimmunity with overlapping ethnicities [11, 201-204, 207-210]. It is reported that RA,

SLE and pSS share some common genetic risk genes such as PTPN22 1858C/T risk mutation,

whereas BANK1 risk mutation appears to be specific for SLE and RA [207-209, 211-216]. However,

another study reported that BANK1 risk mutation is not shared between SLE and RA [217].

The functional impact of those mutations and the global interactions are largely unknown and not fully

delineated. A growing body of literature indicates that the PTPN22 1858C/T polymorphism is a gain-of-

function mutation reducing TCR as well as BCR responses [218-220]. However, in mice PTPN22 risk

mutation is reported to increase BCR signaling [221]. It is also reported that the PTPN22 risk allele is

associated with higher IFNα activity and lower TNF expression [222]. The risk mutation of the adapter

molecule BANK1, which is mainly expressed in CD19+ B cells, leads to a dysbalanced expression of

BANK1 splicing variants, which in turn reduces BCR signaling [204, 223].

3.4.4 Altered BCR Signaling in Autoimmunity

Alterations in the intrinsic BCR signal are thought to promote autoimmunity by affecting the selection

of the naive repertoire and promotion of autoreactive clones during extrafollicular and GC responses

[184]. Furthermore, abnormal BCR signaling in anergic cells may cause activation of silenced

autoreactive B cells [224]. Hyperreactivity in rheumatic diseases is considered to be reflected by

alterations in BCR-associated kinase expression and phosphorylation [225, 226]. However, the major

understanding of BCR signaling in autoimmunity is based on studies in mice, in which increased BCR

signal is a driver of autoimmunity [13]. This is often caused by a lack of negative regulators such as

CD22 and FcγRIIb as well as SHP-1, but also PLCγ2 gain-of-function mice are reported to develop

autoimmunity [227-230]. The role of Lyn is more complex as both, Lyn–/– and Lynup/up mice, produce

ANAs upon B cell hyper-responsiveness [13]. Furthermore, murine B cells overexpressing Btk were

hyperresponsive to BCR stimulation with increased Ca2+ influx, resistance to Fas-mediated apoptosis,

spontaneous GC formations and defective elimination of self-reactive B cells in vivo [231].

Human studies are contradictory in this regard. Some studies reported increased BCR signaling

measured by Ca2+ release and downstream tyrosine phosphorylation caused by a lack of negative

regulation, such as FcγRIIb, phosphatase and tensin homolog (PTEN) and Lyn, in B cells from SLE

patients [15, 16, 232-237]. However, more recent studies reported evidence that the BCR signal in

autoimmunity is impaired, at least in some B cell subsets, with reduced tyrosine phosphorylation, Ca2+

release and recruitment of signaling kinases to lipid rafts upon BCR stimulation [14, 218, 223, 237,

238].

3.4.5 B Cell Directed Therapies in Autoimmune Diseases

The beneficial therapy of SLE, RA and pSS patients with Rituximab underlines the important role of

B cells in the pathogenesis of these autoimmune diseases [3-10, 239]. Rituximab targets the B cell

lineage marker CD20, which mediates Ca2+ influx, and successfully depletes peripheral B cells except

mature ASCs which lack CD20 expression [10]. Targeting B cell lineage survival factors by the

humanized anti-BAFF antibody belimumab is approved in the EU and the USA for the treatment of SLE.

This therapeutic antibody reduces disease activity as well as flare severity and incidence when provided

in combination with standard therapy [10, 196]. However, none of those treatment strategies targets all

B cell subset at once. Anti-CD20 treatment using Rituximab does not deplete long-lived plasma cells

which are responsible for the long-term production of autoantibodies in autoimmune diseases [240].

Also, the anti-BAFF antibody Belimumab does not deplete memory B cells or inhibit IgG autoantibody

production [10, 196]. Therefore, a combination therapy targeting precursors of long-lived plasma cells

and plasma cells using a plasma cell depleting agent, such as the small molecule proteasome inhibitor

bortezomib, might be of therapeutic value and are under research [10, 196, 241].

Besides depletion therapy, another approach is targeting B cell activation by interfering with the BCR

signaling pathway via anti-CD22 antibodies. This approach might be useful, because the quality of the

BCR signal plays an important role in cell fate decision making, B cell activation and maintenance of

self-tolerance [17, 125, 129]. The anti-CD22 therapy aims at reducing BCR hyper-activation by reducing

the BCR signaling strength. CD22 helps in maintain the balance between Syk and SHP-1 activity, and

interfering with this pathway decreases the BCR signal and enhancing the activation threshold [110,

242]. Furthermore, approaches by targeting the IFNα pathway in SLE may have beneficial effects on

B cells by lowering TLR-dependent responses [243].

4 Hypothesis and Aim

B cells are the major source of autoantibodies in diseases such as SLE, RA and pSS, and therefore, a

key element of disease pathology [38-40, 44-47]. Abnormal BCR signaling events in autoimmune

diseases might be responsible for pathologic recognition of autoantigens by B cells. Previous research

implicate reduced responsiveness of SLE B cells towards BCR signals due to abnormal negative

regulation via CD22 feedback loop and increased tyrosine phosphatase activity [14]. Results from our

working group implicate an increased negative regulation by CD22 and SHP-1 as a commonality in

SLE, RA and pSS peripheral B cells (Section 6.1, Figure 5) [244]. To explore potential underlying

molecular or functional abnormalities, this thesis aimed at further characterizing B cell responsiveness

in autoimmunity by addressing the following questions:

a) Is the phenotype of recently observed low responsiveness towards BCR and TLR9 stimulation

specific for SLE or a commonality among peripheral B cell related autoimmune diseases such

as RA and pSS?

i. Are there specific phenotypic properties among peripheral SLE, RA and pSS B cells

with regard on the expression and phosphorylation of BCR signaling molecules and

surface markers related to BCR signaling?

ii. Are there common BCR related functional abnormalities among B cells from SLE, RA

and pSS patients?

iii. Is this phenotype restricted to B cells from the peripheral blood or does this also apply

for tissue resident B cells?

b) Are there potential inducers of abnormal signaling events such chronic stimulation with

cytokines and TLR9 or BCR?

c) Which impact has T cell-dependent co-stimulation on abnormal signaling events in SLE, RA

and pSS?

d) How does T cell-dependent co-stimulation affect proliferation and differentiation of SLE, RA

and pSS B cell?

Question a) was addressed by analyzing phenotypic and functional properties of the BCR signaling

cascade in peripheral B cells from SLE, RA and pSS patients in comparison to HDs. This was done by

analyzing the expression and phosphorylation of BCR signaling molecules with and without BCR

stimulation. This thesis also includes data from our group on PTP/PSP activities and CD22/SHP-1 co-

localization in B cells from SLE, RA and pSS patients compared to HD controls. Additionally, tissue

resident B cells from tonsils, autoimmune ITP and non-autoimmune spleens as well as one pSS parotid

were analyzed for functional BCR signaling.

To address question b), pSyk(Y352) after BCR stimulation in HD, SLE, RA and pSS peripheral B cells

was correlated with a panel of 28 different cytokines and sialic acid-binding Ig-like lectin 1 (Siglec-1)

expression as a surrogate marker for INFα activity. Furthermore, pERK1/2(T202/Y204) was tested as a

potential marker for anergy in autoimmune disease patients. It was tested whether low B cell

responsiveness could be induced by pre-incubation of HD B cells with IFNα, IFNγ, IL-21, IL-2, IL-6,

IL-10 or chronic stimulation of TLR9 and the BCR. In addition, epigenetic abnormalities of SLE, RA and

pSS B cells were analyzed in a meta-analysis from publicly available data together with cooperation

partners.

To answer question c), different CD40 co-stimulating systems were tested. Moreover, the impact of

CD40 co-stimulation together with IL-4 or IL-21 on BCR induced Syk(Y352) phosphorylation was

analyzed in B cells from SLE, RA and pSS patients compared to HDs.

Finally, question d) was addressed analyzing B cell proliferation and differentiation after in vitro

activation of TLR9 and the BCR with and without CD40 co-stimulation. Furthermore, expression of

phosphatases was analyzed from publicly available RNA sequencing data at baseline and upon

CD40L/IL-4 stimulation (by cooperation partners).

5 Donors, Materials and Methods

5.1 Blood and Tissue Donors

This study was approved by the ethic committee of the Charité – Universitätsmedizin Berlin. Written

informed consent was obtained from all donors. Patients with RA fulfilling the American College of

Rheumatology (ACR)/ European League Against Rheumatism (EULAR) criteria [245], SLE according

the Systemic Lupus International Collaborating Clinics (SLICC) criteria [246] and pSS fulfilling the

American-European Consensus Group (AECG) criteria [247] were included in this study.

Ethylenediaminetetraacetic acid (EDTA) anti-coagulated peripheral and/or serum blood samples from

87 SLE, 51 pSS and 44 RA patients and 129 HDs were collected. Ethnicity, gender, mean age, disease

activity and medication of donors are summarized in Table 1. Specimens of human spleens and tonsils

were collected from surgeries with medical implications (Table 2).

Table 1: Gender, mean age, ethnicity, disease activity score and medication of blood donors.

n = 129

Gender

102 females, 27 males

Ethnicity

128 Caucasians, 1 Indian

Mean age [range]

33 [21 – 65]

SLE

n = 87

Gender

79 females, 7 males

Ethnicity

85 Caucasians, 1 African, 1 Asian

Mean age [range]

40 [19 – 73]

SLEDAI

70 low (< 6), 13 high (> 6)

Treatment

7 none, 12 Pred, 5 MTX, 8 HCQ, 1 Aza, 1 Cyclo, 13 Pred/HCQ, 9 Pred/Aza, 2 Aza/HCQ,

1 MTX/HCQ, 4 Pred/MMF, 1 HCQ/MMF. 2 Pred/Cyclo, 2 Pred/CyA, 2 MTX/Pred/HCQ,

3 Pred/Aza/HCQ, 3 Pred/MMF/HCQ, 1 Pred/HCQ/Bemab, 1 HCQ/MMF/Bemab,

3 Pred/HCQ/Cyclo, 1 Pred/MTX/HCQ, 1 Pred/HCQ/MMF/Bemab

n = 44

Gender

34 females, 9 males

Ethnicity

44 Caucasians

Mean age [range]

55 [26 – 79]

DAS28

27 low (< 3.2), 7 moderate (3.2 – 5.1), 7 high (> 5.1)

Treatment

1 none, 6 Pred, 6 MTX, 2 Eterna, 1 Toci, 9 MTX/Pred, 1 MTX/Abata, 5 Pred/Toci,

2 Pred/Eterna, 1 MTX/Simponi, 3 MTX/Eterna, 1 MTX/Pred/Sulfa, 1 Pred/Toci/Sulfa,

2 MTX/Pred/Eterna, 1 MTX/Pred/Abata

pSS

n = 51

Gender

50 females, 1 male

Ethnicity

51 Caucasians

Mean age [range]

56 [34 – 80]

ESSDAI

41 low (< 4), 10 high (> 4)

Manifestation

14 gl, 37 egl

Treatment

18 none, 6 Pred, 17 HCQ, 1 Cyclo, 1 CyA, 6 Pred/HCQ, 1 Pred/Aza, 1 Aza/HCQ

Abatacept (Abata), azathioprine (Aza), belimumab (Bemab), cyclophosphamide (Cyclo), cyclosporine A (CyA), Disease Activity

Score 28 (DAS28), eternacept (Eterna), EULAR Sjögren's syndrome (SS) disease activity index (ESSDAI), extraglandular (egl),

glandular (gl), hydroxychloroquine (HCQ), methotrexate (MTX), mycophenolatmofetil (MMF), number of donors (n), prednisolone

(Pred), sulfasalazine (Sulfa), Systemic Lupus Erythematosus Disease Activity Index (SLEDAI), tocilizumab (Toci)

Table 2: Age, disease and gender of spleen, tonsil and parotid donors.

Tissue

Age at date of surgery

Sex

Disease

Spleen 1

ITP

Spleen 2

ITP

Spleen 3

ITP

Spleen 4

ITP

Spleen 5

Pancreatitis

Spleen 6

Cancer

Spleen 7

Splenomegaly

Spleen 8

Cysts

Spleen 9

Cancer

Spleen 10

Pancreatitis

Spleen 11

Cancer

Tonsil 1

Tonsil 2

Tonsil 3

Tonsil 4

Parotid

pSS

Female (f), male (m), no information (-)

5.2 Materials

Relevant information on consumables (Table 3), chemicals and commercially available buffer

(Table 4), commercial kits (Table 5), buffer, media and preparations (Table 6Table 7), antibodies

(Table 7), stimulation reagents, inhibitors and cytokines (Table 8), cell lines (Table 9), electronic

devices (Table 10) and analysis software (Table 11) are provided below. Supplier information is listed

in the appendix (Supplementary Table 1).

Table 3: Consumables with supplier.

Product

Supplier

Anti-Mouse Ig, κ/Negative Control Compensation Particles

Set BD Bioscience

Calibration Kit BioPlex

BioRad

Product

Supplier

CELLSTAR cell culture flask, 250 ml, 75 cm2, PS, red cap

Greiner Bio-One International GmbH

CELLSTAR cell culture micro plate, 96 well, PS, U–bottom

Greiner Bio-One International GmbH

CELLSTAR cell culture multiwell plate, 24 well, PS, F–

bottom Greiner Bio-One International GmbH

Combitips (various)

Eppendorf

CountBright™ Absolute Counting Beads

Invitrogen/Thermo Fisher

CS&T Research Beads (BD FACSDiva™ software v7 or

later) BD Bioscience

CS&T Beads Kit (BD FACSDiva™ software v6.x)

BD Bioscience

Falcon 70 µm Cell Strainer

Corning

Falcon 15 ml Conical Centrifuge Tubes

Fisher scientific/Thermo Fisher

Falcon 50 ml Conical Centrifuge Tubes

Fisher scientific/Thermo Fisher

Falcon Round-Bottom Polystyrene Tubes

Fisher scientific/Thermo Fisher

FcR Blocking Reagent, human

Miltenyi Biotec GmbH

Heterophilic (HRP) Blocking Tubes

Scantibodies Laboratory

Micrewtube

VWR International GmbH

Microcentrifuge tubes, Safe-Lock PCR clean (0.5 µl)

Eppendorf

Microplate, 96 Well, PS, U-Bottom

Greiner Bio-One International GmbH

MultiScreen

HTS

-BV, 1.2 µm, filter plate

Merck KGaA

Pre-Separation Filters (30 µm)

Miltenyi Biotec GmbH

Rainbow Calibration Particles (8 peaks), 3.0 - 3.4 µm

BD Bioscience

SafeSeal SurPhob filter tips (various)

Biozym Scientific GmbH

Serological pipettes (various)

SARSTEDT AG & Co. KG

Tube 5 ml, 75x12 mm, PS

SARSTEDT AG & Co. KG

VACUETTE EDTA Tubes

Greiner Bio-One International GmbH

VACUETTE Serum collection tubes

Greiner Bio-One International GmbH

Vacutainer Plastic Plus EDTA Blood Collection Tubes

BD Bioscience

Vacutainer Plus Plastic SST Blood Collection Tubes with

Polymer Gel for Serum Separation BD Bioscience

Table 4: Chemicals and commercially available buffers.

Chemical

Supplier

4',6-diamidino-2-phenylindole, dihydrochloride (DAPI)

Invitrogen/Thermo Fisher

AF488 succinimidylester

Molecular Probes/Thermo Fisher

autoMACS Rinsing Solution

Miltenyi Biotec GmbH

BD Pharm Lyse (10x)

BD Bioscience

BD Phosflow Perm Buffer II

BD Bioscience

BD Phosflow Perm Buffer III

BD Bioscience

Brilliant Stain Buffer

BD Bioscience

Buffer EL

Qiagen

Dimethyl sulfoxide (C

; DMSO)

Invitrogen/Thermo Fisher

Fetal Bovine Serum (FBS), heat inactivated

gibco by life technologies/Thermo Fisher

Chemical

Supplier

Ficoll Paque Plus

GE Healthcare

Lyse/Fix Buffer (5X)

BD Bioscience

MACS BSA Stock Solution

Miltenyi Biotec GmbH

Dihydrogen peroxide (H

)

Merck KGaA

Penicillin-Streptomycin (P/S) (10,000 U/ml)

gibco by life technologies/Thermo Fisher

Phosphate Buffered Saline (PBS), without Ca2+, Mg2+

Merck KGaA

RPMI 1640 Medium, GlutaMAX Supplement

gibco by life technologies/Thermo Fisher

Ultra-pure water

Merck KGaA

Table 5: Commercial kits.

Kit

Supplier

Bio-Plex Pro Human Cytokine 27-plex Assay

Bio-Rad Laboratories

Bio-Plex Pro Human Th17 Cytokine IL-21

Bio-Rad Laboratories

CellTrace Carboxyfluorescein succinimidyl ester

(CFSE) Invitrogen/Thermo Fisher

Table 6: Buffer, media and preparations.

Buffer

Reagent

Concentration/dilution

Complete medium

(RPMI, 10 % FBS, 1 % P/S)

FBS

10 %

P/S (10,000 U/ml)

1 %

in RPMI 1640 with GlutaMAX™

CFSE

CellTrace CFSE

(kit component A)

5 mM (stock)

in DMSO (kit component B)

Erythrocytes lysis buffer

Buffer EL

4:1

in MACS buffer

Freezing medium

DMSO

1:10

in FBS

Lyse/Fix Buffer

Lyse/Fix Buffer (5X)

1:5

in H

MACS Buffer

(PBS, 0.5 % BSA, 2 mM EDTA)

MACS BSA Stock Solution

1:10

in autoMACS Rinsing Solution

PBS/BSA

(PBS, 0.1 % BSA)

MACS BSA Stock Solution

1:50

in PBS

Pharm Lyse

BD Pharm Lyse (10x)

1:10

in H

Table 7: Antigens, conjugates, clones and supplier of the applied antibodies.

Antigen

Conjugate

Clone

Species

React.

Supplier

Applic.

CD3

UCHT1

mouse

human

BD Bioscience

CD14

APC-Cy7

M5E2

mouse

human

BioLegend

CD14

M5E2

mouse

human

BD Bioscience

CD19

PE-Cy7

SJ25C1

mouse

human

BD Bioscience

Antigen

Conjugate

Clone

Species

React.

Supplier

Applic.

CD20

BV510

2H7

mouse

human

BioLegend

CD20

HI47

mouse

human

Invitrogene

CD20

PerCp-Cy5.5

H1(FB1)

mouse

human

BD Bioscience

CD22

S-HCL-1

mouse

human

BD Bioscience

CD27

APC

L128

mouse

human

BD Bioscience

CD38

APC-Cy7

mouse

human

BioLegend

CD40

None

G28-5

mouse

human

Andreas Hutloff 1)

Akt1 PerCp-Vio700 REA134

rec

human human Miltenyi Biotec FC

pAkt(S473)

M89-61

mouse

human

BD Bioscience

Btk

53/BTK

mouse

human

BD Bioscience

pBtk(Y223)

FITC

N35-86

mouse

human

BD Bioscience

pERK1/2(T202/Y204)

AF488

20A

mouse

human

BD Bioscience

IgG/IgM (F(ab’)2) None Poly goat human

Jackson

ImmunoResearch SA

Isotype control

AF488

MOPC-21

mouse

BD Bioscience

pPI3K p85(Y467)/

p55(Y199) AF488 2) Poly mouse human

Invitrogene

/Thermo Fisher FC

pPI3CD(Y524)

AF488

Poly

rabbit

human

Bioss Antibodies

REA Control (I) PerCp-Vio700 REA293

rec

human human Miltenyi Biotec FC

pSHP-1(Y564)

AF488 2)

Poly

rabbit

human

Thermo Fisher

Siglec-1

AF647

7-239

mouse

human

BD Bioscience

Syk

FITC

4D10

mouse

human

BD Bioscience

pSyk(Y352) PE

17A/P-

ZAP70 mouse human BD Bioscience FC

PLCγ2

K86-1161

mouse

human

BD Bioscience

pPLCγ2(Y759)

AF488

K86-689.37

mouse

human

BD Bioscience

Alexa flour (AF), allophycocyanin (APC), application (applic.), brilliant violet (BV), Bruton’s tyrosine kinase (Btk), cyanine (Cy),

flow cytometry (FC), fluorescein isothiocyanate (FITC), Mitogen-activated protein kinase 3 (ERK1), pacific blue (PB), pacific

orange (PO), peridinin-chlorophyll-protein (PerCP), 1-phosphatidylinositol-4,5-bisphosphate phosphodiesterase gamma-2

(PLCγ2), phosphoinositide 3-kinase (PI3K), phycoerythrin (PE), protein kinase B (Akt1), reactivity (react.), recombinant (rec),

sialic acid-binding immunoglobulin-type lectin 1 (Siglec-1), spleen tyrosine kinase (Syk), src homology region 2 domain-

containing phosphatase-1 (SHP-1), stimulation assay (SA)

1) Provided by Andreas Hutloff, German Rheumatology Research Center (DRFZ) and Robert Koch Institute (RKI), Berlin,

Germany

2) Labeling at the DRFZ by the lab manager core facility

Table 8: Stimulation reagents, inhibitors and cytokines.

Target

Reagent

Supplier

final

CD40

anti-CD40 antibody

Andreas Hutloff (DRFZ/RKI)

0.1, 1, 5, 10, 100 µg/ml

CD40

CD40L cross-linking Kit

Miltenyi Biotec GmbH

0.5 µg/ml

CD40

sCD40L

PeproTech

0.5 µg/ml

IgG/IgM 1) 2)

anti-IgG/IgM F(ab’)

Jackson ImmunoResearch

13 µg/ml (LOT 121170)

9 µg/ml (LOT 125959)

9 µg/ml (LOT 135690)

Target

Reagent

Supplier

final

IgG/IgM 3)

anti-IgG/IgM F(ab’)

Jackson ImmunoResearch

2 µg/ml (LOT 125959)

IL-2R

rec. human IL-2

Miltenyi Biotec GmbH

0.02 µg/ml

IL-4R

rec. human IL-4

PeproTech

0.02 µg/ml

IL-6R

rec. human IL-6

PeproTech

0.02 µg/ml

IL-10R

rec. human IL-10

Miltenyi Biotec GmbH

0.02 µg/ml

IL-21R

rec. human IL-21

PeproTech

0.02 µg/ml

IFNAR

rec. human IFNα

PeproTech

100 ng/ml

IFNGR

rec. human IFNγ

PeproTech

100 ng/ml

Syk

Entospletenib

Selleck Chemicals

0.1, 1, 10 µM

TLR9

CpG (ODN2006)

Miltenyi Biotec GmbH

0.5 µg/ml

Cytosine-phosphodiester-guanine (CpG), interferon alpha/beta receptor (IFNAR), interferon gamma receptor (IFNGR),

recombinant (rec), soluble CD40L (sCD40L), spleen tyrosine kinase (Syk), toll-like receptor 9 (TLR9)

1) Phospho-kinetics

2) Reagents with different LOT numbers were titrated to the same biological activity

3) Cell culture experiments

Table 9: Cell lines.

Cell line

Organism

Cell type

Modifications

L cells 1)

mouse

fibroblasts, adherent

none

hCD40L L cells 1)

mouse

fibroblasts, adherent

transfected with hCD40L

human CD40L (hCD40L)

1) Provided by Andreas Hutloff, DRFZ and RKI, Berlin, Germany

Table 10: Electronic devices.

Device

Supplier

BioPlex System reader

Bio-Rad Laboratories

FACSCanto II flow cytometer

BD Bioscience

Gammacell® 40 Exactor radiation source

MDS Nordion

LSRFortessa flow cytometer

BD Bioscience

Table 11: Applied software

Software

Supplier

FACS Diva v6.1.3 (FACSCanto II)

BD Bioscience

FACS Diva v8.0.2 (LSR Fortessa)

BD Bioscience

FlowJo 10.4.2

TreeStar

GraphPad Prism v5.04

GraphPad Software

BioPlex Manager v4.1.1

Bio-Rad Laboratories

5.3 Quality Control of Flow Cytometry Staining

Quality control of flow cytometry staining was performed using SPHERO Rainbow Calibration Particles

for stable median fluorescence intensity (MFI) over time and Cytometer Setup and Tracking beads

[248].

5.4 Siglec-1 Expression as Surrogate Marker for In Vivo IFNα Activity

IFNα activity was assessed upon flow cytometric analysis of Siglec-1 (CD169) expression on CD14+

monocytes from fresh peripheral whole blood. Sample preparation and analysis described in this

section was done in cooperation with Karin Reiter (technical assistant, laboratory of Prof. Dr. Dörner,

Charité – Universitätsmedizin Berlin, Berlin, Germany). Siglec-1 analysis was performed as described

earlier [194]. Briefly, whole blood (200 µl) was lysed with 2 ml Pharm Lyse (15 min, room temperature

(RT)). The cells were centrifuged (310 xg, RT) and washed two times with 3 ml MACS buffer (310 xg,

4 °C). Fifty µl cell suspension were incubated with 2.5 µl human FcR blocking reagent (5 min, RT),

stained with CD14-APC-Cy7 and Siglec-1-AF647 (15 min, 4 °C), centrifuged (310 xg, 5 min, 4 °C) and

suspended in 100 µl MACS buffer. DAPI (900 nM) was added before measurement for dead cell

exclusion. Siglec-1 expression was analyzed as MFI on CD14+ monocytes using FACS Canto II and

FACS Diva Software (gating strategy in Figure 1).

Figure 1: Analysis of Siglec-1 expression on CD14+ monocytes (gating strategy). Monocytes were gated according to their

properties in forward (FSC) and sideward (SSC) scatter (left panel) and their CD14 expression (mid panel). An example of

Siglec-1 expression on SLE (red) and HD (black) CD14+ monocytes is given in the right panel.

5.5 Intracellular B Cell Phenotyping for BCR Downstream Kinase Expression and

Phosphorylation at Baseline

Baseline expression and phosphorylation of intracellular kinases were analyzed using intracellular flow

cytometry based on formaldehyde and methanol fixation and permeabilization. For this, fresh peripheral

whole blood (100 µl) was lysed and fixed in 1 ml pre-warmed Lyse/Fix Buffer (10 min, 37 °C). Next,

cells were washed twice with 3 ml ice cold PBS (8 min, 500 xg) and permeabilized with 200 µl Perm

buffer II or III (-20 °C, 12 h). Perm buffer II was used for analysis of the combinations Syk/pSyk(Y352)

and PLCγ2/pPLCγ2(Y759) and Perm buffer III was used for the analysis of Akt/pAkt(S473) and

Btk/pBtk(Y223). Finally, cells were washed two times with 3 ml MACS buffer (8 min, 500 xg, 4 °C) and

stained with the following marker-fluorochrome combination: CD3-PB, CD14-PB, CD19-PE-Cy7,

CD20-PO, CD27-APC and one of the combinations of Syk-FITC/pSyk(Y352)-PE, PLCγ2-

PE/pPLCγ2(Y759)-FITC, Akt1-PerCp-Vio700/pAkt(S473)-PE or Btk-PE/pBtk(Y223)-FITC.

Washed cells were analyzed using FACS Canto II flow cytometer and FACS Diva Software. Akt,

pAkt(S473), Btk, pBtk(Y223), PLCγ2, pPLCγ2(Y759), Syk, pSyk(Y352) MFIs were analyzed from CD27-

B cells and CD27+ memory B cells (gating strategy in Figure 2). CD3+ lymphocytes served as internal

negative control, except for the staining of Akt1. Here an isotype control using REA Control (I)-PerCp-

Vio700 in the same concentration as the antibody was used.

Figure 2: Analysis of intracellular kinases within CD27- B cells and CD27+ memory B cells. Lymphocytes were identified

based on their FSC and SSC characteristics (left panel). Doublets, CD3+ and CD14+ cells were excluded using height (H) and

area (A) of FSC (second left panel). B cells were defined as CD3-/CD14- and CD19+ cells (third panels from left). The CD27-

B cells and CD27+ memory B cell subsets were gated upon their expression of CD20 and CD27 (lower right panel). CD3+/CD14+

cells were back gated on lymphocytes (upper right panel). CD3+ lymphocytes served as unstimulated negative control.

5.6 Analysis of pERK1/2(T202/Y204) Expression as a Surrogate Marker for B Cell

Anergy

Cells from fresh peripheral whole blood were prepared as described in Section 5.5. Phospho-

(p)ERK1/2(T202/Y204) was analyzed using Perm III and the antibodies anti-CD3-PB, anti-CD14-APC-

Cy7, anti-CD19-PE-Cy7, anti-CD20-BV510, anti-CD27-APC and anti-pERK1/2(T202/Y204)-AF488. An

isotype control labeled with AF488 (clone MOPC-21) was used to verify the staining. Washed cells

were analyzed using LSR Fortessa flow cytometer and FACS Diva Software. Phospho-

(p)ERK1/2(T202/Y204) MFIs were analyzed in CD27- B cells and CD27+ memory B cells (gating strategy

in Figure 3).

Figure 3: Analysis of intracellular targets in CD27- B cells and CD27+ memory B cells. Lymphocytes and single cells were

identified upon their properties in SSC versus FSC scatter (upper left panel). Doublets were excluded (two upper mid panels).

CD14+ (upper right panel) and CD3+ (lower left panel) cells were excluded. B cells were identified upon their expression of CD19

(lower mid panel). CD27- B cells and CD27+ memory B cells were identified upon their characteristic expression of CD20 and

CD27 (lower right panel).

5.7 Isolation of Peripheral Blood Mononuclear Cells (PBMCs) from Human Blood

Samples

PBMCs were isolated from fresh whole blood using density gradient centrifugation. Therefore, whole

blood (10 – 25 ml) was diluted with PBS up to a total volume of 30 ml, layered on 15 ml Ficoll reagent

and centrifuged (20 min, 840 xg, RT, without brake). The upper layer (plasma) was drawn off and

discarded. PBMCs were transferred from the interphase into a new tube and washed with 50 ml MACS

buffer (4 °C) for short term stimulation or PBS (RT) for in vitro culture and centrifuged (400 xg, 10 min).

Cells were filtrated through a 30 µm cell strainer and washed with MACS buffer or PBS accordingly.

For short-term anti-IgG/IGM stimulation (phospho-kinetics) and co-stimulation experiments cells were

suspended in RPMI. For CFSE staining and subsequent long-term in vitro culture cells were suspended

with PBS in appropriate concentrations.

5.8 Isolation of Mononuclear Cells (MNCs) from Human Spleen, Tonsil and Parotid

MNCs were isolated from human spleen, tonsil and parotid as previously described [249]. Therefore,

fresh tissue (spleen, tonsil or parotid) was minced into small pieces with a scalpel, transferred into PBS

(RT) and intensely shaken for 1 min. Then, the supernatant was filtered through a cell strainer (70 µm)

and the procedure was repeated two more times with fresh PBS. The filtrates were pooled and layered

on 15 ml Ficoll reagent. Centrifugation and isolation of MNCs was done as described for PBMC isolation

(Section 5.7). Cells were washed with MACS buffer (4 °C) and treated with erythrocytes lysis buffer

(10 min, on ice), centrifuged (400 xg, 10 min, 4 °C), suspended in MACS buffer and centrifuged again

(400 xg, 10 min, 4 °C). Isolated cells were suspended in freezing medium (2 ∙ 107 cells/ml) and slowly

cooled down to -80 °C using a CoolCell freezing container (Biozym). Cells were quickly thawed at the

day of the experiment in 50 ml RPMI (37 °C) and washed two times with RPMI (400 xg, 10 min, RT).

Prior to the second washing step, cells were filtrated (30 µm). Finally, cells (1 ∙ 106) were suspended in

100 µl RPMI for further anti-IgG/IgM short-term stimulation experiments.

5.9 Analysis of Ex Vivo PTP and PSP Activities within CD19+ B Cell and CD3+

T Cells

Data and method are published [244]. Experiments and analysis were carried out by Franziska

Szelinski (PhD student, AG Dörner, Charité – Universitätsmedizin Berlin). Briefly, B and T cell

enrichment from PBMCs was performed using human B cell kit II or human Pan T cell kit (Miltenyi

Biotec) for magnetic cell sorting according to the manufacturer’s protocols. B and T cell purities were

checked by flow cytometry and cell suspensions with more than 82 % purity were used for further

experiments. Purified cells were lysed using Halt Protease Inhibitor Cocktail (1 % in Pierce IP Lysis

Buffer; Thermo Fisher; 30 min on ice) and analyzed using a commercial PTP/PSP activity kit (Promega

Corporation, Madison, Wisconsin., United States) as previously described [250]. Phosphatase activity

was quantified by the release of free phosphate from the PTP and PSP-specific substrates

Tyr PP1/Tyr PP2 and Ser/Thr PP, respectively. Absolute concentrations were assessed from standard

dilution series. Assay specificity was ensured by using the inhibitors monovanadate (PTP inhibitor;

10 mM) and sodium fluoride (PSP inhibitor, 10 – 20 mM) (both Sigma-Aldrich). Cell lysates were

analyzed at 600 nm using a Spectramax Plus 384 micro plate reader (Molecular Devices, San Jose,

CA. USA).

5.10 Analysis of CD22/SHP-1 Co-Localization in CD19+ B Cells

Data and method are published [244]. Experiments and analysis were carried out by Dr. Eva

Schrezenmeier (MD, AG Dörner, Charité – Universitätsmedizin Berlin). B cells were purified from

PBMCs as described in Section 5.9. Cells were suspended in 100 µl RPMI (2 ∙ 105 cells), equilibrated

(1 h, 37 °C), stimulated with anti-CD22 F(ab’)2 epratuzumab-A488 (10 μg/ml) (UCB Pharma, Slough,

United Kingdom) or left unstimulated, fixed and permeabilized as described in Section 5.5. Cells were

stained with mouse anti-human-SHP-1 (BD Bioscience), goat anti-human-IgG/IgM (Jackson

ImmunoResearch) and for unstimulated control with anti-CD22 F(ab’)2 epratuzumab-A488. Washed

cells were stained with the secondary antibodies donkey anti-mouse-rhodamine red-X (RRX) and

donkey anti-goat-A647 (Jackson ImmunoResearch). Finally, cells were centrifuged onto slides and

covered with Vectashield HardSet mounting medium containing DAPI (Vector Laboratories, USA) to

stain the nucleus. Co-localization/fluorescence overlap of SHP-1/CD22 was evaluated (0 = no co-

localization, 1 = all pixels co-localized) using a Nikon A1-Rsi confocal microscope and NIS Elements C

imaging software (Nikon, Tokyo, Japan).

5.11 Functional Analysis of BCR Associated Signaling Kinases Upon Anti-IgG/IgM

Stimulation

The functional analysis of the BCR-associated signaling molecules Syk, Btk and Akt was carried out

using freshly isolated PBMCs or thawed MNCs (1 ∙ 106 cells). Cells were rested for 1 h at 37 °C in

100 µl RPMI and then stimulated with 100 µl anti-IgG/IgM F(ab’)2 (cfinal see Table 8) for 2, 5, 8, 15 and

30 min. An additional RPMI control served as control at baseline (0 min). The stimulation was stopped

by adding 1 ml pre-warmed (37 °C) Lys/Fix buffer. Lysis, fixation, permeabilization and staining were

performed as described above (Section 5.5). Cells were stained with anti-CD3-PB, anti-CD14-PB, anti-

CD19-PE-Cy7, anti-CD20-PerCp-Cy5.5, anti-CD27-APC and the combinations anti-Syk-FITC/anti-

pSyk(Y352)-PE, anti-Btk-PE/anti-pBtk(Y223)-FITC and anti-Syk/anti-pAkt(S473)-PE for analysis of Syk,

Btk and Akt, respectively. In some pilot experiments cells were stimulated for 5 min with anti-IgG/IgM

F(ab’)2 or H2O2 (3 % in RPMI) as positive staining control and stained with anti-pPI3K

p85(Y467)/p55(Y199)-AF488, anti-PI3CD(Y524)-AF488 or anti-pSHP-1(Y564)-AF488. Flow cytometry

analysis was performed using a FACSCanto II flow cytometer and FACS Diva software. MFIs were

used to assess phosphorylation intensity of Akt(S473), Btk(Y223), PI3CD(Y524), PI3K p85(Y467)/p55(Y199),

SHP-1(Y564) and Syk(Y352) in CD27- B cells and CD27+ memory B cells (gating strategy is show in

Figure 2).

5.12 Anti-IgG/IgM Induced Syk(Y352) Phosphorylation Upon In Vitro Pre-Incubation

with Cytokines or CpG

Isolated PBMCs (1 ∙ 106 cells) were incubated with recombinant human IFNα (100 ng/ml), IFNγ

(100 ng/ml), IL-21 (20 ng/mL) or combinations of IFNα or IFNγ with IL-21; IL-2 (20 ng/ml), IL-6

(20 ng/ml), IL-10 (20 ng/ml) or CpG (500 ng/ml) with and without IL-4 (20 ng/ml) or IL-21 in a 96-well

plate. After incubation (48 h, 37 °C, 5 % CO2) cells were harvested, washed with pre-warmed (37 °C)

RPMI and centrifuged (310 xg, RT). BCR stimulation was conducted as described above

(Section 5.11) for 5 min with anti-IgG/IgM F(ab’)2 or RPMI as unstimulated control. Permeabilized cells

(Perm II) were stained with anti-CD3-PB, anti-CD14-APC-Cy7, anti-CD19-PE-Cy7, anti-CD20-BV510,

anti-CD27-APC, anti-Syk-FITC and anti-pSyk(Y352)-PE. Analysis was done using LSR Fortessa flow

cytometer and FACS Diva Software. The MFI of pSyk(Y352) was analyzed from CD27- B cells and

CD27+ memory B cells (gating strategy in Figure 3).

5.13 Chronic BCR and TLR9 In Vitro Stimulation

For chronic BCR and TLR9 stimulation experiments, cells were pre-incubated with anti-IgG/IgM

(2 µg/ml), CpG (500 ng/ml) or RPMI for 24 h, 48 h or 72 h (37 °C, 5 % CO2), washed with pre-warmed

(37 °C) RPMI and subsequently stimulated with anti-IgG/IgM or RPMI as a control for 5 min as

described above (Section 5.11). Permeabilized cells (Perm II) were stained with anti-CD3-PB, anti-

CD14-APC-Cy7, anti-CD19-PE-Cy7, anti-CD20-BV510, anti-CD27-APC, anti-Syk-FITC and anti-

pSyk(Y352)-PE. The MFI of pSyk(Y352) was analyzed from CD27- B cells and CD27+ memory B cells

using FACS Canto II flow cytometer and FACS Diva Software (gating strategy in Figure 2).

5.14 CD40 In Vitro Co-Stimulation Strategies

The CD40 receptor requires stimulation by CD40L multimers for optimal signaling [251]. Therefore,

cross-linking of CD40 is required for optimal stimulation. Stimulation with soluble (s)CD40L might be

insufficient. Thus, three different strategies were approached for the optimal stimulation of CD40: (i) an

anti-CD40 antibody coated on a micro-well plate, (ii) a co-culturing system with mouse fibroblast cells

expressing human (h)CD40L and (iii) a cross-linking kit containing sCD40L and anti-CD40L cross-

linking antibody.

5.14.1 B Cell Co-Stimulation by Anti-CD40 Coating

Plate (96-well microplate) coating was performed with 100 µl anti-CD40 antibody (clone G28-5) (0.1, 1,

5, 10 or 100 µg/ml in PBS). PBS only was used as uncoated control. After incubation (2 h, 37 °C) the

plate was washed two times with 200 µL PBS and loaded with PBMCs (1 ∙ 106 cells per well) in 100 µl

RPMI. Cells were incubated (48 h, 37 °C, 5 % CO2), harvested, washed with pre-warmed (37 °C) RPMI

and centrifuged (310 xg, RT). BCR stimulation was conducted as described above (Section 5.11) for

5 min with anti-IgG/IgM F(ab’)2 or RPMI as unstimulated control. Permeabilized cells (Perm II) were

stained with anti-CD3-PB, anti-CD14-APC-Cy7, anti-CD19-PE-Cy7, anti-CD20-BV510, anti-CD27-

APC, anti-Syk-FITC and anti-pSyk(Y352)-PE. Analyses was performed using an LSR Fortessa flow

cytometer and FACS Diva Software. The MFI of pSyk(Y352) was analyzed from CD27- B cells and

CD27+ memory B cells (gating strategy in Figure 3).

5.14.2 Co-Culturing System Using hCD40L Expressing Mouse Fibroblast Cell Line

5.14.2.1 Thawing, Culturing and Passaging of L Cells

L cells with and without hCD40L expression were quickly thawed in 50 ml complete medium, washed

once with complete medium, centrifuged (350 xg, 10 min, RT) and cultured (37 °C, 5 % CO2). Cells

were passaged at approximately 80 % confluence. Therefore, the medium was discarded, and cells

were detached using EDTA containing MACS buffer (5 min, 37 °C). Cells were washed with complete

medium, centrifuged (350 xg, 10 min, RT) and seeded at a dilution of 1:10. Cells were cultured in

75 cm² cell culture flasks for maintenance and expansion of the cell line. For the co-culturing

experiment, cells were seeded into 24-well flat-bottom cell culture plates and cultured to 80 %

confluence.

5.14.2.2 Attenuation of L Cell Proliferation

L cell proliferation was attenuated after irradiation using Gammacell® 40 Exactor radiation source. After

irradiation the medium was discarded. Attenuation of proliferation was tested using CFSE staining.

Therefore, CFSE (37 °C, 5 µM in PBS) was added to the cells and incubated (20 min, 37 °C).

Afterwards, the cells were washed twice with complete medium and incubated (10 min) with fresh

complete medium. Medium was exchanged with fresh complete medium and cells were incubated

(48 h, 37 °C, 5 % CO2). Medium was removed; cells were washed with PBS and detached using MACS

buffer (10 min, 37 °C). Cells were washed and stained with anti-CD40-PE (4 °C, 15 min). Washed cells

were analyzed using FACS Canto II flow cytometer and FACS Diva software. Dead cells were excluded

using DAPI staining (900 nM).

5.14.2.3 Co-Culturing of Transfectant Cells with PBMCs

Irradiated L cells with and without hCD40L expression were layered with PBMCs (5 ∙ 106 cells per well)

and incubated with 500 µl RPMI (48 h, 37 °C, 5 % CO2). PBMCs were harvested, washed with pre-

warmed (37 °C) RPMI (310 xg, RT) and anti-IgG/IgM stimulation (5 min, 37 °C) was conducted as

described previously (Section 5.11). Permeabilization, staining and analysis of pSyk(Y352) were

performed as described above (Section 5.14.1).

5.14.3 Co-Stimulation Using a CD40L Cross-Linking Kit

CD40L cross-linking kit was prepared according to the manufacture’s protocol. Briefly, lyophilized

CD40L was suspended in H2O (0.5 mg/ml). CD40L and the cross-linking antibody were incubated in

equivalent volumes with complete medium 30 min prior to use (RT). Finally, isolated PBMCs

(1 ∙ 106 cells) were incubated with cross-linked CD40L (0.5 µg/ml) in a 96-well plate. In some

experiments IL-4 (20 ng/ml) or IL-21 (20 ng/ml) were added to the culture. After incubation (48 h, 37 °C,

5 % CO2) cells were harvested and treated as previously described (Section 5.14.1).

5.15 Analysis of CD19+ B Cell In Vitro Proliferation Using CFSE Staining

For cell proliferation analysis upon B cell stimulation, PBMCs (2 ∙ 106 cells/ml in PBS) were stained with

5 µM CFSE (4 min, 37 °C). After staining, cells were washed once with PBS and incubated in 10 ml

RPMI for 30 min at 37 °C. Cells were washed with complete medium before stimulation.

5.16 In Vitro Differentiation of B Cells into Antibody Secreting Cells (ASCs)

PBMCs with and without previous CFSE staining (Section 5.15) were seeded in a 96-well microtiter

plate (100 µl, 106 cells), incubated (1 h, 37 °C) and subsequently stimulated with CpG (0.5 µg/ml) or a

combination of CpG (0.5 µg/ml) with anti-IgG/IgM antibody (2 µg/ml) for 5 days (37 °C, 5 % CO2) in

complete medium. For B cell proliferation IL-2 (20 ng/ml) and IL-10 (20 ng/ml) and for co-stimulation

experiments cross-linked CD40L (500 ng/ml), was added to the cells. After stimulation, cells were

washed with MACS buffer and stained with anti-CD3-PB, anti-CD14-PB, anti-CD19-PE-Cy7, anti-

CD20-BV510, anti-CD27-APC and anti-CD38-APC-Cy7 (15 min, 4 °C). After washing (2 ml MACS

buffer, 310 xg, 5 min, 4 °C), counting beads were added to the samples without CFSE staining to

assess absolute cell concentrations. Before flow cytometry analysis, DAPI (900 nM) was added to

exclude dead cells. Cells were analyzed using a FACSCanto II flow cytometer. The gating was done

as shown in Figure 4.

Figure 4: Analysis of CD19+ B cells after in vitro stimulation (gating strategy). Counting beads (red) were identified upon

their characteristics in FSC vs. SSC scatter (left panel) and their high fluorescence in PerCp-Cy5.5 and AmCyan (upper panel).

Lymphocytes and single cells were identified upon SSC versus FSC gating (left panel). Doublets (lower left panel), CD14+, CD3+

and dead cells (DAPI+) cells (lower mid panel) were excluded. B cells (black) were identified upon their CD19 expression (lower

right panel).

5.17 Cytokine Quantification in Human Sera Using BioPlex Technology

Human serum samples were collected at the day of the respective experiment and stored (-20 °C) until

further analysis. Thawed serum samples (450 µl) were transferred into HRP blocking tubes to prevent

cross-reactivity of the assay with RF in human samples [252, 253]. Samples were centrifuged

(12,000 xg, 10 min, 4 °C) and the supernatants were used for subsequent analysis. The following

cytokines were analyzed using the Bio-Plex Pro™ Human Cytokine 27-plex Assay: IL-1b, IL-1Ra, IL-2,

IL-4, IL-5, IL-6, IL-7,IL-8,IL-9, IL-10, IL12(p70), IL-13, IL-15, IL-17, eotaxin, fibroblast growth factor 2

(FGF basic), granulocyte colony-stimulating factor (G-CSF), GM-CSF, IFNγ, C-X-C motif chemokine

10 (IP-10), C-C motif chemokine 2 (MCP-1 or MCAF), macrophage inflammatory protein 1-alpha (MIP-

1a), MIP-1b, platelet-derived growth factor subunit B (PDGF bb), C-C motif chemokine 5 (RANTES),

TNFα and vascular endothelial growth factor A (VEGF). Bio-Plex Pro Human Th17 Cytokine IL-21 was

analyzed as single assay. All reagents and buffer were provided with the kit.

Lyophilized standards were dissolved in 250 µL standard diluent and incubated (30 min, on ice). The

dissolved standards were split into 3 aliquots (each 70 µL) and frozen for long term storage (-20 °C).

At the day of the experiment 64 µL of thawed standard solution was diluted with 136 µl standard diluent.

Standard curve was prepared by 8-times 1:40 dilution. 27-plex or IL-21 beads were prepared by 1:40

dilution with assay buffer and incubation prior to use (20 min, RT). The filter plate was moistened with

100 µl assay buffer per well and vacuumed (between -1 to -3 mmHg) using a vacuum station. Then,

the plate was prepared with 50 µl diluted beads per well, vacuumed, washed two times with 100 µl

wash buffer and vacuumed. Samples, standards and blank (each 50 µl) were pipetted on the plate in

technical duplicates and shortly incubated at high rpm (30 sec, 1100 rpm, RT) and then at low rpm

(30 min, 300 rpm, RT) in the dark. Detection antibody was prepared at a 1:40 dilution with antibody

diluent prior to use (20 min, RT). After incubation, the plate was vacuumed and washed three times

with 100 ml wash buffer. Diluted detection antibody (25 µl) was added to the plate and incubated as

described above. Streptavidin-PE was diluted with assay buffer (1:100) and incubated prior to use

(10 min, RT). After incubation, the plate was evacuated, washed three times with wash buffer (100 ml),

streptavidin-PE (50 µl) was added to the wells and the plate was incubated as described above. After

incubation, the plate was washed three times with wash buffer (100 µl). After evacuation, assay buffer

(100 µl) was added and then plate was incubated under shaking as described above 10 min before

reading. Samples were analyzed using Bio-Plex-Systems. Calibration was performed using BioPlex

Calibration Kit prior to the analysis. The running protocol was set to 50 beads per region, 100 regions

bead map, sample size 50 µl and DD gates were set to 5,000 (low). Absolute concentrations were

assessed according to standard dilution curves (Supplementary Figure 1)

5.18 Meta-Analysis of Differentially Methylated CpGs in SLE, RA and pSS

This meta-analysis of methylation data from SLE, RA and pSS CD19+ B cells was carried out in

cooperation with Prof. Jörn Walter (Department of Genetics and Epigenetics, Saarland University,

Saarbrücken, Germany). Data on SLE and RA patients were collected from previously published

studies [254-256]. Methylation data of pSS patients were kindly provided by Prof. Lars Rönnblom

(Department of Medical Sciences, Rheumatology and Science for Life Laboratory, Uppsala University,

Uppsala, Sweden). The data were processed as published [244]. Briefly, Idat files of the Illumina

Infinium HumanMethylation450 BeadChip data were processed with RnBeads (v1.6.1) [254-256]. Next,

data was aligned to hg19 reference genome, single nucleotide polymorphisms (SNPs) and sex

chromosomes were excluded from further processing. A bead count cutoff of ≥ 10 and a greedy cut

p-value cutoff of ≤ 0.01 was set to filter the data for high quality. The data was normalized using the

Swan method. Finally, demethylated CpGs were defined as CpGs with ≥ 5 % DNA methylation

difference and p-value ≤ 0.01.

5.19 Differential Gene Expression Analysis of RNA-Sequencing Data

Data analysis was conducted in cooperation with Dr. Peter E. Lipsky (RILITE Research Institute,

Charlottesville, Virginia, United States) as published [244] (Section 5.19.1 and Section 5.19.2). The

experimental procedure of CD40L/IL-4R stimulation was performed by Franziska Szelinski (PhD

student, AG Dörner, Charité – Universitätsmedizin Berlin) (Section 5.19.2).

5.19.1 Analysis of Differential Phosphatase Expression from Publicly Available CD20+,

CD4+ and CD8+ SLE Cells and CD19+ Multiple Sclerosis (MS) RNA-Sequencing

Data Sets

Data were derived from publicly available datasets: CD20+ B Cells from SLE patients and HDs (6 SLE,

7 HDs; GSE4588; https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE4588), CD19+ B cells

from MS patients and HDs (10 MS, 10 HDs; GSE117935,

https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi), CD4+ T cells from SLE patients and HDs (53 SLE,

41 HDs; E-MTAB-2713, https://www.ebi.ac.uk/arrayexpress/experiments/E-MTAB-2713/) and CD8+

T cells from SLE patients and HDs (22 SLE, 31 HDs; E-MTAB-2713,

https://www.ebi.ac.uk/arrayexpress/experiments/E-MTAB-2713/). Differential expression was done for

each dataset of SLE patients and HDs. Guanine cytosine robust multi-array analysis (GCRMA)

normalized expression values were variance corrected using local empirical Bayesian shrinkage before

calculation of differential expression using the ebayes function in the open source package

BioConductor LIMMA package (https://www.bioconductor.org/packages/release/bioc/html/limma.html).

Resulting p-values were adjusted for multiple hypothesis testing and filtered to retain differentially

expressed probes with an false discovery rate (FDR) < 0.2 [257].

5.19.2 Analysis of Differential Phosphatase Expression from CD19+ SLE Cells After

CD40L/IL-4R Stimulation

Isolated PBMCs from two SLE and one HD were cultured in the presence of CD40L (0.5 µg/ml) and

IL-4 (20 ng/ml) or RPMI as a control as described in Section 5.14.3 for 48 h. CD19+ B cells were

isolated for RNA-sequencing analysis as described in Section 5.9. Three technical replicates were

included for each cohort and time point; files were obtained from FASTQC. FASTQC, Trimmomatic,

STAR, Sambamba, and FeatureCounts were done separately. After careful examination of the principal

component analysis (PCA) plots, three technical replicates of each cohort and condition were averaged

into one and then used to perform relative gene expression. After FASTQC quality control analysis,

Trimmomatic was used to cut adapter sequences, low-quality reads, and the first 14 reads of each

sequence due to non-random primer bias. Reads were aligned to the human reference genome hg38

in STAR, and the ‘.sam’ files were converted to sorted ‘.bam’ files using Sambamba. Relative

differentially expressed counts were generated in FeatureCounts. FastQC, Trimmomatic, STAR,

Sambamba, and the FeatureCounts programs are all free, open source programs (web addresses see

Table 12). RNA-Sequencing data are available under PRJNA564980

(https://www.ncbi.nlm.nih.gov/bioproject/PRJNA564980).

Table 12: Web addresses of open source programs used for RNA-Sequencing analysis

Open source program

Web address

FastQC

https://www.bioinformatics.babraham.ac.uk/projects/fastqc/

Trimmomatic

http://www.usadellab.org/cms/?page=trimmomatic

STAR

https://github.com/alexdobin/STAR

http://labshare.cshl.edu/shares/gingeraslab/www-

data/dobin/STAR/STAR.posix/doc/STARmanual.pdf

Sambamba

http://lomereiter.github.io/sambamba/

FeatureCounts

http://subread.sourceforge.net/

5.20 Data Analysis and Statistics

Flow cytometry data were analyzed with FlowJo 10.4.2. BioPlex raw data were analyzed using BioPlex

Manager v4.1.1. Statistical analysis was performed with GraphPad Prism v5.04. For all data sets a

Gaussian distribution was assumed. For the comparison of two groups unpaired t-test and for paired

analysis paired t-test was applied. When multiple groups were compared, one-way analysis of variance

(ANOVA) with Dunnett’s test for multiple comparisons (DMCT) was applied. For the comparison of

time-dependent kinetics and multiple groups two-way ANOVA with Bonferroni test for multiple

comparisons (BMCT) was used.

6 Results

6.1 Increased PTP and PSP Activities in SLE and Increased Co-Localization of

CD22 with SHP-1 in SLE, RA and pSS CD19+ B Cells

The strength of BCR downstream signaling is transmitted by the activity of signaling kinases such as

Syk. Kinase activity is indicated by phosphorylation of specific tyrosine, serine or threonine sites. This

phosphorylation is counter balanced by the activity of tyrosine- or serine/threonine-specific

phosphatases [95, 112]. SHP-1 recruitment to CD22 provides an essential negative feedback loop to

counterbalance Syk tyrosine phosphorylation [95, 105, 106, 112]. Increased global PTP activities in

CD19+ B cells, CD22 expression and phosphorylation in CD27- B cells from SLE patients contribute to

reduced Syk phosphorylation in SLE [14]. To analyze whether there are similar signaling abnormalities

in other autoimmune diseases, such as RA and pSS, PTP and PSP activities were analyzed in SLE,

RA and pSS peripheral CD19+ B cells and compared to HDs (Figure 5a, b). Additionally, the

localization of the PTP SHP-1 in relation to the negative regulator CD22 with and without anti-CD22

stimulation was analyzed in peripheral CD19+ B cells from SLE, RA, pSS and HDs (Figure 5c, d).

PTP activities against both PTP-specific substrates (TyrPP1 and TyrPP2) were statistically significant

and specifically increased in SLE CD19+ B cells compared to HDs (median free phosphate in HD vs.

SLE: 1,030 vs. 3,277 pmol for TyrPP1 and 2,257 vs. 5,339 ppm for TyrPP2) (Figure 5a). Also, PSP

activity towards Ser/Thr PP substrate was significantly and particularly increased in SLE CD19+ B cells

compared to HDs (median free phosphate in HD vs. SLE: 417 vs. 1,081 ppm) (Figure 5b). Specificity

of the assay was validated by adding 10 mM monovanadate for blocking PTP activities and 10 – 20 mM

sodium fluoride for blocking PSP activities. The same assay was applied on CD3+ T cells from SLE,

RA, pSS and HDs to proof B cell specificity of the results (Supplementary Figure 2). Notably, PTP as

well as PSP activities in SLE, RA and pSS CD3+ T cells were comparable to HDs.

Of note, baseline co-localization of CD22 receptor and SHP-1 was significantly increased in SLE, RA

and pSS CD19+ B cells compared to HDs with co-localization coefficients of 0.80 (SLE), 0.69 (RA) and

0.68 (pSS) compared to 0.55 (HD) (Figure 5d). Anti-CD22 stimulation significantly increased

CD22/SHP-1 colocalization in RA to 0.84, pSS to 0.79 and HDs to 0.68 compared to unstimulated, but

this was not seen for SLE. Noteworthy, CD22/SHP-1 colocalization in SLE CD19+ B cells at baseline

was as high as under stimulated conditions (0,80 and 0,81 at baseline and anti-CD22 stimulation,

respectively) in all other donors and could not be further increased upon anti-CD22 stimulation.

Figure 5: Enhanced PTP and PSP activities in SLE B cells and enhanced baseline colocalization of SHP-1 with CD22 in

B cells from patients with SLE, RA and pSS. Baseline activities of PTPs and PSPs as well as colocalization of SHP-1 with

CD22 was analyzed at baseline and upon anti-CD22 stimulation in SLE, RA, pSS and HD CD19+ B cells. (a) Activities of PTPs

(n(HD/SLE/RA/pSS) = 22/8/4/13) and (b) PSPs (n(HD/SLE/RA/pSS) = 19/8/5/10) in HD (grey), SLE (red), RA (blue) and pSS

(green) CD19+ B cells. Box whisker plots represent median (line), mean (plus) and the range from minimum to maximum. (c)

Colocalization of SHP-1 (red) with CD22 (green) on HD, SLE, RA and pSS CD19+ B cells (representative fluorescence microcopy

pictures). The nucleus (blue) was stained with DAPI. (d) Scatter dot plot of colocalization coefficients of HD (black), SLE (red),

RA (blue) and pSS (green) CD19+ B cells (n(HD/SLE/RA/pSS) = 2/2/2/2). Each dot represents a cell and the lines indicate the

mean (one-way ANOVA with DMCT; ** p ≤ 0.01, *** p ≤ 0.001, **** p < 0.0001).

SHP-1/CD22 co-localization at baseline is increased in CD19+ B cells from SLE, RA and pSS patients

compared to HDs. This co-localization could be increased in HD, RA and pSS CD19+ B cells upon anti-

CD22-stimulation, but not in SLE CD19+ B cells. Thus, CD19+ B cells from SLE patients displayed

already maximal SHP-1/CD22 co-localization together with increased PTP and PSP activities at

baseline.

6.2 Comparable Syk, Btk, PLCγ2 and Akt Baseline Expression and Phosphorylation

Between SLE, pSS, RA and HDs in CD27- B Cells and CD27+ Memory B Cells

Phosphorylation of Syk, Btk, PLCγ2 and Akt at their activation sites Syk(Y352), Btk(Y223), PLCγ2(Y759)

and Akt(S473), respectively, are regulated by PTPs (Syk, Btk and PLCγ2) or PSPs (Akt) [258]. Therefore,

Increased PTP and PSP activities and co-localization of CD22 with SHP-1 (Section 6.1) may impact

the baseline phosphorylation of BCR downstream signaling of those molecules. Hence, protein

expression and phosphorylation at their corresponding activation sites were analyzed in SLE, RA, pSS

and HD peripheral B cells. To account for subset-specific signaling properties, CD19+ B cells were

subdivided into conventional CD27- B cells and CD27+ memory B cells [14, 100].

Overall, Syk and pSyk(Y352) expression was similar among SLE, RA, pSS and HDs for CD27- B cells

and CD27+ memory B cells with the exemption of Syk expression in pSS CD27- B cells compared to

HDs (Figure 6a). In pSS, Syk expression in CD27-, but not CD27+ B cells, was significantly higher

compared to HDs (mean MFI 3,125 in pSS vs. 2,429 in HD). In general, Syk and pSyk(Y352) expression

were significantly higher in CD27+ memory than in CD27- B cells for HDs, RA and pSS patients and

tend to be higher for pSyk(Y352) in SLE patients (p = 0.0762). As an example, HD CD27- B cells and

CD27+ memory B cells exhibited mean MFIs of 2,492 and 4,181, respectively. Mean MFIs of pSyk(Y352)

were 663 in CD27- B cells and 932 in CD27+ memory B cells from HDs.

Btk and pBtk(Y223) MFIs were similar among patients and HDs in CD27- B cells and CD27+ memory

B cells (Figure 6b). Exemplarily, mean MFIs of HD CD27- B cells and CD27+ memory B cells were

1,154 and 1,309 for Btk as well as 2,334 and 3,382 for pBtk(Y223), respectively. Expression of Btk was

comparable between CD27- B cells and CD27+ memory B cells in SLE, RA and pSS. However, Btk

expression in CD27+ B cells from HDs was slightly, but significantly higher compared to CD27- B cells.

Phospho-Btk(Y223) in CD27+ memory B cells showed a tendency of higher expression in all groups

compared to CD27- B cells, with significantly higher MFIs in HDs and pSS patients.

Similar PLCγ2 and pPLCγ2(Y759) expressions were found among patients and HDs (Figure 6c). HD

CD27- B cells exhibited mean MFIs of 2,222 for PLCγ2 and 375 for pPLCγ2(Y759), whereas CD27+

memory B cells displayed mean MFIs of 3,230 for PLCγ2 and 595 for pPLCγ2(Y759). As seen for Syk

and pSyk(Y352), PLCγ2 expression was significantly higher in CD27+ memory B cells than compared to

CD27- B cells from HDs, SLE and pSS patients; there was a trend of somewhat higher expression

levels in RA patients (mean MFIs of 2,716 vs. 3,262 in CD27- B cells vs. CD27+ memory B cells from

RA patients, respectively). Phospho-PLCγ2(Y759) was significantly increased in HDs and tended to be

increased in SLE, RA and pSS CD27+ memory B cells compared to CD27- B cells. In detail,

pPLCγ2(Y759) mean MFIs were 465 vs. 584 (SLE), 434 vs. 511 (RA) and 500 vs. 629 (pSS) in CD27-

B cells vs. CD27+ memory B cells, respectively.

Comparable Akt1 and pAkt(S473) expression was observed among CD27- B cells and CD27+ memory

B cells from all donor groups with the exemption of pSS (Figure 6d). For example, HD mean Akt1 MFIs

were 352 vs. 410 and mean pAkt(S473) MFIs were 230 vs. 265 in CD27- B cells vs. CD27+ memory

B cells, respectively. In pSS patients, Akt1 expression was found to be significantly higher in CD27+

memory B cells (mean MFI 261) compared to CD27- B cells (mean MFI 232).

Figure 6: Comparable baseline expression and phosphorylation of BCR downstream kinases in SLE, RA and pSS

patients compared to HDs. Baseline (a) Syk and pSyk(Y352) (n(HD/SLE/RA/pSS) = 32/19/14/13), (b) Btk and pBtk(Y223)

(n(HD/SLE/RA/pSS) = 30/16/11/15), (c) PLCγ2 and pPLCγ2(Y759) (n(HD/SLE/RA/pSS) = 25/15/6/11) and (d) Akt and pAkt(S473)

(n(HD/SLE/RA/pSS) = 30/14/14/13) expression and phosphorylation was analyzed in CD27- B cells (dots) and CD27+ memory

(circles) B cells from unstimulated HDs (black), SLE (red), RA (blue) and pSS (green) patients whole blood samples.

Representative histograms show the expression of the indicated kinase in CD27- B cells (solid line) and CD27+ memory B cells

(dashed line). Negative controls (grey areas) are defined by (a, b, c) CD3+ lymphocytes or (d) isotype control. The horizontal line

represents the mean ± standard deviation (SD) (one-way ANOVA with DMCT; t-test; * p ≤ 0.05, ** p ≤ 0.01, **** p ≤ 0.0001).

Taken together, baseline expression and phosphorylation of Syk, Btk, PLCγ2 and Akt in SLE, RA and

pSS peripheral CD27- B cells and CD27+ memory B cells are comparable to HDs. Thus, indicating that

tonic signaling is not affected by the observed increase in CD22/SHP-1 colocalization in SLE, RA and

pSS and increased PTP and PSP activities in SLE (Section 6.1). Notably, baseline expression of Syk

and PLCγ2 protein and phosphorylation of Syk(Y352) and PLCγ2(Y759) was characteristically increased

in CD27+ memory versus CD27- B cells.

6.3 Reduced Tyrosine Phosphorylation of Syk(Y352) and Btk(Y223) Upon Anti-

IgG/IgM Stimulation in B Cells From SLE, RA and pSS Patients

Impaired functional BCR signal due to increased PTP activities was reported in SLE B cells, which is

characterized by reduced Syk(Y352) phosphorylation after BCR stimulation [14]. Increased PTP

activities were not observed in RA and pSS, but increased baseline co-localization of CD22 with the

PTP SHP-1 (Section 6.1). To analyze whether pSS and RA share the same signaling abnormality with

SLE, phosphorylation kinetics of Syk(Y352) were analyzed in peripheral CD27- B cells and CD27+

memory B cells after IgG/IgM stimulation in autoimmune disease B cells (Figure 7). Downstream

progression of the signal was analyzed by anti-IgG/IGM induced Btk(Y223) phosphorylation kinetics in

SLE, RA, pSS and HD CD27- and CD27+ memory B cells (Figure 8).

Anti-IgG/IgM induced Syk(Y352) phosphorylation kinetics of HD CD27+ memory B cells were generally

increased for all time points analyzed compared to CD27- B cells (Figure 7a, b). Maximum

phosphorylation was reached at 5 min with mean MFIs of 2,906 and 4,273 for HD CD27- B cells and

CD27+ memory B cells, respectively. Syk(Y352) phosphorylation kinetics were significantly reduced in

SLE CD27- B cells (1,753 mean MFI at 5 min) and CD27+ memory B cells (1,803 mean MFI at 5 min)

compared to HDs. Additionally, pSyk(Y352) kinetics were significantly reduced in RA and pSS CD27+

memory B cells compared to HDs with mean MFIs of 2,855 (RA) and 2,901 (pSS) at 5 min. Phospho-

Syk(Y352) kinetics in RA and pSS CD27- B cells were comparable to HDs. In SLE, RA and pSS

pSyk(Y352) kinetics completely lack a differentiation between CD27- B cells and CD27+ memory B cells.

Figure 7: Reduced anti-IgG/IgM induced Syk(Y352) phosphorylation kinetics in SLE, RA and pSS CD27+ memory B cells

and SLE CD27- B cells. PBMCs from HDs, SLE, RA and pSS patients were stimulated with anti-IgG/IgM F(ab)2 fragments for 0

(RPMI control), 2, 5, 8, 15 and 30 min and Syk(Y352) phosphorylation kinetics were analyzed. (a) Representative pSyk(Y352)

histograms of CD27- B cells (top row) and CD27+ memory B cells (bottom row) were shown for the indicated time points. CD3+

lymphocytes served as negative control (grey areas). (b) Phospho-Syk(Y352) (n(HD/SLE/RA/pSS) = 19/11/11/10) kinetics for HD

(black), SLE (red), RA (blue) and pSS (green) CD27- B cells (solid lines and dots) and CD27+ memory B cells (circles and dashed

lines). Data are represented as mean ± 95 % confidence interval (CI) (two-way ANOVA with BMCT; * p ≤ 0.05, ** p ≤ 0.01,

*** p ≤ 0.001, **** p ≤ 0.0001).

Phospho-Btk(Y223) kinetics were qualitatively comparable to pSyk(Y352) kinetics: Phosphorylation in HD

CD27+ memory B cells was higher than in CD27- B cells for all time points and maximum

phosphorylation was reached at 5 min after anti-IgG/IgM stimulation (Figure 8a, b). Mean pBtk(Y223)

MFIs of HD CD27- B cells and CD27+ memory B cells were 11,036 and 15,613 at 5 min, respectively.

In CD27+ memory B cells pBtk(Y223) kinetics were reduced in SLE (9,271 mean MFI at 5 min), RA

(11,320 mean MFI at 5 min) and pSS (11,590 mean MFI at 5 min) compared to HDs (15,613 mean MFI

at 5 min). Thus, pBtk(Y223) kinetics of CD27+ memory B cells of SLE, RA and pSS patients are

comparable to CD27- B cells of HDs. In addition, Btk(Y223) phosphorylation tend to be reduced in CD27-

B cells from SLE (8,821 mean MFI at 5 min) and RA (9,291 mean MFI at 5 min) patients vs. HDs

(11,036 mean MFI at 5 min).

Figure 8: Reduced anti-IgG/IgM induced Btk(Y223) phosphorylation kinetics in SLE, RA and pSS CD27+ memory B cells.

PBMCs were stimulated with anti-IgG/IgM F(ab)2 fragments for 0 (RPMI control), 2, 5, 8, 15 and 30 min and Btk(Y223)

phosphorylation kinetics were analyzed. (a) Representative histograms of pBtk(Y223) in CD27- B cells (top row) and CD27+

(bottom row) memory B cells from HDs (black), SLE (red), RA (blue) and pSS (green) patients upon the indicated stimulation

time. CD3+ lymphocytes served as negative control (grey area). (b) Phospho-Btk(Y223) (n(HD/SLE/RA/pSS) = 21/10/6/14) kinetics

in CD27- B cells (solid lines and dots) and CD27+ memory B cells (dashed lines and circles) from HDs (black), SLE (red), RA

(blue) and pSS (green) patients. Data are represented as mean ± 95 % CI (two-way ANOVA with BMCT; * p ≤ 0.05, ** p ≤ 0.01,

*** p ≤ 0.001, **** p ≤ 0.0001).

Syk(Y352) phosphorylation kinetics were reduced in SLE peripheral CD27- B cells and CD27+ memory

B cells compared to HDs which is consistent with the previous reports [14]. As a commonalty SLE, RA

and pSS CD27+ memory B cells displayed reduced Syk(Y352) phosphorylation kinetics. Consistent with

this observation, downstream propagation of the BCR signal via Btk(Y223) phosphorylation was also

found to be reduced in SLE, RA and pSS CD27+ memory B cells compared to HDs.

6.4 Anti-IgG/IgM Induced Serine Phosphorylation of Akt(S473) is Increased in SLE

and Comparable to HDs in RA and pSS

Next, it was analyzed whether pSS and RA B cells display the same functional BCR signaling

unbalance, with increased phosphorylation of Akt(S473) after anti-IgG/IgM stimulation, as reported for

SLE [14]. Anti-IgG/IgM induced Akt(S473) phosphorylation kinetics were analyzed in peripheral CD27-

B cells and CD27+ memory B cells from SLE, RA and pSS patients in comparison to HDs.

Akt(S473) phosphorylation kinetics were distinctive between CD27- B cells and CD27+ memory B cells

with higher phosphorylation in CD27+ memory B cells in all donor groups (Figure 9a, b). Maximum

phosphorylation was reached after 8 min in CD27- and CD27+ memory B cells. For example, HD CD27-

B cells and CD27+ memory B cells exhibited mean pAkt(S473) MFIs of 1,037 and 1,405 at 8 min,

respectively. Phospho-Akt(S473) kinetics were increased in SLE CD27- B cells (1,437 mean MFI at

8 min) and CD27+ memory B cells (1,829 mean MFI at 8 min) compared to HDs (Figure 9b). In contrast

to SLE, Akt(S473) phosphorylation kinetics of CD27- B cells and CD27+ memory B cells from RA and

pSS were comparable to HDs at all the time points after anti-IgG/IgM stimulation.

Figure 9: Increased anti-IgG/IgM induced Akt(S473) phosphorylation kinetics in SLE CD27- and CD27+ memory B cells

compared to HDs. PBMCs from HDs and SLE, RA and pSS patients were stimulated with anti-IgG/IgM for 0 (RPMI control), 2,

5, 8, 15 and 30 min and Akt(S473) phosphorylation was analyzed. (a) Representative histograms of CD27- and CD27+ memory

B cells from SLE (red), RA (blue) and pSS (green) patients and HDs (black) upon the indicated stimulation time. CD3+

lymphocytes were used as negative control (grey areas). (b) Phospho-Akt(S473) (n(HD/SLE/RA/pSS) = 29/15/11/10) kinetics for

HDs (black), SLE (red), RA (blue) and pSS (green) CD27- B cells (solid lines and dots) and CD27+ memory B cells (circles and

dashed lines). Data are represented as mean ± 95 % CI (two-way ANOVA with BMCT; * p ≤ 0.05, ** p ≤ 0.01, *** p ≤ 0.001).

Reduced Syk(Y352) and downstream Btk(Y223) phosphorylation kinetics in SLE, RA and pSS

(Section 6.3) did not directly translate into reduced Akt(S473) phosphorylation. Phospho-Akt(S473)

kinetics of RA and pSS CD27- B cells and CD27+ memory B cells were comparable to HDs. Phospho-

Akt(S473) kinetics were increased in SLE CD27- and CD27+ B cells compared to HDs. In contrast to

Syk(Y352) and Btk(Y223) phosphorylation kinetics (Section 6.3), Akt(S473) phosphorylation was

distinctive between CD27- B cells and CD27+ memory B cells with higher phosphorylation in CD27+

memory B cells in autoimmune disease patients compared to HDs.

6.5 Reduced Anti-IgG/IgM Induced Syk(Y352) Phosphorylation in CD27+ Memory

B Cells from ITP Spleens

Circulating B cells of autoimmune patients showed reduced Syk(Y352) phosphorylation upon anti-

IgG/IgM treatment (Section 6.3). To address the question whether tissue resident B cells from

autoimmune patients share the same hyporesponsive phenotype, CD27- B cells and CD27+ memory

B cells from spleens, tonsils and parotid tissue were analyzed for Syk(Y352) phosphorylation after anti-

IgG/IgM stimulation (Figure 10). Spleens were obtained from autoimmune patients with ITP and

patients without autoimmune disease. Tonsils were obtained from patients with chronic tonsillitis. One

parotid was obtained from a pSS patient, and therefore, reflects an actual site of autoimmune

inflammation.

In non-ITP splenic B cells, Syk(Y352) phosphorylation kinetics were qualitatively comparable to

Syk(Y352) phosphorylation kinetics from peripheral blood B cells (Section 6.3). Higher phosphorylation

in CD27+ memory B cells compared to CD27- B cells and maximum phosphorylation at 5 min after anti-

IgG/IgM stimulation was observed (Figure 10a). In detail, mean Syk(Y352) MFIs were 1,788 and 3,823

in CD27- B cells and CD27+ memory B cells, respectively. Phospho-Syk(Y352) kinetics were significantly

reduced in ITP CD27+ memory B cells (2,162 mean MFI at 5 min) compared to non-ITP CD27+ memory

B cells (3,823 mean MFI at 5 min). ITP samples tend to lack the distinction between CD27- B cells and

CD27+ memory B cells (1,459 vs. 2,162 mean MFI at 5 min).

Phospho-Syk(Y352) kinetics in CD27- B cells and CD27+ memory B cells from tonsils (917 vs. 1,591

mean MFIs at 5 min) and pSS parotid (1,041 vs. 1,392 mean MFIs at 5 min) were overall lower

(Figure 10b) compared to non-ITP splenic (1,788 vs. 3,823 mean MFIs at 5 min) (Figure 10a) and HD

peripheral (2,906 vs. 4,273 mean MFIs at 5 min) (Section 6.3) CD27- B cells and CD27+ memory

B cells. Notably, pSyk(Y352) phosphorylation kinetics in CD27- and CD27+ B cells from the pSS parotid

was comparable to the kinetics of CD27- and CD27+ B cells from tonsils.

Figure 10: Reduced anti-IgG/IgM induced Syk(Y352) phosphorylation kinetics in splenic B cells from ITP patients

compared to non-ITP patients. MNCs were isolated from spleens, tonsils and one pSS parotid. Cells were stimulated with anti-

IgG/IgM F(ab)2 for 0 (RPMI control), 2, 5, 8, 15 and 30 min and analyzed for Syk(Y352) phosphorylation. (a) Representative

pSyk(Y352) histograms after 5 min anti-IgG/IgM stimulation (solid line) or unstimulated (filled areas) and Syk(Y352) phosphorylation

kinetics from ITP (pink) and non-autoimmune (grey/black) CD27- B cells (left; solid lines and dots) and CD27+ memory B cells

(right; dashed lines and circles). Each pSyk(Y352) kinetic represents one donor (n(ITP/non-ITP) = 4/7). (b) Representative

pSyk(Y352) histograms and kinetics of CD27- B cells (left; solid lines and dots) and CD27+ memory B cells (right; dashed lines

and circles) from tonsils (grey/black) and pSS parotid (green). Data represent absolute MFIs (two-way ANOVA with BMCT;

* p ≤ 0.05, ** p ≤ 0.01, *** p ≤ 0.001).

These functional analysis of tissue resident B cells revealed that pSyk(Y352) kinetics in CD27- B cells

and CD27+ memory B cells from spleen are comparable to pSyk(Y352) kinetics in peripheral blood

B cells. Moreover, ITP CD27+ memory B cells from spleen displayed reduced Syk(Y352) phosphorylation

kinetics compared to non-ITP CD27+ memory B cells. Overall, B cells from parotid as well as tonsils

displayed lower Syk(Y352) phosphorylation after anti-IgG/IgM stimulation compared to peripheral blood

and splenic B cells. CD27+ memory B cells with reduced Syk(Y352) phosphorylation kinetics are also

present in autoimmune disease tissues.

6.6 Comparable ERK1/2(T202/Y204) Baseline Phosphorylation in B Cells from HDs,

SLE and RA Patients

Reduced BCR responsiveness reflects a functional status of B cells which may be related to B cell

anergy. Recently, increased frequencies of pERK1/2(T202/Y204)+ cells were found among B cells from

patients with type #4 mutated chronic lymphatic leukemia (M-CLL) [259-261]. Type #4 M-CLL patients

predominantly express IGHV4-34/IGKV2-30 Igs whereas the IGHV4-34 gene encodes for intrinsically

autoreactive autoantibodies which are known to be secreted by SLE patients, too. The BCR in type #4

M-CLL is often unresponsive, which may be due to chronic auto-antigen presence. Therefore,

increased pERK1/2(T202/Y204) is thought to be a marker for anergy in type #4 M-CLL. Due to the parallels

in terms of IGHV4-34 expression and unresponsive BCR in SLE (Section 6.3), pERK1/2(T202/Y204)

expression was tested in peripheral CD27- B cells and CD27+ memory B cells as a potential marker for

B cell anergy in a pilot experiment.

For comparability to the aforementioned reports, frequencies of pERK1/2(T202/Y204)+ cells were

analyzed to isotype control as a reference (Figure 11a, b). Frequencies of pERK1/2(T202/Y204)+ cells

ranged between 3 and 77 % (CD27- B cells) as well as 9 and 86 % (CD27+ memory B cells).

Autoimmune disease groups were comparable to HDs with no significant difference between CD27-

B cells and CD27+ memory B cells (Figure 11b).

When MFIs were analyzed, pERK1/2(T202/Y204) was generally higher expressed in CD27+ memory

B cells compared to CD27- B cells, but this was not significantly different for SLE (Figure 11c). In

example, mean pERK1/2(T202/Y204) MFIs of HD CD27- B cells and CD27+ memory B cells was 431 and

610, respectively. However, no significant difference was observed in the expression of

pERK1/2(T202/Y204) between HDs, SLE and RA patients for CD27- B cells and CD27+ memory B cells.

Nevertheless, there is a tendency of reduced pERK1/2(T202/Y204) expression in SLE and RA CD27-

B cells as well as CD27+ memory B cells compared to HDs.

Figure 11: Comparable baseline phosphorylation of ERK1/2(T202/Y204) in SLE, RA and HDs. Baseline ERK(T202/Y204)

phosphorylation was analyzed from unstimulated HD, SLE and RA whole blood samples. (a) Representative histograms of

pERK(T202/Y204) in CD27- B cells (solid line) and CD27+ memory B cells (dashed line) compared to isotype control (grey area).

The horizontal lines indicate the gating on pERK1/2(T202/Y204) positive and negative cells according to isotype control. (b)

Phospho-ERK1/2(T202/Y204)+ cells in HD (black), SLE (red) and RA (blue) CD27- B cells (dots) and CD27+ memory B cells (circles).

(circles). The horizontal lines indicate means ± SD (test; * p ≤ 0.05, ** p ≤ 0.01).

Phospho-ERK1/2(T202/Y204) does not exhibit any difference in frequencies or the MFI between

peripheral CD27- B cells and CD27+ memory B cells from SLE and RA patients compared to HDs.

Moreover, pERK1/2(T202/Y204) MFI tends to be reduced in SLE and RA CD27- B cells and CD27+

memory B cells compared to HDs.

6.7 Reduced Anti-IgG/IgM Induced pSyk(Y352) in SLE, RA and pSS CD27+ Memory

B Cells Does Not Correlate with Siglec-1 or Cytokine Expression

IFNα signature measured by the expression of Siglec-1 (CD169) on CD14+ monocytes is increased in

patients with SLE and extraglandular pSS [193, 194]. This IFNα signature might be a commonality

between these diseases and a potential inducer of the reduced BCR induced pSyk(Y352) signaling

observed in SLE, RA and pSS patients (Section 6.3). To address this hypothesis Siglec-1 expression

was compared between HDs, SLE, RA and pSS patients and correlated with pSyk(Y352) MFIs from

CD27+ memory B cells after 5 min anti-IgG/IgM stimulation (Figure 12).

In line with the literature [193, 194], patients with SLE and pSS express more Siglec-1 on CD14+

monocytes than HDs (Figure 12a). However, on RA CD14+ monocytes, the Siglec-1 expression was

comparable to HDs. Siglec-1 expression did not correlate with pSyk(Y352) in CD27+ memory B cells

after 5 min anti-IgG/IgM stimulation in HDs, SLE, RA and pSS (Figure 12b).

Figure 12: Increased Siglec-1 expression in SLE and pSS does not correlate with pSyk(Y352) phosphorylation at 5 min

of anti-IgG/IgM stimulation. Siglec1 expression was analyzed on CD14+ monocytes from unstimulated HD (black), SLE (red),

RA (blue) and pSS (green) whole blood samples and correlated with pSyk(Y352) in CD27+ memory B cells after 5 min anti-IgG/IgM

stimulation (n(HD/SLE/RA/pSS) = 12/10/10/16). (a) Siglec-1 expression in HDs, SLE, RA and pSS patients. The horizontal lines

represent the mean ± SD (one-way ANOVA with DMCT; * p ≤ 0.05, ** p ≤ 0.01). (b) Linear regression analysis of Siglec-1

expression versus Syk(Y352) phosphorylation in CD27+ memory B cells after 5 min anti-IgG/IgM stimulation in HDs (black), SLE

(red), RA (blue) and pSS (green) patients. Linear regression lines, coefficients of determination (R2) and Pearson’s correlation

coefficients (r) are indicated in the figure.

Further, there may be serum factors commonly increased or reduced in SLE, RA and pSS patients

potentially leading to reduced Syk(Y352) phosphorylation in all three diseases. To test this hypothesis,

serum samples of 10 HD, 4 SLE, 6 RA and 10 pSS patients were collected at the day of Syk(Y352)

phosphorylation experiments. Those serum samples were screened for the expression of IL-1β, IL-1Ra,

IL-2, IL-4, IL-5, IL-6, IL-7,IL-8,IL-9, IL-10, IL-12(p70), IL-13, IL-15, IL-17, IL-21, eotaxin, FGF basic,

G-CSF, GM-CSF, IFNγ, IP-10, MCP-1(MCAF), MIP-1a, MIP-1b, PDGF bb, RANTES, TNFα as well as

VEGF and analyzed for differential expression and correlation with pSyk(352) in CD27+ memory B cells

after 5 min anti-IgG/IgM stimulation (Supplementary Figures 2, 3, 4, Supplementary Tables 2, 3).

Tables with absolute serum concentrations (Supplementary Tables 2, 3), a heat map with relative

cytokine expression for each donor (Supplementary Figure 3) and the correlation analysis

(Supplementary Figure 4) are listed in the appendix. Not all parameters were detectable within the

range of the standard curves, in particular IL-6, IL-7, IL-15, IL-21 and G-CSF.

IL-1β, IL-1Ra, IL-10, IL-12(p70), IL-17, GM-CSF, RANTES and TNFα serum expression was

significantly increased in SLE patients and IP-10 was significantly increased in pSS patients compared

to HDs (Supplementary Figure 4). However, none of the tested serum factors was found commonly

increased among all three autoimmune diseases, neither did the expression of one of the factors

correlate with pSyk(Y352) after 5 min anti-IgG/IgM stimulation in CD27+ memory B cells.

Neither in vivo Siglec-1 nor in vivo IL-1β, IL-1Ra, IL-2, IL-4, IL-5,IL-8,IL-9, IL-10, IL12(p70), IL-13, IL-

17, eotaxin, FGF basic, GM-CSF, IFNγ, IP-10, MCP-1(MCAF), MIP-1a, MIP-1b, PDGF bb, RANTES,

TNFα and VEGF expression correlated with the ex vivo anti-IgG/IgM induced phosphorylation of

Syk(Y352) in CD27+ memory B cells.

6.8 Common CpG Methylation Patterns Among SLE, RA, pSS and HD CD19+

B Cells

T cell hypomethylation is associated with SLE [262]. Therefore, it was hypothesized whether epigenetic

factors, such as differential CpG methylation, may control B cell hyperresponsiveness. A meta-analysis

of Infinium HumanMethylation450K BeadChip data from individual epigenome-wide association studies

(EWAS) was performed by our cooperation partner (Figure 13). Differentially methylated regions

(DMR) were analyzed from public available data sets of SLE, RA , pSS patients and the respective HD

control CD19+ B cells [254-256].

Overall, the global CpG methylation values from autoimmune disease CD19+ B cells correlate with

those from HD CD19+ B cells (r =0.99) (Figure 13a). Mostly, no substantial differences were found

when the methylation status of certain genes, related to CD40 and BCR signaling, B cell activation and

the methylation status of kinases and phosphatases, was analyzed (Figure 13b). However, some

hypomethylation of multiple CpGs at the interferon-induced transmembrane protein 1 (IFITM1) locus,

the kinase eukaryotic translation initiation factor 2 alpha kinase 2 (EIF2AK2) (cg14126601) and the

kinase modulator thyroid hormone receptor interactor 6 (TRIP6) (cg19279257) were found as a general

characteristic in autoimmune disease CD19+ B cells. Genes encoding interferon induced proteins, such

as IFITM1, interferon induced protein 44 like (IFI44L) and myxoma resistance protein 1 (MX1) were

found to be the most differentially methylated CpGs, mainly in SLE and pSS and to a lesser extent in

RA B cells compared to HDs (Figure 13c, Supplementary Table 4).

Figure 13: Comparable methylation pattern of HD, SLE, RA and pSS B cells. Meta-analysis of publicly available methylome

data from HDs (black), SLE (red), RA (blue) and pSS (green) B cells. (a) Correlation of mean β-values of total single CpGs in

HDs versus autoimmune disease (AID) samples (n(HD/SLE/RA/pSS) = 175/48/49/24). (b) Correlation of CpG methylation

associated with the indicated categories between HDs and autoimmune disease samples. (c) Individual CpGs with 10 % lower

DNA methylation in SLE, RA and pSS samples compared to HDs in (a). Data shown are represented as mean ± SEM.

6.9 Chronic Anti-IgG/IgM Stimulation Prevents Syk(Y352) Phosphorylation Upon

IgG/IgM Rechallange

A potential underlying mechanism of reduced BCR signaling measured by Syk(Y352) phosphorylation

may be the induction by external factors such as chronic cytokine, TLR or BCR engagement. Even

though there was no solid hint from the tested patient’s sera (Section 6.7), local environmental

differences, for example in autoimmune inflamed tissues, rather than peripheral cytokine levels, might

be involved in such events. Thus, a set of cytokines was tested to induces reduced pSyk(Y352) upon

48 h ex vivo incubation with subsequent anti-IgG/IgM stimulation in HD CD27- B cells and CD27+

memory B cells.

An increased IFNα signature is typically found in SLE and pSS patients [194, 263], IL-21 may drive

autoreactive plasma cell development [264] and, together with IFNγ, t-bet expression in B cells is

associated with autoimmunity [265] (Supplementary Figure 5a, b). Thus, these cytokines, as well as

IL-2, IL-6 and IL-10, which play a role in inflammation and autoimmunity [266-268] were tested to induce

reduced pSyk(Y352) upon anti-IgG/IgM stimulation (Supplementary Figure 5c). However, none of

those conditions was able to change the anti-IgG/IgM-induced Syk(Y352) phosphorylation in CD27-

B cells or CD27+ memory B cells compared to RPMI control within 48 h of incubation.

TLR9 signaling may govern a checkpoint for DNA-containing antigens [158] and chronic stimulation of

the BCR leads to B cell anergy [269]. Therefore, it was tested whether continuous stimulation of the

BCR or TLR9 may be able to induce reduced Syk(Y352) phosphorylation upon re-stimulation with anti-

IgG/IgM (Figure 14). HD PBMCs were cultured with anti-IgG/IgM or CpG for 24, 48 or 72 h and

subsequently stimulated with anti-IgG/IgM for 5 min.

Notably, chronic challenge with anti-IgG/IgM revealed reduced Syk(Y352) phosphorylation in CD27-

B cells and CD27+ memory B cells after 24, 48 and 72 h (Figure 14a, b, c). However, chronic CpG

stimulation did not alter anti-IgG/IgM induced pSyk(Y352) in comparison to unstimulated RPMI control.

In detail, chronic anti-IgG/IgM stimulation reduced pSyk(Y352) MFI from 2,476 (RPMI control) to 1,202

(anti-IgG/IgM) in CD27- B cells and from 4,593 to 1,316 in CD27+ memory B cells after 24 h of

incubation between RPMI control and anti-IgG/IgM stimulation, respectively. Chronic anti-IgG/IgM

induced MFIs did not increase after 48 h (1,069 in CD27- B cells and 1,206 in CD27+ memory B cells)

and 72 h (851 and 1,002 in CD27- B cells and CD27+ memory B cells, respectively). Furthermore, in

CD27- B cells, mean MFI after stimulation with CpG were 3,259, 2,484 and 1,822 for 24, 48 and 72 h,

respectively. In CD27+ memory B cells, mean MFI were 5,731, 4,571 and 3,684 after 24, 48 and 72 h

stimulation with CpG, respectively. Thus, CpG stimulated cells exhibited comparable MFIs to RPMI

control for CD27- B cells (2,476, 2,079 and 1,762) and CD27+ memory B cells (4,593, 3,675 and 3,459)

after 24, 48 and 72 h.

Figure 14: Reduced pSyk(Y352) in CD27- B cells and CD27+ memory B cells upon chronic IgG/IgM stimulation. PBMCs

were cultured in the presences of anti-IgG/IgM (red), CpG (blue) or RPMI (black) as control for 24, 48 and 72 h. Harvested cells

were subsequently re-stimulated with anti-IgG/IgM for 5 min or left unstimulated (grey) and analyzed for pSyk(Y352) in CD27-

B cells and CD27+ memory B cells. (a) Representative pSyk(Y352) histograms of CD27- B cells (left) and CD27+ memory B cells

(right) at day 0 of culture and 24, 48 and 72 h thereafter. Phospho-Syk(Y352) MFIs in (b) CD27- B cells and (c) CD27+ memory

B cells (n(HD) = 3). Horizontal lines indicate the mean ± SD.

In vitro pre-incubation of HD B cells with IFNα, IFNγ, IL-21, IL-2, IL-6, IL-10 or CpG could not induce

reduced pSyk(Y352) MFIs upon re-stimulation with anti-IgG/IgM. However, chronic stimulation of the

BCR led to sustained low pSyk(Y352) MFIs over 72 h in vitro.

6.10 CD40 Co-Stimulation Increases Anti-IgG/IgM-Induced Syk(Y352)

Phosphorylation

Reduced phosphorylation of Syk(Y352) and Btk(Y223) upon anti-IgG/IgM stimulation appears to be

counter-intuitive to the pathogenic involvement of B cells in autoimmunity. Nevertheless, in vivo B cell

activation in autoimmunity may be linked to abnormal GC activity [2, 181, 270]. Furthermore, cognate

T cell help via CD40 signaling is critically involved in GC formation and is further known to augment

BCR signaling via Syk [27]. Therefore, CD40 co-stimulation may be able to enhance the reduction of

anti-IgG/IgM induced Syk(Y352) phosphorylation in SLE, RA and pSS B cells. CD40 requires cross-

linking for optimal activation. To reproduce optimal CD40 co-stimulation in vitro, three approaches were

tested: (i) Anti-CD40 plate coating, (ii) co-culture with an adherent hCD40L expressing cell line and (iii)

a CD40L cross-linking kit. Differential expression of pSyk(Y352) after culturing with a CD40-stimulating

reagent for 48 h and subsequent anti-IgG/IgM stimulation for 5 min was analyzed in CD27- B cells and

CD27+ memory B cells. Frequencies of CD27- and CD27+ memory B cells were monitored to assess

negative effects by the respective stimulus on these subsets.

6.10.1 Appropriate Activation of CD40 Using the CD40L Cross-Linking Kit

(i) HD PBMCs were cultured for 48 h on an anti-CD40 coated plate at 0.1, 1, 5, 10, 100 µg ml-1 and a

PBS control. Frequencies of CD27- and CD27+ memory B cells did not show any substantial difference

up to the highest concentration tested (100 µg/ml) compared to baseline and PBS control (Figure 15a).

Furthermore, there was no difference on anti-IgG/IgM induced pSyk(Y352) MFI between PBS control

and the antibody at any concentration tested for CD27- B cells (Figure 15b) and CD27+ memory B cells

(Figure 15c).

Figure 15: Comparable Syk(Y352) phosphorylation with and without anti-CD40 coating. HD PBMCs were incubated with

plate coated anti-CD40 at the concentrations 0 (PBS control), 0.1, 1, 5, 10 and 100 µg/ml, subsequently stimulated with anti-

IgG/IgM for 5 min and analyzed for pSyk(Y352). (a) Representative dot plots of CD27- B cells and CD27+ memory B cell

frequencies at baseline (left) and 48 h after culture without (middle) or with anti-CD40 stimulation (right). Representative

pSyk(Y352) histograms and MFIs in (b) CD27- B cells and (c) CD27+ memory B cells without (black) and with anti-CD40 co-

stimulation at the concentrations 0.1, 1, 5, 10 and 100 µg/ml (blue). Data represent three technical replicates. Horizontal lines

represent the mean ± SD.

(ii) A co-culturing system using adherent hCD40L expressing L cells was tested. Proliferation of L cells

was stopped using irradiation. The cells became larger upon irradiation compared to non-irradiated

cells. This is reflected by their increased SSC vs. FSC scatter properties (Figure 16a, b). Optimal

irradiation dosage was tested using CFSE proliferation staining. The cells did not proliferate upon 5,000,

7,500 and 10,000 rad irradiation dosage (Figure 16c). Furthermore, irradiated cells exhibited higher

CFSE staining than at baseline. This circumstance can be explained by the increased size of irradiated

cells. 5,000 rad was selected and taken forward into the following experiments. In addition, CD40

expression was confirmed on irradiated and non-irradiated hCD40L-transfected versus wild type (WT)

L cells (Figure 16d). Upon co-culture of hCD40L expressing or WT L cells with PBMCs, CD27+ memory

B cell frequencies dropped from 28.7 % at baseline to 7.16 % under CD40L co-stimulation, whereas

frequencies under WT conditions remained at 26.8 % (Figure 168e). Anti-IgG/IgM induced Syk(Y352)

phosphorylation increased in CD27- B cells upon CD40L co-stimulation (2,238) compared to the WT

condition (1,738) (Figure 16f). For the remaining CD27+ memory B cells, no effect was detectable.

Figure 16: Reduced frequencies of CD27+ memory B cells after co-culture with hCD40L L cells. HD PBMCs were co-

cultured with irradiated murine L cells with and without hCD40L transfection for 48 h. Harvested cells were stimulated with anti-

IgG/IgM for 5 min and analyzed for Syk(Y352) phosphorlyation. Representative dot plots of L cells (a) before and (b) after

irradiation gated on living (DAPI-) cells. (c) CFSE staining histograms of L cells at baseline (black line) and after irradiation with

5,000 rad (light orange), 7,500 rad (middle orange) and 10,000 rad (dark orange). Unstained (DMSO) control is shown in grey.

(d) Human CD40L expression on WT (black line) and transfected (blue line) L cells. The grey area represents the unstained

control. (e) Dot plots of CD27- B cells and CD27+ memory B cell frequencies at basline (left) and after co-cultur with WT (middle)

and transfected (right) L cells. (f) Phospho-Syk(Y352) MFI in CD27- B cells (dots) and CD27+ memory B cells (circles) after co-

culture with WT (black) or transfected (blue) L cells. Data represent three technical replicates. Horizontal lines indicate the

mean ± SD.

(iii) A commercially available cross-linking kit containing sCD40L and a cross-linking antibody was used.

Frequencies of CD27+ memory B cells upon co-stimulation were lower (15.9 %) than for RPMI or

sCD40L control (19.7 % and 19.8 %, respectively) and compared to baseline (29.8 %) (Figure 17a).

No effects were observed for sCD40L or the cross-linking antibody alone (Figure 17b, c, d, e).

However, anti-IgG/IgM induced pSyk(Y352) MFIs were increased in CD27- B cells (3,441 vs. 2,697), as

well as in CD27+ memory B cells (4,290 vs. 3,441) using the cross-linked CD40L compare to RPMI

control (Figure 17d, e).

Figure 17: Increased Syk(Y352) phosphorylation upon co-stimulation with CD40L cross-linking kit. HD PBMCs were

incubated with and without the CD40L cross-linking kit for 48 h, subsequently stimulated with anti-IgG/IgM for 5 min and analyzed

for pSyk(Y352). (a) Representative dot plots of CD27- B cells and CD27+ memory B cell frequencies at baseline (left) and after

48 h culture with RPMI (middle left), sCD40L (middle right) and the CD40L cross-linking kit (right). (b) Representative histograms

of anti-BCR induced Syk(Y352) phosphorylation in CD27- B cells (left) and CD27+ memory B cells (right) upon co-stimulation with

RPMI (dotted line), sCD40 (solid line) and the CD40L cross-linking kit (blue line). Unstimulated control is represented in grey. (c)

Phospho-Syk(Y352) MFI upon co-stimulation with RPMI (black), sCD40L (black) and the CD40L cross-linking kit (blue) in CD27-

B cells (dots) and CD27+ memory B cells (circles). Data represent three technical replicates. Horizontal lines indicate the

mean ± SD. (d) Representative pSyk(Y352) histograms of CD27- B cells and CD27+ memory B cells upon co-stimulation with

RPMI (dashed line), the cross-linking antibody from the kit only (solid line) and cross-linked CD40L (blue). (e) Phospho-Syk(Y352)

MFIs from CD27- B cells (dots) and CD27+ memory B cells (circles) upon co-stimulation with RPMI (black), the cross-linking

antibody (black) and cross-linked CD40L.

Coated anti-CD40L antibody exhibited no efficiency in this experimental setup (Figure 15). However,

co-culturing with hCD40L expressing cells and co-stimulation with CD40L cross-linking kit increased

anti-IgG/IgM induced Syk(Y352) phosphorylation mainly in CD27- B cells (Figures 16, 17).

Unfortunately, CD40L expressing L cells led to a strong depletion of CD27+ B cells, which makes them

unsuitable for further experiments. Depletion of CD27+ memory B cells was also observed after use of

the CD40L cross-linking kit, but to a somewhat lesser extent. Therefore, CD40L cross-linking was

chosen for subsequent experiments.

6.10.2 Increased Anti-IgG/IgM Induced Syk(Y352) Phosphorylation Upon CD40-Co-

Stimulation in SLE, RA, pSS and HD B cells

Next, HD, SLE, RA and pSS CD27- B cells and CD27+ memory B cells were tested for their

responsiveness to anti-IgG/IgM stimulation upon CD40 co-stimulation using the CD40L cross-linking

kit (Section 6.10.1). Anti-IgG/IgM induced pSyk(Y352) MFIs after stimulation with CD40L increased

among CD27- B cells and CD27+ memory B cells from HDs, SLE, RA and pSS patients compared to

anti-IgG/IgM-only stimulation (Figure 18a, b). Overall, co-stimulation with CD40L significantly

increased mean pSyk(Y352) MFIs in HD (from 2,101 to 3,333), SLE (from 1,757 to 3,184), RA (from

1,922 to 2,960) and pSS (from 2,036 to 2,698) CD27- B cells as well as in HD (from 3,688 to 4,769)

and pSS (from 2,733 to 3,404) CD27+ memory B cells compared to no co-stimulation (Figure 18c). In

SLE CD27+ memory B cells, CD40 co-stimulation increased anti-IgG/IgM induced pSyk(Y352), even

though the phosphorylation remained lower compared to HDs. Differences of anti-IgG/IgM induced

Syk(Y352) phosphorylation in RA and pSS CD27+ memory B cells upon CD40 co-stimulation were not

significant. Of note, co-stimulation increased anti-IgG/IgM induced Syk(Y352) phosphorylation in RA and

pSS CD27+ memory B cells and SLE CD27- B cells to almost comparable levels of HDs.

The cytokines IL-4 and IL-21 contribute to TFH helper signals in a GC reaction [62]. Furthermore, CD40L

together with IL-4 stimulation is reported of being able to restore reduced BCR signaling in an anergic

IgM-IgD+CD45+ B cell subset [271] and IL-21 plays a crucial role in the development of autoreactive

plasma cells [264]. Therefore, the impact of IL-4, IL-21 and combinations of CD40L with IL-4 or IL-21

were tested on their co-stimulatory capacity to anti-IgG/IgM induced Syk(Y352) phosphorylation in HDs,

SLE, RA and pSS.

IL-4R or IL-21R co-stimulation with the cytokines IL-4 or IL-21 alone had minor effects on Syk(Y352)

phosphorylation in CD27- B cells and CD27+ memory B cells from all groups (Figure 18c). Remarkably,

stimulation with CD40L in combination with IL-4 significantly increased anti-IgG/IgM induced Syk(Y352)

phosphorylation in HD, SLE, RA and pSS CD27- B cells and CD27+ memory B cells in comparison to

no co-stimulation. Upon CD40/IL-21R co-stimulation, the effects were moderate with significantly

increased Syk(Y352) phosphorylation in CD27- B cells from all groups and CD27+ memory B cells from

HDs.

Figure 18: Increased anti-IgG/IgM induced Syk(Y352) phosphorylation after CD40 co-stimulation in HD, SLE, RA and pSS

CD27- and CD27+ memory B cells. HD (black), SLE (red), RA (blue) and pSS (green) PBMCs were incubated with IL-4, IL-21,

CD40L alone or combinations thereof for 48 h, subsequently stimulated with anti-IgG/IgM for 5 min and analyzed for pSyk(Y352).

Representative pSyk(Y352) histograms of (a) CD27- B cells and (b) CD27+ memory B cells. Cells without co-stimulation are

indicated in grey. (c) Phospho-Syk(Y352) MFI in CD27- B cells (filled boxes) and CD27+ memory B cells (blank boxes) with

(n(HD/SLE/RA/pSS) = 11/7/5/5) and without co-stimulation (n(HD/SLE/RA/pSS) = 30/18/16/15). Within the Box whisker plots the

median (line), mean (plus) and range (whiskers) are represented (one-way ANOVA with DMCT, * p ≤ 0.05, ** p ≤ 0.01,

*** p ≤ 0.001; repeated measures ANOVA with DMCT, # p ≤ 0.05, ## p ≤ 0.01, ### p ≤ 0.001).

In this set of experiments, it was also tested whether co-stimulation impacts basal Syk expression and

Syk(Y352) phosphorylation which may influence signaling capacity of Syk (Supplementary Figure 6).

A small upregulation of Syk was found upon CD40 and CD40/IL-4R co-stimulation in SLE, RA and HD

CD27- B cells as well as in HD CD27+ memory B cells. Notably, only SLE CD27- B cells were found to

have a significantly increased basal Syk expression upon CD40/IL-21R co-stimulation. Basal

pSyk(Y352) was overall increased in CD27- B cells and CD27+ memory B cells from all groups upon

CD40L co-stimulation with and without IL-4 or IL-21. However, the extent of the change was modest.

These data show that CD40 co-stimulation with and without IL-4, and to a lesser extend with IL-21,

stimulation increases anti-IgG/IgM induced Syk(Y352) phosphorylation in SLE, RA, pSS and HD CD27-

B cells as well as CD27+ memory B cells. SLE CD27- B cells showed remarkable responses upon co-

stimulation with CD40L alone or in combination with IL-4 or IL-21.

6.11 Reduced TLR9 Induced Differentiation into CD27+CD38+ ASCs of SLE, RA and

pSS B Cells

TLR9 activation and signaling has been linked to the induction of autoantibodies against dsDNA and

ribonucleoproteins, indicating a critical role of this receptor in the activation of B cells in autoimmunity

[186, 187]. TLR9 engagement mainly activates memory B cells and drives in vitro activation,

proliferation and differentiation of B cells into ASCs [159, 160, 272]. However, impaired activation of

SLE B cells upon TLR9 stimulation has been reported [22-24]. Within this study reduced Syk(Y352)

phosphorylation upon anti-IgG/IgM stimulation was found of being a commonality within SLE, RA and

pSS autoimmune disease (Section 6.3). Addressing the question whether impaired TLR9 activation is

also a shared abnormality in terms of B cell activation among these autoimmune diseases, B cell

differentiation into CD27+CD38+ ASC in HDs, SLE, RA and pSS patients upon in vitro stimulation with

CpG was analyzed.

As a result, CD27+CD38+ ASC frequencies and absolute concentrations were approximately 2 to 4-fold

higher in HDs (28.5 % with 95.4 cells/ml) compared to SLE (12.2 % with 28.7 cells/ml), RA (13.6 % with

22.3 cells/ml) and pSS (15.0 % with 56.0 cells/ml) patients upon TLR9 stimulation with CpG

(Figure 19a, b, c). These results were significantly different for SLE, RA and pSS in terms of

CD27+CD38+ frequencies as well as for SLE and RA in terms of CD27+CD38+ ASC concentrations.

Dual engagement of TLR9 and the BCR is thought of playing a central role in breaking tolerance against

nuclear antigens [160, 188, 273] and leads to a stronger activation of naive B cells compared to TLR9

alone [159, 160]. Therefore, dual stimulation of TRL9 and the BCR was tested in HDs, SLE, RA and

pSS (Figure 19a, b, c). Combined IgG/IgM and TLR9 activation did not substantially alter the

frequency of CD27+CD38+ from HD or pSS B cells compared to TLR9 only stimulation (Figure 19a, b).

However, mean frequencies of CD27+CD38+ cells were marginally increased from 12.2 to 19.4 % in

SLE and 13.6 to 17.5 % in RA (TLR9 vs. TLR9/BCR, respectively) (Figure 19b). Absolute CD27+CD38+

ASC concentrations show a similar pattern with an increase mainly in SLE B cell concentration from

28.7 to 59.0 cells/ml. However, the response of autoimmune disease B cells remained overall lower

than for HDs with significantly lower frequencies in pSS (42.9 cells/ml) compared to HDs (70.5 cells/ml)

(Figure 19c). As a control, CD27+CD38+ cell frequencies and concentrations after anti-IgG/IgM only

stimulation was comparable to IL-2/IL-10 background control in all groups (Figure 19a, b, c).

To assess the effects of CD40 co-stimulation, cells were cultured with CD40L only and the combinations

of CD40L with CpG or CpG/anti-IgG/IgM (Figure 19a, b, c). Overall, frequencies and concentrations of

CD27+CD38+ ASCs upon culture with CD40L alone or in the presence of CpG or CpG/anti-IgG/IgM

were comparable with IL-2/IL-10 background control. This is in line with a previous report showing that

CD40L stimulation blocks in vitro differentiation of B cells [274].

Figure 19: Less ASC differentiation of SLE, RA and pSS B cells upon TLR9 stimulation. HD (black), SLE (red), RA (blue)

and pSS (green) PBMCs were cultured for 5 days with anti-IgG/IgM, CD40L or CpG and the combinations CD40L/CpG, CpG/anti-

IgG/IgM or CD40L/CpG/anti-IgG/IgM in the presence of IL-2 and IL-10. ASCs were analyzed upon their high expression of CD27

and CD38. (a) Representative contour plots of CD19+ B cells gated on CD27+CD38+ ASC from SLE, RA, pSS patients and HDs

for the indicated stimulus. (b) CD27+CD38+ frequencies for HD, SLE, RA and pSS samples (n(HD/SLE/RA/pSS) = 18/18/11/10

(IL-2/IL-10 control); 12/8/6/5 (IgG/IgM); 12/8/7/7 (CD40); 17/18/9/10 (TLR9); 12/8/5/6 (TLR9/CD40); 17/18/8/10 (IgG/IgM/TLR9);

12/8/5/6 (IgG/IgM/TLR9/CD40)). (c) CD27+CD38+ concentrations for HD, SLE, RA and pSS samples

(n(HD/SLE/RA/pSS) = 15/17/8/8 (IL-2/IL-10 control); 8/7/3/3 (IgG/IgM); 13/8/7/6 (CD40); 14/17/6/8 (TLR9); 12/8/5/6

(TLR9/CD40); 14/17/5/8 (IgG/IgM/TLR9); 12/8/5/6 (IgG/IgM/TLR9/CD40)). Bars indicate the mean ± SD (one-way ANOVA with

DMCT; * p ≤ 0.05, ** p ≤ 0.01; # p ≤ 0.05, ## p ≤ 0.01, ### p ≤ 0.001).

It has been previously reported that Syk inhibition leads to an impaired in vitro B cell activation and

differentiation upon TLR9 signaling [162, 163]. Therefore, TLR9 induced B cell differentiation under

entospletinib, a specific Syk inhibitor, was tested on HD PBMCs. The effect of entospletinib was

concentration-depended with the highest inhibitory capacity at 10 µM (1.14 % CD27+CD38+ ASCs)

compared to DMSO control (16.6 % CD27+CD38+ ASCs) (Figure 20a). In vitro inhibition of Syk using

10 µM entospletinib resulted in reduced CD27+CD38+ frequencies and concentrations upon TLR9

stimulation of HD B cells (Figure 20b) mimicking hyporesponsiveness to TLR9 signals observed in

SLE, RA and pSS B cells (Figure 19).

Figure 20: Less TLR9 induced ASC differentiation upon Syk inhibition. HD PBMCs were stimulated with CpG for 5 days

with or without the presence of entospletinib, a specific Syk inhibitor. CD19+ B cells were analyzed for the differentiation into

CD27+CD38+ ASCs. (a) Representative couture plots of CD27+CD38+ gating for unstimulated (IL-2/IL-10 background control)

and stimulated cells with 0.1, 1 and 10 µM entospletinib or DMSO control. (b) CpG induced ASC frequencies and concentrations

with or without 10 µM Syk inhibitor (n(HD) = 5); (paired t-test; * p ≤ 0.05).

Differentiation into CD27+CD38+ ASCs was found to be impaired in SLE, RA and pSS B cells upon

TLR9 engagement. Reduced frequencies of CD27+CD38+ cells upon TLR9 stimulation and Syk

inhibition suggested a functional relationship between reduced BCR signaling and reduced responses

upon TLR9 stimulation. In line with this, CD27+CD38+ ASCs were only modestly increased in SLE, RA

and pSS upon combined TLR9 and BCR stimulation, but overall were not fully restored to HD

responses.

6.12 Restored Proliferation of SLE, RA and pSS B Cells Upon Co-Stimulation with

CD40L

Besides CD27+CD38+ B cell differentiation (Section 6.10), proliferation was assessed using CFSE

staining. In line with reduced TRL9-induced differentiation in SLE, RA and pSS, mean frequencies of

proliferated SLE (46.6 %), RA (55.4 %) and pSS (50.0 %) CD19+CFSElow B cells were reduced

compared to HDs (68.2 %) (Figure 21a, b). This was significant for SLE. Combined activation of TLR9

and BCR increased the proliferation of SLE (80.2 %), RA (91.7 %) and pSS (80.6 %) B cells to the

levels of HDs (85.4 %). Even though there was low differentiation into CD27+CD38+ ASCs observed

upon CD40 stimulation (Figure 19a, b, c), CD40L induced B cell proliferation was comparable between

HD, SLE, RA and pSS samples (Figure 21a, b). Notably, low TLR9-induced proliferation of SLE, RA

and pSS B cells were increased to HD levels upon the addition of CD40L and led to an overall stronger

proliferation compared to CD40, TLR9 or anti-IgG/IgM alone.

Figure 21: Decreased proliferation of SLE B cells upon TLR9 stimulation and comparable proliferation of SLE, RA, pSS

and HD B cells upon CD40 stimulation or combined IgG/IgM stimulation. HD (black), SLE (red), RA (blue) and pSS (green)

PBMCs were cultured for 5 days and treated to target IgG/IgM, CD40 and/or TLR9. Therefore, anti-IgG/IgM, CD40L or CpG and

the combinations CD40L/CpG, CpG/anti-IgG/IgM or CD40L/CpG/anti-IgG/IgM were added in the presence of IL-2 and IL-10.

Cultured cells were analyzed for proliferation using CFSE staining (a) Representative CFSE histograms of HD, SLE, RA and

pSS B cells after stimulation with the indicated stimulus (lines) compared to IL-2/IL-10 background control (grey). (b) Frequencies

of CFSElow B cells from HD, SLE, RA and pSS samples (n(HD/SLE/RA/pSS) = 17/19/9/10 (IL-2/IL-10 control); 11/10/6/5

(IgG/IgM); 10/7/4/5 (CD40); 16/18/7/9 (TLR9); 10/7/4/5 (TLR9/CD40); 16/19/7/9 (IgG/IgM/TLR9); 10/7/4/5 (IgG/IgM/TLR9/CD40))

(c) Resulting frequency of CD27+CD38+ B cells upon activation in culture (n(HD/SLE/RA/pSS) = 18/18/11/9 (IL-2/IL-10 control);

12/8/6/5 (IgG/IgM); 12/8/7/7 (CD40); 17/18/9/10 (TLR9); 12/8/5/6 (TLR9/CD40); 17/19/8/10 (IgG/IgM/TLR9); 12/7/5/6

(IgG/IgM/TLR9/CD40)). Bars represent the mean ± SD (one-way ANOVA with DMCT; * p ≤ 0.05, ** p ≤ 0.01; # p ≤ 0.05,

## p ≤ 0.01, ### p ≤ 0.001).

These data show that the proliferative capacity of SLE, RA and pSS B cells is limited upon TLR9

stimulation. However, CD40 engagement as co-stimulatory signal induces strong and comparable

proliferation in HD, SLE, RA and pSS B cells.

6.13 CD40/IL-4R Co-Stimulation Decreases PTP Expression

PTP/PSP activities were found uniquely increased in SLE CD19+ B cells at baseline (Figure 5) and

CD40/IL-4R co-stimulation was able to increase anti-IgG/IgM induced Syk(Y352) phosphorylation

(Figure 18). This led to the suggestion that CD40/IL-4R signaling may be involved in the modulation of

PTP and PSP expression. The Expression of non-receptor and receptor type PTP and PSP genes was

analyzed within publicly available gene expression data sets from SLE and HD CD20+ B cells, CD4+

and CD8+ T cells as well as MS and HD CD19+ B cells as controls (Figure 22). Furthermore, the impact

of CD40/IL-4R co-stimulation on their expression was assessed.

Increased PTPN2, PTPN11, PTPN22, PTP receptor type C (PTPRC) and PTP receptor type O

(PTPRO) gene expression was found in SLE CD20+ B cells. However, no differentially expressed PTP

was found in MS B cells compared to HDs indicating that differential expression of PTPN2, PTPN11,

PTPN22, PTPRC and PTPRO is specific for SLE. Among the analyzed PTPs, no differentially

expressed RPTP and only marginal differential expression of the NRPTPs PTPN1, PTPN9 and

PTPN22 among SLE CD4+ T cells and PTPN1, PTPN7, PTPN9, PTPN11 and PTPN22 among SLE

CD8+ T cells was found when compared to HDs.

PTPN6 and PTP receptor type N 2 (PTPRN2) gene expression was increased in unstimulated SLE

CD19+ B cells compared to unstimulated CD19+ B cells from HDs. However, in contrast to the data

from the literature gene expression of PTPRB was decreased. Of note, CD40L/IL-4 stimulation led to a

downregulation of PTPN2 and PTPN22 as well as all RPTP (except PTP receptor type B (PTPRB))

gene expression compared to their overexpression before stimulation.

Figure 22: Receptor-type PTPs show reduced expression upon CD40/IL-4R co-stimulation. Selcted non-receptor type and

receptor type PTPs were differentially analyzed for their gene expression. Data were obtained from publicly available data sets

(lines 1 – 4) or collected experimentally upon co-stimulation with CD40L/IL-4 (lines 5 – 8). Lines 1 – 4: SLE vs. HD CD20+ B cells

(6 SLE, 7 HD), MS vs. HD CD19+ B cells (10 MS, 10 HD), SLE vs. HD CD4+ (53 SLE, 41 HD) and CD8+ T cells (22 SLE, 31 HD).

Lines 5 – 8: Un-stimulated SLE vs. HD as well as CD40L/IL-4 stimulated vs. un-stimulated SLE or HD CD19+ B cells, respectively

(n(HD/SLE) = 1/2). Gene expression is shown as linear fold change (LFC). Red squares indicate induction, white squares indicate

no change and blue squares indicate reduction compared to HDs.

As PSP activities were found to be increased in SLE B cells, genes related to serine/threonine-protein

phosphatase 2 (PP2) and PP2C family were analyzed (Supplementary Figure 7). Analyzing the data

from the literature, small differences were found in PSP gene expression when SLE B and T cells were

compared to HDs. No differences were found when MS B cells were compared to HDs. In addition,

unstimulated B cells displayed small differences in PP2 and PP2C gene expression, whereas CD40/IL-

4R co-stimulation led to heterogeneous changes: increased expression of PP2 family genes except

PP2A subunit B isoform PR48 (PPP2R3B) (unaffected) and decreased PP2A B subunit isoform PR61-

delta (PPP2R5D) was detected. However, PP2C family members were unaffected.

Taken together, differential baseline expression of the PTPs PTPN2, PTPN11, PTPN22, PTPRC and

PTPRO is specific for SLE B cells compared to HD. Comparable expression of PTPs and PSPs

between SLE vs. HD in CD4+ and CD8+ T cells correspond to comparable PTP activities in SLE and

HD CD3+ T cells (Section 6.1, Supplementary Figure 2). Provision of T cell help by CD40/IL-4R

engagement alters the expression of NRPTPs such as PTPN22 and different RPTPs in HD and SLE

B cells and as such is considered an important modulator of intracellular PTP activity.

6.14 Summary of Results

This comparative study of SLE, RA and pSS peripheral B cells shows that autoimmune disease B cells

share hyporesponsiveness towards BCR and TLR9 stimulation. This was demonstrated by commonly

reduced anti-IgG/IgM induced phosphorylation kinetics of the BCR downstream PTKs Syk and Btk, at

their activation sites Syk(Y352) and Btk(Y223), in CD27+ memory B cells from SLE, RA and pSS patients

(Section 6.3). Additionally, Syk(Y352) phosphorylation kinetics were reduced in SLE CD27- B cells.

Furthermore, reduced proliferation and differentiation of CD19+ B cells upon TLR9 engagement was

demonstrated (Sections 6.11). Notably, there was no distinction of Syk(Y352) and Btk(Y223)

phosphorylation kinetics between CD27- B cells and CD27+ memory B cells in SLE, RA and pSS

patients, whereas kinetics in HD CD27+ memory B cells were increased compared to CD27- B cells.

Furthermore, reduced Syk(Y352) phosphorylation kinetics were observed in tissue resident CD27+

memory B cells from autoimmune disease patients (Section 6.5). The increased colocalization of CD22

with SHP-1 in SLE, RA and pSS CD19+ B cells points into the direction of commonly increased negative

regulation of BCR downstream signaling (Section 6.1). Notably, the strongest phenotype was observed

for SLE with reduced kinetics in CD27+ memory as well as CD27- B cells whereas kinetics of CD27-

B cells in RA and pSS were comparable to HDs. Moreover, increased PTP and PSP activity was only

observed in SLE, and CD22/SHP-1 colocalization was at maximum and could not be further increased

in SLE. Syk inhibition experiments implicate that impaired TLR9-dependent differentiation of SLE, RA

and pSS B cells into CD27+CD38+ ASCs is Syk-depended. Accordingly, combined engagement of the

BCR and TLR9 increased CD27+CD38+ ASC differentiation only modestly. Reduced Syk activity in

SLE, RA and pSS peripheral B cells did not translate into reduced Akt(S473) phosphorylation

(Section 6.4). Akt(S473) phosphorylation kinetics were comparable in RA and pSS and increased in

SLE CD27- B cells and CD27+ memory B cells compared to HDs.

Common differences in baseline expression and phosphorylation of the signaling molecules Syk, Btk,

PLCγ2 and Akt, which may account for signaling abnormalities, were not observed (Section 6.2). Also,

pERK1/2(T202/Y204), a potential marker for anergy, did not exhibit any differences between HD, SLE,

RA and pSS peripheral B cells (Section 6.6). Furthermore, no commonality in the expression and

correlation with reduced Syk(Y352) phosphorylation were observed for Siglec-1, reflecting the

characteristic type I IFN signature (incl. IFNα), or any of the 23 tested serum cytokines (Section 6.7).

In addition, IFNα, IFNγ, IL-2, IL-4, IL-6, IL-10, IL-21 and CpG did not induce reduced anti-IgG/IgM

induced Syk(Y352) phosphorylation in HD B cells. However, chronic engagement of IgG and IgM led to

a sustained reduction of Syk(Y352) phosphorylation upon re-engagement with anti-IgG/IgM in CD27-

B cells and CD27+ memory B cells (Section 6.9). Nevertheless, CpG methylation was comparable

among autoimmune diseases and HDs, except for some hypomethylation at IFITM1, EIF2AK2 and

TRIP6 locus (Section 6.8). CD40 co-stimulation with and without addition of IL-4 or IL-21 increases

anti-IgG/IgM induced Syk(Y352) phosphorylation in SLE, RA, pSS and HD CD27- B cells as well as in

SLE, RA and pSS CD27+ memory B cells (Section 6.9). Remarkably, CD27- B cells from SLE were

able to normalize their Syk(Y352) phosphorylation response to HD level upon CD40 co-stimulation with

and without the addition of IL-4 and IL-21. Furthermore, CD40 co-stimulatory induces strong and

comparable proliferation of HD, SLE, RA and pSS B cells. (Section 6.11). Besides the increase of anti-

IgG/IgM induced pSyk(Y352 ) (Section 6.9), CD40/IL-4R co-stimulation reduced gene expression of

NRPTPs, for example PTPN22, and different RPTPs in HD as well as SLE CD19+ B cells

(Section 6.12).

7 Discussion

7.1 Reduced BCR Responsiveness is a Commonality Among Peripheral as Well as

Tissue Resident B Cells from Patients with Autoimmune Diseases

Increased B cell activity in autoimmune diseases such as SLE, RA and pSS is characterized by the

production of high autoantibody titers and abnormal B cell subset distributions such as increased

frequencies of circulating plasma cells and plasmablasts typically found in the peripheral blood of SLE

patients [38-40, 44-47, 76, 77, 83-86, 170-174, 275, 276]. Beneficial effects of B cell directed therapies

underscore the pathogenic role of B cells in those autoimmune diseases and highlight the importance

of B cell directed therapies [3-10]. The intracellular BCR signal as a major driver of B cell activation and

cell fate, was thought to be increased and the main driver of B cell activity in autoimmunity [15, 16,

225]. In contrast to this hypothesis, this and other work demonstrated reduced BCR signals measured

by Syk(Y352) phosphorylation in SLE CD27- B cells and CD27+ memory B cells [14, 244]. Moreover, the

presented work demonstrates that phosphorylation of the PTKs Syk and Btk, at their activation sites

Syk(Y352) and Btk(Y223), is generally reduced in CD27+ memory B cells from SLE, RA and pSS patients.

This finding indicates that reduced responsiveness of intracellular BCR signaling is a more general

phenomenon of autoimmune diseases. However, reduced Syk(Y352) phosphorylation upon BCR

stimulation is specific for CD27- B cells from SLE patients. Interestingly, the amplitude of Syk(Y352) and

Btk(Y223) phosphorylation in SLE, RA and pSS CD27+ memory B cells was comparable to CD27- B cells

of the respective disease indicating CD27- B cell-like signaling properties. Iwata et al. previously

reported increased BCR signaling measured by pSyk(Y348) expression in SLE CD19+ B cells compared

to HDs [277]. However, within that study CD27-Syk++ memory-like B cells, which show higher Syk(Y348)

phosphorylation and increased frequencies in SLE patients can bias the analysis [278]. These cells

were not excluded in the study from Iwata et al., 2015, but in the presented study. Thus, the previously

reported increase in BCR signaling do not appear contradictory to the data presented in this work.

Interestingly, serine phosphorylation of Akt(S473) was not found to be affected by reduced signaling in

SLE, RA and pSS B cells even though it also depends on Syk activation [95]. These results indicate

that reduced BCR responsiveness does not globally affect all signaling pathways and point towards

alternative regulation pathways of peripheral autoimmune disease B cells. Interestingly, reduced BCR

responsiveness of ex vivo stimulated SLE, RA and pSS B cells observed in this study may corresponds

to the observation of low responsiveness towards vaccination among those patients. Several studies

reported unresponsiveness, measured by low antibody titers, mainly analyzed and found in SLE and

RA patients, upon pneumococcus or H1N1 vaccination [279-281]. However, an impact of disease-

modifying antirheumatic drug (DMARD) treatment on those results cannot be excluded [280, 282].

Furthermore, one study found increased responses after H1N1 influenza vaccination of untreated pSS

patients compared to HDs [283]. As the BCR signal is a major driver of B cell fate, it might be possible

that these highly reactive B cells, with potentially increased BCR signal in autoimmune disease, migrate

to lymphatic or inflamed tissue. However, this work demonstrates that reduced BCR signal is not

restricted to peripheral B cells, it also affects tissue resident B cells. Syk(Y352) phosphorylation among

CD27+ memory B cells from patients with ITP was reduced compared to CD27+ memory B cells from

patients without autoimmunity. In addition, the analysis of Syk(Y352) phosphorylation in CD27+ memory

B cells from a pSS parotid was rather decreased compared to peripheral B cells, even though they are

located at an actual site of autoimmune inflammation.

7.2 Impaired Responsiveness of SLE, RA and pSS Peripheral B Cells to BCR and

TLR9 Stimuli is Connected by Syk

Besides BCR signaling, TLR9 signaling is a potential driver of autoimmunity facilitating dsDNA and

ribonucleoprotein autoantibody development, drives in vitro activation, proliferation and differentiation

of B cells into ASCs and is considered to be involved in type I interferon (IFN) production in

autoimmunity [159, 160, 186, 187, 284]. Within the presented study, responses towards TLR9 activation

were diminished including reduced proliferation and differentiation into CD27+CD38+ ASCs. This is

consistent with previous studies reporting diminished responsiveness of SLE B cells after TRL9

activation [22-24]. Ginsburg et al. found that active SLE patients did not generate ASCs in response to

pokeweed mitogen in vitro [24]. Furthermore, Sieber et al. found reduced IL-6, IL-10, vascular

endothelial growth factor (VEGF), and IL-1ra production together with reduced expression of the

proliferation marker Ki-67 after TLR9 in vitro stimulation [22]. Another study reported impaired TLR9

responses in SLE B cells which are characterized by reduced frequencies of CD69+CD86+ and

TACI+CD25+ B cells [23]. This work, supported by the data from Iwata et al. and Kremlitzka et al.,

demonstrates a functional connection between TLR9 and BCR signaling by inhibiting TLR9 induced

differentiation upon Syk inhibition [162, 163]. Based on this, a similar regulatory connection between

reduced BCR and reduced TLR9 signaling in autoimmune diseases can be assumed. In line with this

hypothesis, combined BCR and TLR9 stimulation increased proliferation and differentiation of

autoimmune disease CD19+ B cells only modestly.

7.3 Reduced BCR Responsiveness is Likely Caused by an Increase in Negative

Feedback Regulation Mediated by Protein Phosphatases

GWAS support an association of certain risk mutations within the BCR signaling cascade and the

development of autoimmunity [11, 201-210]. Therefore, it might be possible that genetic alterations may

play a role in the presented findings of reduced BCR responsiveness in autoimmune diseases. Risk

mutations of LYN, BLK, BANK1 and PTPN22 are associated with SLE [11, 201-204] and it is reported

that RA and pSS share some of these risk alleles [207-209]. A commonality of all three autoimmune

diseases is an association with PTPN22 1858C/T risk mutation [211-214], which is reported to be a

gain-of-function mutation reducing TCR as well as BCR responses in humans [218-220]. However,

Metzler et al. reported augmented BCR as well as CD40 responses in mice expressing this risk

mutation [221]. Furthermore, the risk mutation of the adapter molecule BANK1, which is mainly

expressed in CD19+ B cells, leads to a dysbalanced expression of BANK1 splicing variants, which in

turn reduces BCR signaling [204, 223]. However, PTPN22 as well as BANK1 risk alleles were reported

to reduce Akt phosphorylation [218, 223], which was not found in the present study. Furthermore,

BANK1 risk mutation appears to be specific for SLE and RA [207-209, 215] or even SLE only [217].

Therefore, an impact of mutation variants on the presented findings of reduced BCR signaling cannot

be completely excluded but appears to be less likely.

Within this study, in vivo factors, such as the expression of cytokines or Siglec-1 as surrogate marker

for type I IFN (IFNα) activity, were excluded as common inducers of reduced pSyk(Y352) in SLE, RA

and pSS patients. Of note, increased Siglec-1 expression was present in SLE and pSS patients, as

also previously reported [193, 194], but not in RA compared to HDs. The meta-analysis of common

differentially methylated CpGs among SLE, RA and pSS compared to HDs revealed that reduced BCR

and TLR9 responsiveness is likely not under epigenetic control. Also, the overall availability of the

signaling molecules and the tonic phosphorylation at the distinct sites Syk(Y352), Btk(Y223), PLCγ2(Y759)

and Akt(S473) is not affected and largely comparable to HDs.

Increased co-localization of CD22 and SHP-1 in SLE, RA and pSS CD19+ peripheral B cells compared

to HDs favors the idea of a common signaling disbalance in autoimmune disease based on increased

negative regulation via PTPs such as SHP-1. Increased PTP and PSP activities and maximal

CD22/SHP-1 colocalization indicates a stronger phenotype for SLE. Together with reduced BCR

induced Syk(Y352) phosphorylation after chronic BCR stimulation, chronic in vivo stimulation may serve

as potential mechanism of reduced BCR signaling observed in SLR, RA and pSS. Of note, baseline

expression and phosphorylation of signaling molecules is not different between HDs and autoimmune

disease patients indicating that only functionally and not tonic BCR signaling is affected by the negative

feedback loop. Furthermore, SLE B cells had maximal colocalization of CD22/SHP-1 which could not

be further increased upon anti-CD22 stimulation and increased activities of PTPs in total CD19+ B cells.

This might explain the stronger phenotype of reduced Syk(Y352) phosphorylation in CD27+ memory as

well as CD27- B cells compared to RA and pSS. In this regard, dysregulated recruitment of Syk to the

proximal BCR signaling complexes has been recently reported by Vasquez et al. The authors

hypothesize that this dysregulation is caused by constant activation through the BCR, and thus, strongly

supports the hypothesis of the presented work [238].

7.4 B Cells from Autoimmune Disease Patients Remain in a ‘Post-Activation’ State

Common to Anergy

Reduced BCR responsiveness is a hallmark of B cell anergy [285], which is a non-reactive state of

autoreactive B cells preventing tolerance breach, if cells are not silenced by receptor editing or clonal

deletion [143-145]. Between 5 and 7 % of the normal B cell repertoire is anergic [149, 150, 286]. In

humans anergic B cells are mainly identified as mature naive IgD+/IgM+ B cells, which are

predominantly autoreactive (2.5 % of peripheral B cells) [149]. Anergy has been previously described

with impaired BCR signaling leading to reduced intracellular Ca2+ mobilization and phosphorylation of

tyrosine residues [125, 144, 269, 287-290]. This is consistent with the presented observations of

reduced BCR signal in autoimmune disease CD27+ memory B cells and CD27- B cells from SLE.

Anergic B cells do not proliferate, upregulate activation markers or secret Ig upon BCR stimulation [147,

148]. In line with this, reduced proliferation and differentiation into ASCs by TLR9 and, to a lesser extent,

TLR9 and BCR stimulation, both Syk-dependent mechanisms, were observed in this study.

Furthermore, it has been reported that reduced signaling of CD19/PI3K suppresses

phosphatidylinositol-3,4,5-triphosphate (PIP3) generation by PI3K and is key for B cell anergy [291].

However, in this studies Akt(S473) phosphorylation, which is downstream of PI3K, was found to be

normal in RA and pSS and increased in SLE CD27- B cells and CD27+ memory B cells. Thus, indicating

that there might be other mechanisms for anergy or an anergy-like state independent of CD19/PI3K.

Another characteristic of anergic B cells is elevated basal Ca2+ levels [133]. This was not directly

assessed within this study. However, our group previously reported no increase of basal Ca2+ in CD19+

B cells from SLE patients [14]. In line with the presented data on similar basal phosphorylation between

autoimmune disease patients and HDs as well as BCR-activation induced differential signaling,

differential Ca2+ responses occur after BCR engagement. It is thought that BCR unresponsiveness in

anergic cells is due to chronic antigen exposure [269], which has been mimicked in vitro within this

work. However, B cell anergy is not permanent and can be reversed upon removal of the antigen [269].

It has been reported that reduced BCR signaling of SLE B cells is permanent and cannot be restored

upon incubation with medium over 48 h [14]. This is confirmed by the present work in which RPMI

control data of CD40 and BCR co-stimulation experiments after 48 h incubation are still reduced in SLE

as well as RA and pSS B cells compared to HDs.

Furthermore, it has been reported that continuous signaling via the phosphatases SHIP-1 and SHP-1

is required to maintain anergy [287, 292]. Within this study, we demonstrated enhanced recruitment of

SHP-1 to CD22, a negative regulator of BCR downstream signaling, and thus, involved in maintaining

low BCR responsiveness, as a commonality among SLE, RA and pSS B cells. Moreover, B cells in GC

were found to display reduced BCR signaling, which is maintained by SHP-1 and SHIP-1 activity, as

well as increased colocalization of SHP-1 with the BCR after activation [250]. These results indicate

that BCR signaling is downmodulated at some point after B cell activation. Following this, post-

activation and functional anergy might be characterized by a reduced BCR signaling in peripheral and

tissue resident CD27+ memory B cells of autoimmune diseases, such as SLE, RA and pSS. One

possible way of inducing this dysfunction in HD B cells is chronic BCR stimulation by self-antigens or

immune complexes without an appropriate co-stimulation. However, this study indicates that B cells

from patients with SLE, RA and pSS are in a regulated state of low responsiveness. Of note, BCR

signaling seems to be crucial for this state of ‘post-activation’, since TLR9 stimulation via CpG alone

could not induce low BCR responsiveness in HD B cells. However, decreased TLR9 activation was

observed, indicating that also this pathway is controlled during the state of B cell ‘post-activation’.

In addition, B cells expressing IGVH4-34 gene are suggested to be anergic, because they fail to induce

Ca2+ upon BCR stimulation [293], which is accompanied by increased pERK1/2(T202/Y204) expression

also observed in autoimmune type #4 M-CLL patient’s B cells [259-261]. However, the analysis of

pERK1/2(T202/Y204) expression in SLE and RA CD27- B cells and CD27+ memory B cells revealed

comparability to HD cells indicating that pERK1/2(T202/Y204) expression is not a suitable marker for

‘post-activation’.

7.5 Lymphocyte Hyporesponsiveness in Autoimmune Diseases is not Restricted to

B Cells

Within the presented study global PTP/PSP activities and expression of selected PTPs and PSPs of

T cells were investigated as a control to proof B cell specificity of the results. Indeed, PTP and PSP

activities of SLE, RA and pSS T cells were found comparable to HD and PTP/PSP genes exhibited only

marginal differential expression in SLE indicating normal T cell function. Interestingly, T cell

hyporesponsiveness has been reported in SLE, RA and pSS. In detail, responses of SLE CD8+ T cells

upon viral antigens are defective due to loss of the protein signaling lymphocytic activation molecule

family member 7 (SLAMF7) [294, 295]. McKinney et al. found CD8+ T cell exhaustion to be

characterized by low IL-7R and enhanced PD-1 expression in virus infections and SLE [296]. Tsokos

and colleagues found that T cells from SLE have functional abnormalities including impaired CD3ζ–

zeta chain of TCR associated protein kinase 70 (ZAP-70) signaling, as well as transcriptional changes

of serine/threonine-protein phosphatase 2A (PP2A) and reduced IL-2 and inversely increased IL-17

expression [297, 298]. T cells in the synovium of inflamed joints of RA patients display severe

hyporesponsiveness to antigenic stimulation characterized by impaired phosphorylation of the TCR

downstream molecule adaptor protein linker for activation of T cells (LAT) due to oxidative stress [299].

In pSS, reduced TH1 and TH2 Ca2+ responses are reported indicating a state of sustained reactivity

possibly due to ongoing immune response [300]. Thus, there might be distinctive mechanisms for

dysbalanced functions between B and T cells in these diseases.

7.6 Reduced BCR Signaling Can Play a Pathogenic Role in the Development,

Maintenance and Progression of Autoimmunity

BCR signaling quality is an essential key point for B cell fate and BCR hypersensitivity or

hyperresponsiveness is considered a major driver of tolerance brake and maintenance of autoimmunity

[15-17, 301]. This is contrary to the observed BCR hyporesponsiveness within the presented study.

However, the development and progression of autoimmunity has been linked to reduced BCR signaling,

too [302, 303]. This could be experimentally demonstrated in a diabetes mouse model in which Syk

was replaced by the less active Syk-related protein kinase Zap-70 in B cells, leading to disease

development. The authors hypothesized that reduced BCR signal transduction allows for positive

selection of auto- or polyreactive B cell clones and their survival due to chronic autoantigen stimulation

[302]. In this context, Schickel et al. demonstrated that inhibition of PTPN22 could reset central B cell

tolerance in non-obese diabetic scid gamma (NSG) mice which were engrafted with human

hematopoietic stem cells carrying a gain-of-function mutation of PTPN22 [303]. This indicates that B cell

hyporesponsiveness in autoimmune patients may promote persistence of autoreactive cells due to a

lower susceptibility to BCR-dependent elimination.

7.7 CD40 Co-Stimulation is a Critical Activator of ‘Post-Activated B Cells in SLE, RA

and pSS

This study demonstrated, that ‘post-activated’ B cells from SLE, RA and pSS patients are sensitive to

T cell help induced co-stimulation. Increase of BCR signaling and B cell proliferation could be induced

by CD40 co-stimulation. Furthermore, T cell help by CD40/IL-4R stimulation resulted in a reduced

expression of PTPs, like PTPN22, in B cells. These results may reflect a more persistent stimulation of

B cells by TFH cells. The latter one show enhanced expression in SLE, which positively correlate with

SLEDAI, serum IgG, ANA and anti-dsDNA antibody titers [304-307]. Upregulation of CD40 gene

expression in PTPN22 risk gene carriers is also consistent with the idea that this pathway is critical for

regulating the overly active immune system in autoimmunity [308]. Consistent with a prior study

showing that naive and memory B cell compartments fuel the pool of circulating ASCs in SLE due to

abnormal GC reaction [309], our study provides insights that this may be related to an increased

susceptibility of ‘post-activated’ SLE CD27- naive B cells to T cell help. Xu et al. found that in vitro

blocking of the T/B interaction by anti-CD40L led to decreased antibody production [307]. Furthermore,

Rao et al. reported an expanded population of non-exhausted ‘peripheral helper’ T (TPH) cells

characteristically expressing PD-1hiCXCR5-CD4+ in RA synovium [310]. Those TPH cells are thought of

playing a pathogenic role in promoting B cell responses and antibody production within inflamed tissues

and were recently found to correlated with severity of SLE. [310, 311]. The importance of T cell help in

autoimmunity is further emphasized by a gene set analysis of naive B cells from RA synovial tissues

revealed that CD40L responsive genes are significantly enriched [312]. In addition, it was recently

demonstrated that IL-21 promotes CD11chiT-bet+ B cell development, which are enriched for

autoreactive cells in SLE [264]. Thus, it is very likely that CD40 is a critical context-dependent co-

stimulatory molecule for the regulation of full BCR-dependent B cell activation. Autoreactive B cells (i.e.

9G4 B cells) are physiologically eliminated during the early stages of the GC reaction, potentially by

anergic responses of the BCR. However, it is hypothesized that cells might escape this anergic stage

and progress to memory and plasma cells [293]. In line with this, the data presented in this study as

well as the discussed data of increased T cell help in autoimmunity (see above), pointing in the direction

that abnormal CD40 stimulation of anergic SLE 9G4 B cells may let these cells pass this checkpoint.

The presented result that CD40 co-stimulation can render BCR susceptibility of autoimmune disease

‘post-activated’ B cells and CD40 co-stimulation of SLE B cells diminished the expression of e.g.

PTPN22 further support that modulation of the CD40 pathway is of critical importance.

7.8 Implications for Therapeutic Approaches

B cell directed therapies such as rituximab and belimumab have been approved and underscore the

role of B cells in these diseases [10, 196, 313, 314]. Given that reduced BCR signaling promotes

autoimmunity [302, 303], depletion of ‘post-activated’ B cells appears to be of therapeutic benefit in

autoimmune diseases. Belimumab targets the B cell lineage survival factor BAFF and mainly depletes

CD27- naive B cells which includes ‘post-activated’ CD27- B cells in SLE [10, 48, 196]. However,

memory B cells are not depleted and IgG autoantibody production is not affected by belimumab

treatment [10, 196]. Anti-CD20 Rituximab therapy depletes peripheral B cells [10]. First, immature

B cells repopulate the periphery, followed by plasma cells and naive B cells [315]. However,

repopulation of CD27+ memory B cells is delayed. This could imply that rituximab successfully depletes

‘post-activated’ CD27+ memory B cells. In this context, relapse of SLE after autologous stem cell

transplantation has been linked to prior recurrence of memory B cells [316]. Of note, targeting CD22 by

the therapeutic anti-CD22 antibody epratuzumab was thought to raise the threshold of BCR activation

by increasing SHP-1 activity and inhibiting Syk phosphorylation [110]. However, epratuzumab did not

show efficacy in phase III clinical trial [317]. This is likely related to B cell ‘post-activation’ of autoimmune

disease B cells. As ‘post-activation’ is characterized with low BCR induced Syk phosphorylation,

autoimmune disease B cells are not further accessible to CD22-induced inhibition.

The current results implicate that CD40 co-stimulation is critical for activation of ‘post-activated’ B cells

in autoimmune diseases such as SLE, RA and pSS. Accordingly, blocking CD40/CD40L interaction

could be of therapeutic benefit. Indeed, a therapeutic anti-CD40L antibody was tested and was able to

prohibit plasma cell and plasmablasts generation in SLE patients [318]. In addition, anti-CD40L

antibody improved SLEDAI score, reduced proteinuria and anti-dsDNA antibodies and increased

serum-C3 concentrations. However, clinical trials had to be stopped during phase I/II because of

serious Fc-related complications [319] and thrombotic effects [320]. Nevertheless, the therapeutic

approach is still under research and a monoclonal antibody with a PEGylated Fc part is currently under

clinical development for SLE [321]. Besides positive effects of the anti-CD40L antibody in SLE, data

presented and discussed in this work, implicate that beneficial effects of this therapy might also help in

other autoimmune diseases like RA and pSS.

7.9 Outlook

A deeper understanding of how ‘post-activation’ is regulated by phosphatases may open new

perspectives for the treatment of B cells in autoimmune diseases (Figure 23). The dysbalance of BCR

downstream kinase phosphorylation in autoimmune diseases is contradictory as Akt phosphorylation

depends on Syk activity but does not translate signaling strength. Furthermore, it is reported that Akt

feedback mechanisms in GC may negatively regulates BCR responses [322, 323]. Even though PSP

activities were found increased in SLE CD19+ B cells, this points into an alternative regulation pathway

of Akt signaling. This may be directed by PTEN and SHIP which play a role in anergy maintenance and

control of GC B cells responsiveness [287, 292, 322-324]. Increased PTEN expression is associated

with low PI(3,4,5)P3 production and may contribute to reduced BCR induced Ca2+ signals [292].

Reversely, the depletion of PTEN results in increased Ca2+ signals and anergy disruption and tolerance

breakdown [291]. SHIP-1 counterbalances PTEN activity by dephosphorylating PTEN generated

PI(3,4,5)P3. After BCR engagement it is recruited to the inhibitory co-receptor in a Syk depended

manner [325]. Furthermore, PTEN controls GC reaction by regulating the expression of IgD BCR [324]

which regulates IgM-induced anergy response in transitional and mature B cells [326]. This and the fact

that the composition of CD27- isotype switched B cells or switched and non-switched CD27+ memory

B cells, which were not analyzed in the presented study, can differ among autoimmune patients and

HD underlines the importance of analyzing isotype and subset specific signaling abnormalities in

autoimmune diseases [327]. Furthermore, the role of IgA positive B cells is of great interest as around

58 % of plasma blast are IgA+ indicating overactive involvement of the mucosomal immune system

[328].

Another field of interest may be checkpoint molecules such as cytotoxic T-lymphocyte-associated

protein 4 (CTLA-4), B- and T-lymphocyte attenuator (BTLA) and PD-1. Blockade of CTLA-4 and PD-1

was successful in antitumor therapy [329]. However, side effects such as autoimmune inflammation

indicate a molecular switch between developing cancer or autoimmunity [329]. Checkpoint molecules,

such as PD-1, can contain ITIM motifs recruiting downstream PTPs such as SHP-1 or SHP-2 to fulfil

their negative regulating functions [329] (Figure 23). However, no direct interaction of CTLA-4 and

SHP-1 was found [330]. Notably, PD-1 has been reported of being increased among SLE B cells and

may cause ‘post-activation’ [331]. Furthermore, PD-1 expression and the expression of its ligands, PD-

L1 and PD-L2, have been linked to TLR and type I interferon pathways and maybe to aryl hydrocarbon

receptor (AhR) pathways [332]. It is reported that PD-1 blockade can recover functionally impaired

hepatitis B-specific B cells in chronic hepatitis B infection [333]. Thus, indicating a potential mechanism

to release ‘post-activated’ B cells from their reduced functionality.

Figure 23: A complex interplay of phosphatases and kinases regulates BCR signaling. Syk phosphorylation is

counterbalanced by the negative feedback loop of SHP-1 recruitment to the ITIM region of the co-receptor CD22 [105, 106]. Akt

phosphorylation is induced after BCR engagement via Syk activity [95, 99]. The activity of Akt is balanced by a complex interplay

of PI3K, PTEN and SHIP-1 activity, which regulate the balance of phosphatidylinositol-4,5-biphosphate, phosphatidylinositol-

3,4,5-triphosphate and phosphatidylinositol-3,4-biphosphate [291, 292]. Checkpoint molecules such as PD-1 and BTLA recruit

the phosphatases SHP-1 and SHP-2 [329] and may play a role in the modulation of BCR downstream signaling. Finally, Ca2+-

and Akt-dependent transcription factors, such as NF-AT, NFκB, ERK, mechanistic target of rapamycin (mTOR) and forkhead box

protein O (FOXO), become active in dependence of the signal strength [100, 101, 139, 140].

A potential target for SHP-1 analysis is tyrosine residue Y564, which is indispensable for maximal

phosphatase activity and gets phosphorylated by Lyn upon DNA damage [334, 335]. Lyn also translate

early BCR signaling events indicating that BCR engagement promotes SHP-1(Y564) phosphorylation.

Indeed, pilot experiments on SHP-1(Y564) phosphorylation upon anti-IgG/IgM stimulation demonstrated

that SHP-1(Y564) gets phosphorylated in CD27- B cells and CD27+ memory B cells from HDs. Thus,

higher activity in CD27+ memory B cells making this phosphatase interesting as a target for further

analysis (Figure 24).

Figure 24: Enhanced phosphorylation of SHP-1(Y564) after BCR stimulation in CD27- and CD27+ memory B cells. PBMCs

were stimulated with anti-IgG/IgM for 5 min. (a) Phospho-SHP-1 in CD27- (left) and CD27+ memory (right) B cells after anti-

IgG/IgM stimulation (solid line) versus unstimulated control (dashed line). Unstimulated CD3+ lymphocides (grey area) and H2O2

(red line) were used as a secondary negative control and a positive control, respectively. (b) Baseline phosphorylation (left) and

anti-IgG/IgM stimulation (right) in CD27- B cells (solid line) and CD27+ memory B cells (dashed line).

PI3K consists of a regulatory and a catalytic subunit. PI3CD and PI3K p85 are mainly expressed in

lymphoid cells. Phosphorylation of the catalytic PI3CD(Y524) as well as regulatory PI3K p85(Y467)

subunit are connected to enzyme activity. Also, the regulatory subunit p55(Y199), which is expressed in

lymphoid cells, detects enzyme activity. However, phosphorylation after BCR engagement has not

been analyzed in the available literature. Both subunits, PI3CD(Y524) and p85(Y467)/p55(Y199), were

found to be phosphorylated after BCR as well as H2O2 positive control stimulation in CD27- B cells and

CD27+ memory B cells compared to unstimulated control. These preliminary experiments indicate

comparable phosphorylation of CD27- B cells and CD27+ memory B cells (Figure 25).

Figure 25: Enhanced phophorylatio of the PI3K subunits PI3CD(Y524) and p85(Y467)/p55(Y199) in CD27- B cells and CD27+

memory B cells. PBMCs were stimulated with anti-IgG/IgM for 5 min. (a) Phospho-PI3CD(Y524) in CD27- B cells (left) and CD27+

memory B cells (right) upon stimulation with anti-IgG/IgM (solid line) and unstimulated (dashed line). Grey area represents CD3+

lymphocytes and the red line indicates H2O2 positive control. (b) Phosphorylation of PI3CD(Y524) in CD27- B cells (solid line) and

CD27+ memory B cells (dashed line) under unstimulated (left) and stimulated (right) conditions. (c) PI3K p85(Y467)/p55(Y199)

phosphorylation was analyzed under the same experimental conditions. Stimulation (solid line) and unstimulated (dashed line)

conditions of CD27- B cells (left) and CD27+ memory B cells (right) as well as CD3+ lymphocytes (grey area) and H2O2 positive

control are shown. (d) Comparison of CD27- B cells (solid line) and CD27+ memory B cells (dashed line) under unstimulated and

stimulated conditions.

In these preliminary studies, commercially available SHP-1(Y564) and PI3K p85(Y467)/p55(Y199)

antibodies were labeled with AF488. However, a lack of labeling efficiency, and therefore, a lack of

functional antibody for flowcytometric analysis makes the development of new tools or antibodies

indispensable for detailed analysis.

Furthermore, a deeper understanding of signaling crosstalk between the BCR and CD40 pathway may

shed light on how T cell help can activate ‘post-activated’ B cells in autoimmunity. This crosstalk

involves MAPK signaling in addition to NFκB signaling. An interesting target would be ERK, as BCR

induced ERK phosphorylation is enhanced by CD40 treatment [336]. Further targets of interest involve

DOCK8 and TRAF-2 [59]. TRAF-2(Y484) phosphorylation is thought to be crucial for BCR and CD40

synergy and enhancement of the CD40 [27, 337]

8 Conclusion

In contrast to the generally accepted concept of hyperreactive BCR signaling in autoimmune diseases

[15, 16, 225], this study provides evidence on a commonly reduced BCR signal, measured by Syk(Y352)

and Btk(Y223) phosphorylation, in autoimmune diseases such as SLE, RA and pSS. This signaling

abnormality is characteristic of CD27+ memory B cells, but not CD27- B cells except for SLE. B cells

from SLE patients exhibited the strongest phenotype with reduced BCR signaling in CD27+ memory

B cells and CD27- B cells. Interestingly, this signaling abnormality does not extend to Akt signaling,

which was found normal in RA and pSS, as well as increased in SLE B cells. These results indicate a

complex and differential regulation of BCR downstream signaling pathways. As a potential mechanism,

constitutively increased recruitment of SHP-1 to the negative co-receptor CD22 in SLE, RA and pSS

B cells may result in increased dephosphorylation of Syk tyrosine residues. The strong phenotype

observed in SLE can be explained by maximal SHP-1/CD22 co-localization together with increased

PTP activities, which were uniquely found in SLE together with increased PSP activities. Notably, the

amplitude of BCR signaling in autoimmune disease CD27+ memory B cells was comparable to CD27-

B cells, indicating naive-like signaling properties. Importantly, reduced BCR signaling of autoimmune

disease B cells is not restricted to peripheral B cells but was also found in tissue resident B cells from

ITP spleens and pSS parotid gland. Moreover, B cell hyporesponsiveness towards TLR9 signals was

also observed in peripheral B cells from SLE, RA and pSS with reduced proliferation and differentiation

into ASCs. This abnormality is potentially linked to BCR hyporesponsiveness via Syk activity. Those

B cell abnormalities are likely to reflect continuous stimulation through the BCR in vivo without

appropriate co-stimulation. and therefore, reflect a status of ‘post-activation’ which is functionally

comparable but not identical to anergy. CD40 co-stimulation resulted in a gain-of-responsiveness

towards BCR stimulation and increased B cell proliferation. The analysis of PTP expression under

CD40/IL-4R stimulation and unstimulated conditions was analyzed in two SLE patients and one HD as

a proof of concept. This analysis found that co-stimulation reduced gene expression of PTPs such as

PTPN22 in SLE.

Taken together, this study found peripheral as well as tissue resident CD27+ memory B cells in

autoimmune diseases remain in ‘post-activation’ with impaired BCR and TLR9 responsiveness. The

more extensive ‘post-activation’ status in SLE B cells is possibly related to stronger negative regulation

by increased phosphatase activity. This ‘post-activation’ functionally related to anergy likely owing to

in vivo engagement of the BCR without appropriate T cell-derived co-stimulation. CD40 stimulation of

B cells appears to be key for B cell activation in the autoimmune milieu in such a way that it improves

BCR responses and is critical to overcome ‘post-activation’. The presented findings support the idea

that CD40/CD40L interaction is of clinical relevance and the investigation of therapeutic options

interfering with this pathway to foster functional B cell anergy and decreased disease activity.

Figure 26: Reduced BCR and TLR9 responsiveness can be overcome by CD40 co-stimulation. Overview of the analyzed

signaling pathways. Molecules which were found with differential activity in all three autoimmune diseases are highlighted in red.

Molecules which were found with differential activity in SLE only are highlighted in light red. BCR engagement in autoimmune

diseases leads to reduced phosphorylation of the downstream signaling kinases Syk and Btk potentially leading to reduced Ca2+

flux and Ca2+-dependent transcription. However, BCR-dependent Akt signaling, which is normal in RA and pSS and increased in

SLE, is not affected by reduced Syk phosphorylation. These abnormalities are accompanied by increased PTP/PSP activity in

SLE and increased recruitment of SHP-1 to CD22 in SLE, RA and pSS indicating a potential regulatory mechanism. TLR9

induced proliferation, differentiation and cytokine production [22] is reduced in autoimmune diseases, which is potentially

connected to a general reduced Syk activity. However, CD40 does not show any abnormality in terms of reduced signaling and

is able to overcome or increase the reduced responsiveness by the BCR and TLR9.

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10 Tables and Figures

10.1 Table of Main Figures

Figure 1: Analysis of Siglec-1 expression on CD14+ monocytes (gating strategy). ............................ 43

Figure 2: Analysis of intracellular kinases within CD27- B cells and CD27+ memory B cells. ............. 44

Figure 3: Analysis of intracellular targets in CD27- B cells and CD27+ memory B cells. .................... 45

Figure 4: Analysis of CD19+ B cells after in vitro stimulation (gating strategy). .................................. 50

Figure 5: Enhanced PTP and PSP activities in SLE B cells and enhanced baseline colocalization of

SHP-1 with CD22 in B cells from patients with SLE, RA and pSS. ...................................................... 56

Figure 6: Comparable baseline expression and phosphorylation of BCR downstream kinases in SLE,

RA and pSS patients compared to HDs. .............................................................................................. 58

Figure 7: Reduced anti-IgG/IgM induced Syk(Y352) phosphorylation kinetics in SLE, RA and pSS

CD27+ memory B cells and SLE CD27- B cells. ................................................................................... 60

Figure 8: Reduced anti-IgG/IgM induced Btk(Y223) phosphorylation kinetics in SLE, RA and pSS CD27+

memory B cells. .................................................................................................................................... 61

Figure 9: Increased anti-IgG/IgM induced Akt(S473) phosphorylation kinetics in SLE CD27- and CD27+

memory B cells compared to HDs. ....................................................................................................... 62

Figure 10: Reduced anti-IgG/IgM induced Syk(Y352) phosphorylation kinetics in splenic B cells from

ITP patients compared to non-ITP patients. ......................................................................................... 64

Figure 11: Comparable baseline phosphorylation of ERK1/2(T202/Y204) in SLE, RA and HDs............ 65

Figure 12: Increased Siglec-1 expression in SLE and pSS does not correlate with pSyk(Y352)

phosphorylation at 5 min of anti-IgG/IgM stimulation. .......................................................................... 66

Figure 13: Comparable methylation pattern of HD, SLE, RA and pSS B cells. .................................. 68

Figure 14: Reduced pSyk(Y352) in CD27- B cells and CD27+ memory B cells upon chronic IgG/IgM

stimulation. ............................................................................................................................................ 70

Figure 15: Comparable Syk(Y352) phosphorylation with and without anti-CD40 coating. ................... 71

Figure 16: Reduced frequencies of CD27+ memory B cells after co-culture with hCD40L L cells. ..... 73

Figure 17: Increased Syk(Y352) phosphorylation upon co-stimulation with CD40L cross-linking kit. .. 74

Figure 18: Increased anti-IgG/IgM induced Syk(Y352) phosphorylation after CD40 co-stimulation in HD,

SLE, RA and pSS CD27- and CD27+ memory B cells. ......................................................................... 76

Figure 19: Less ASC differentiation of SLE, RA and pSS B cells upon TLR9 stimulation. ................. 78

Figure 20: Less TLR9 induced ASC differentiation upon Syk inhibition. ............................................. 79

Figure 21: Decreased proliferation of SLE B cells upon TLR9 stimulation and comparable proliferation

of SLE, RA, pSS and HD B cells upon CD40 stimulation or combined IgG/IgM stimulation. .............. 81

Figure 22: Receptor-type PTPs show reduced expression upon CD40/IL-4R co-stimulation. ........... 82

Figure 23: A complex interplay of phosphatases and kinases regulates BCR signaling. ................... 93

Figure 24: Enhanced phosphorylation of SHP-1(Y564) after BCR stimulation in CD27- and CD27+

memory B cells. .................................................................................................................................... 94

114

Figure 25: Enhanced phophorylatio of the PI3K subunits PI3CD(Y524) and p85(Y467)/p55(Y199) in CD27-

B cells and CD27+ memory B cells. ..................................................................................................... 95

Figure 26: Reduced BCR and TLR9 responsiveness can be overcome by CD40 co-stimulation. ..... 97

10.2 Table of Supplementary Figures

Supplementary Figure 1: Standard curves for 27plex and IL-21 serum concentration analysis. ... 116

Supplementary Figure 2: Comparable PTP and PSP activities between SLE, RA, pSS and HD in

CD3+ T cells. ...................................................................................................................................... 117

Supplementary Figure 3: Cytokine expression profile of human serum from HDs, SLE, RA and pSS

patients. .............................................................................................................................................. 120

Supplementary Figure 4: Reduced pSyk(Y352) in CD27+ memory B cells after 5 min anti-IgG/IgM

stimulation does not correlate with serum cytokine expression. ........................................................ 122

Supplementary Figure 5: Syk(Y352) phosphorylation in HD CD27- B cells and CD27+ memory B cells

remains stable upon co-stimulation with IFNα, IFNγ, IL-2, IL-6 and IL-10. ........................................ 124

Supplementary Figure 6: Syk and Syk(Y352) expression upon co-stimulation with CD40L, IL-4 and IL-

21 and combinations thereof in HD, SLE, RA and pSS cells without anti-IgG/IgM stimulation. ........ 125

Supplementary Figure 7: Common expression of PP2 and PP2C family genes upon CD40L/IL-4 co-

stimulation in SLE and HD CD19+ B cells. ......................................................................................... 126

10.3 Table of Tables

Table 1: Gender, mean age, ethnicity, disease activity score and medication of blood donors. ........ 37

Table 2: Age, disease and gender of spleen, tonsil and parotid donors. ............................................ 38

Table 3: Consumables with supplier. .................................................................................................. 38

Table 4: Chemicals and commercially available buffers. .................................................................... 39

Table 5: Commercial kits. .................................................................................................................... 40

Table 6: Buffer, media and preparations. ............................................................................................ 40

Table 7: Antigens, conjugates, clones and supplier of the applied antibodies. ................................... 40

Table 8: Stimulation reagents, inhibitors and cytokines. ..................................................................... 41

Table 9: Cell lines. ............................................................................................................................... 42

Table 10: Electronic devices. ............................................................................................................... 42

Table 11: Applied software .................................................................................................................. 42

Table 12: Web addresses of open source programs used for RNA-Sequencing analysis ................. 52

10.4 Table of Supplementary Tables

Supplementary Table 1: Supplier information ................................................................................. 115

Supplementary Table 2: Serum cytokine concentrations (pg/ml) in HD and SLE serum samples . 118

Supplementary Table 3: Serum cytokine concentrations (pg/ml) in RA and pSS serum samples . 119

Supplementary Table 4: List of differentially methylated CpG sides ............................................... 123

115

11 Appendix

Supplementary Table 1: Supplier information

Supplier

Location

BD Bioscience

Franklin Lakes, New Jersey. United States

BioLegend

San Diego, California, United States

Bioss Antibodies

Woburn, MA, United States

Bio-Rad Laboratories

Hercules, California, United States

Biozym Scientific GmbH

Hessisch Oldendorf, Germany

Corning Inc.

Corning, New York, United States

eBioscience/Thermo Fisher

Carlsbad, California, United States

Eppendorf AG

Hamburg, Germany

Fisher scientific/Thermo Fisher

Carlsbad, California, United States

GE Healthcare

Chalfont St Giles, Great Britain

gibco by life technologies/Thermo Fisher

Carlsbad, California, United States

GraphPad Software

La Jolla, California, United States

Greiner Bio-One International GmbH

Kremsmünster, Austria

Invitrogen/Thermo Fisher

Carlsbad, California, United States

Jackson ImmunoResearch

West Grove, Florida, United States

MDS Nordion

Ottawa, Canada

Merck KGaA

Darmstadt, Germany

Miltenyi Biotec GmbH

Bergisch Gladbach, Germany

Molecular Probes/Thermo Fisher

Carlsbad, California, United States

PeproTech

Rocky Hill, New Jersey, United States

Qiagen

Venlo, Netherlands

Sarstedt AG & Co. KG

Nümbrecht, Germany

Scantibodies Laboratory

Santa fee, California, United States

Selleck Chemicals

Houston, Texas, United States

Sigma-Aldrich

St. Louis, Missouri, United States

TreeStar

Ashland, Oregon, United States

VWR International GmbH

Darmstadt, Germany

116

Supplementary Figure 1: Standard curves for 27plex and IL-21 serum concentration analysis. For the analysis of

cytokine concentrations in human serum samples standard curves for IL-1β, IL-1Ra, IL-2, IL-4, IL-5, IL-6, IL-7 IL-8, IL-9, IL-

10, IL-12(p70), IL-13, IL-15, IL-17, Eotaxin, FGF basic, G-CSF, GM-CSF, IFNγ, IP-10, MCP-1(MCAF), MIP-1a, MIP-1b,

PDGF bb, RANTES, TNFα, VGEF and IL-21 were calculated. Graphs show blank subtracted fluorescence intensities (FIs)

versus diluted standard concentrations (Michales-Menten fit, bars indicate SD).

117

Supplementary Figure 2: Comparable PTP and PSP activities between SLE, RA, pSS and HD in CD3+ T cells. CD3+

T cells from HDs (grey), SLE (red), RA (blue) and pSS (green) were analyzed for their (a) PTP (n(HD/SLE/RA/pSS) =

14/10/4/10)) and (b) PSP activities (n(HD/SLE/RA/pSS) = 13/9/4/9)) Box whisker plots represent the median (line), mean

(plus) and the range (whiskers).

118

Supplementary Table 2: Serum cytokine concentrations (pg/ml) in HD and SLE serum samples

Donors

Cytokines

(pg/ml)

HD SLE

1 2 3 4 5 6 7 8 9 10 1 2 3 4

IL-1β 2 ↓ 3 2 2 2 2 2 2 2 2 3 3 6

IL-1Ra 93 37 76 76 79 65 100 72 100 90 72 93 148 315

IL-2 ↓ ↓ ↓ ↓ 1 ↓ ↓ 1 1 1 2 1 2 4

IL-4 3 ↓ 3 3 4 ↓ 3 2 3 3 3 2 5 8

IL-5 ↓ ↓ ↓ 5 5 ↓ 6 5 5 3 ↓ 6 5 11

IL-6 ↓ ↓ ↓ ↓ ↓ ↓ ↓ ↓ ↓ ↓ ↓ ↓ 5 9

IL-7 ↓ ↓ ↓ ↓ ↓ ↓ 11 ↓ ↓ 20 ↓ 10 ↓ 20

IL-8 6 ↓ 6 ↓ 18 7 7 ↓ 6 8 7 10 9 20

IL-9 21 10 21 10 24 15 24 16 14 27 20 33 19 28

IL-10 6 ↓ 6 ↓ 3 4 5 4 9 6 ↓ 12 18 41

IL-12(p70) 20 ↓ 20 ↓ 12 15 16 14 23 19 ↓ 44 29 80

IL-13 ↓ ↓ 15 9 22 24 17 8 8 15 ↓ 10 12 21

IL-15 ↓ ↓ ↓ ↓ ↓ ↓ ↓ ↓ ↓ ↓ ↓ ↓ ↓ ↓

IL-17 ↓ ↓ 75 99 ↓ ↓ 89 ↓ 113 195 99 166 588 1613

IL-21 ↓ ↓ ↓ ↓ ↓ ↓ ↓ ↓ ↓ ↓ ↓ ↓ ↓ ↓

Eotaxin 102 143 137 176 172 141 326 288 437 215 46 88 537 260

FGF basic ↓ ↓ ↓ 18 ↓ ↓ 9 11 22 42 27 42 18 143

G-CSF ↓ ↓ ↓ ↓ ↓ ↓ ↓ ↓ ↓ ↓ ↓ 133 151 368

GM-CSF 18 9 14 19 17 18 21 18 25 41 18 37 47 147

IFN-γ 109 ↓ 109 ↓ 132 ↓ 142 97 103 121 85 121 153 348

IP-10 861 1415 868 556 844 1531 2187 1387 1261 1321 2458 ↑ 972 2312

MCP-1(MCAF) 19 24 ↓ 34 60 36 54 88 94 120 75 28 21 44

MIP-1a ↓ 1 2 2 4 1 2 2 4 2 8 4 3 6

MIP-1b 15 29 25 15 17 16 27 24 13 65 27 54 23 26

PDGF bb 1281 1010 1129 1218 1516 619 2017 267 1221 7829 2282 4286 1557 922

RANTES 379 570 850 835 385 469 1035 1387 652 ↑ 2163 ↑ 1031 1208

TNF-α 221 157 112 179 168 200 200 200 231 241 168 280 355 682

VEGF 74 13 86 ↓ 42 90 35 55 162 105 12 332 143 178

↓ below standard curve; ↑ above standard curve

119

Supplementary Table 3: Serum cytokine concentrations (pg/ml) in RA and pSS serum samples

Donors

Cytokines

(pg/ml)

RA pSS

IL-1β 2 2 3 2 3 4 2 2 2 2 2 3 3 2 4 3

IL-1Ra 79 100 104 79 114 104 62 58 65 ↓ 86 124 128 90 104 100

IL-2 1 ↓ 2 1 1 1 ↓ ↓ 1 ↓ ↓ 2 2 ↓ 2 1

IL-4 3 3 4 3 4 4 3 2 3 3 3 4 5 2 5 4

IL-5 3 5 5 ↓ 7 7 ↓ ↓ 5 4 ↓ 5 9 5 10 9

IL-6 ↓ 16 12 7 ↓ 9 ↓ ↓ 10 ↓ ↓ ↓ ↓ 6 6 6

IL-7 ↓ ↓ ↓ ↓ 13 19 ↓ ↓ ↓ ↓ ↓ ↓ 10 ↓ ↓ ↓

IL-8 ↓ 7 7 19 7 11 ↓ ↓ 7 ↓ 9 33 19 29 8 16

IL-9 18 22 44 17 17 29 12 12 17 15 17 23 33 13 31 37

IL-10 6 6 9 7 8 6 4 3 3 3 5 5 12 10 15 8

IL-12(p70) 19 30 36 29 19 20 22 12 15 15 20 23 26 33 43 32

IL-13 8 8 11 6 14 9 7 11 10 6 11 11 12 10 38 27

IL-15 ↓ ↓ ↓ ↓ ↓ ↓ ↓ ↓ ↓ ↓ ↓ ↓ ↓ ↓ ↓ ↓

IL-17 80 59 99 75 37 140 89 ↓ 70 70 64 80 174 131 278 227

IL-21 ↓ ↓ ↓ ↓ ↓ ↓ ↓ ↓ ↓ ↓ ↓ ↓ ↓ ↓ ↓ ↓

Eotaxin 98 205 234 461 443 443 27

253 358 438 373 497 345 193 233

FGF basic 20 27 ↓ ↓ 24 27 ↓ ↓ 17 12 9 15 14 18 42 24

G-CSF ↓ ↓ ↓ ↓ ↓ 139 ↓ ↓ ↓ ↓ ↓ ↓ 151 ê 160 123

GM-CSF 24 14 21 15 21 30 15 10 18 3 15 22 24 16 52 32

IFN-γ 109 91 85 109 153 153 ↓ ↓ 109 ↓ 109 153 193 85 221 163

IP-10

119

477

219

123

162

358

199

146

208

176

194

453

907

288

847

MCP-1(MCAF) ↓ 82 70 86 115 41 76 54 32 47 93 65 40 211 52 59

MIP-1a 3 1 2 5 3 6 2 2 4 2 4 16 6 3 1 3

MIP-1b 22 18 21 19 ↓ 34 14 15 14 13 20 36 71 46 38 52

PDGF bb

177

209

128

147

570

285

129

124

236

109

233

736

117

301

321

RANTES 672 582 477 686 329 938 680

676 649 333 781 898

112

↑

189

TNF-α 157 221 ↓ 231 318 318 157

112 200 280 290 241 135 299 261

VEGF 93 101 88 95 44 59 77 30 32 51 61 110 122 178 283 139

↓ below standard curve; ↑ above standard curve

120

Supplementary Figure 3: Cytokine expression profile of human serum from HDs, SLE, RA and pSS patients.

Concentrations of the cytokines IL-1β, IL-1Ra, IL-2, IL-4, IL-5, IL-6, IL-7,IL-8,IL-9, IL-10, IL12(p70), IL-13, IL-15, IL-17,

Eotaxin, FGF basic, G-CSF, GM-CSF, IFNγ, IP-10, MCP-1(MCAF), MIP-1a, MIP-1b, PDGF bb, RANTES, TNFα and VEGF

were analyzed from SLE, RA, pSS and HD serum samples (n(HD/SLE/RA/pSS) = 10/4/6/10). Values ranging in the upper

(≥ 75 %), upper middle (≥ 50 %), lower middle (≥ 25 %) and lower (< 25 %) quartile are represented in dark red, light red,

light grey and black, respectively. Values below (black arrows down) or above (red arrows up) the detection limit are

indicated.

121

122

Supplementary Figure 4: Reduced pSyk(Y352) in CD27+ memory B cells after 5 min anti-IgG/IgM stimulation does not

correlate with serum cytokine expression. Cytokine expression was quantified in human serum from SLE (red), RA (blue)

and pSS (green) patients and compared to HDs (black). Cytokine concentrations were correlated with pSyk(Y352) in CD27+

memory B cells after 5 min of anti-IgG/IgM stimulation. Only data within the range of standard curves are shown and

analyzed. Horizontal lines indicate the mean. Linear regression lines, coefficients of determination (R2) and Pearson’s

correlation coefficients (r) are indicated in the figure (one-way ANOVA with DMCT; linear regression; Person’s correlation;

* p ≤ 0.05, ** p 0.01).

123

Supplementary Table 4: List of differentially methylated CpG sides

Cg ID

Gene ID

Region Annotation

Chromosome

Start

Stop

cg06872964

IFI44L

TSS1500

chr1

79085250

79085251

cg03607951

IFI44L

TSS1500

chr1

79085586

79085587

cg17980508

IFI44L

TSS1500

chr1

79085713

79085714

cg00855901

IFI44L

TSS1500

chr1

79085765

79085766

cg05696877

IFI44L

5'UTR

chr1

79088769

79088770

cg07285983

RABGAP1L

body; TSS200

chr1

174844490

174844491

cg06188083

IFIT3

body; body

chr10

91093005

91093006

cg05552874

IFIT1

body

chr10

91153143

91153144

cg04582010

IFITM1

TSS1500

chr11

313120

313121

cg09026253

IFITM1

TSS1500

chr11

313267

313268

cg01971407

IFITM1

TSS1500

chr11

313624

313625

cg23570810

IFITM1

body

chr11

315102

315103

cg21686213

IFITM1

3'UTR

chr11

315118

315119

cg03038262

IFITM1

3'UTR

chr11

315262

315263

cg20045320

IFITM3

downstream

chr11

319555

319556

cg09122035

IFITM3

downstream

chr11

319667

319668

cg17990365

IFITM3

2nd exon

chr11

319718

319719

cg25674027

PAH

upstream

chr12

103325781

103325782

cg27056740

MIR300

body

chr14

101507727

101507728

cg07839457

CETP

TSS1500

chr16

57023022

57023023

cg01028142

CMPK2

body

chr2

7004578

7004579

cg10959651

RSAD2

1st exon

chr2

7018020

7018021

cg10549986

RSAD2

1st exon

chr2

7018153

7018154

cg17283620

HAAO

body

chr2

43013772

43013773

cg26312951

MX1

TSS200; 5'UTR

chr21

42797847

42797848

cg21549285

MX1

5'UTR

chr21

42799141

42799142

cg14293575

USP18

5'UTR

chr22

18635460

18635461

cg20098015

ODF3B

TSS200

chr22

50971140

50971141

cg22930808

PARP9

5'UTR

chr3

122281881

122281882

cg08122652

PARP9

5'UTR

chr3

122281939

122281940

cg00959259

PARP9

5'UTR

chr3

122281975

122281976

cg05994974

PARP12

body

chr7

139761087

139761088

cg14864167

PDE7A

body

chr8

66751182

66751183

Interferon-induced protein 44-like (IFI44L), Rab GTPase-activating protein 1-like (RABGAP1L), interferon-induced protein

with tetratricopeptide repeats (IFIT), interferon-induced transmembrane protein (IFITM), phenylalanine-4-hydroxylase

(PAH), microRNA (MIR), cholesteryl ester transfer protein (CETP), UMP-CMP kinase 2, mitochondrial (CMPK2), radical S-

adenosyl methionine domain-containing protein 2 (RSAD2), 3-hydroxyanthranilate 3,4-dioxygenase (HAAO), interferon-

induced GTP-binding protein Mx1 (MX1), Ubl carboxyl-terminal hydrolase 18 (USP18), outer dense fiber protein 3B

(ODF3B), poly [ADP-ribose] polymerase (PARP), high affinity cAMP-specific 3',5'-cyclic phosphodiesterase 7A (PDE7A),

transcription start site (TSS)

124

Supplementary Figure 5: Syk(Y352) phosphorylation in HD CD27- B cells and CD27+ memory B cells remains stable

upon co-stimulation with IFNα, IFNγ, IL-2, IL-6 and IL-10. HD PBMCs were incubated for 48 h with RPMI as unstimulated

control or (a) IFNα, IL-21, IFNα together with IL-21, (b) IFNγ, IL-21, IFNγ together with IL-21 and (c) IL-2, IL-6, IL-10 and

subsequently stimulated with anti-IgG/IgM (black) or RPMI (pink) for 5 min. Phoso-Syk(Y352) was analyzed in CD27- (dots)

and CD27+ memory (circles) B cells. Horizontal lines represent the mean ± SD.

125

Supplementary Figure 6: Syk and Syk(Y352) expression upon co-stimulation with CD40L, IL-4 and IL-21 and

combinations thereof in HD, SLE, RA and pSS cells without anti-IgG/IgM stimulation. HD (black), SlE (red), RA (blue)

and pSS (green) PBMCs were incubated with IL-4, IL-21, CD40L alone or combinations thereof for 48 h and analyzed for

Syk and pSyk(Y352) expression. (a) Phospho-Syk(Y352) and (b) Syk MFI in CD27- B cells (filled boxes) and CD27+ memory

B cells (blank boxes) with (n(HD/SLE/RA/pSS) = 11/7/5/5) and without co-stimulation (n(HD/SLE/RA/pSS) = 30/18/16/15).

Within the Box whisker plots the median (line), mean (plus) and range (whiskers) are represented (repeated measures

ANOVA with DMCT, # p ≤ 0.05, ## p ≤ 0.01, ### p ≤ 0.001).

126

Supplementary Figure 7: Common expression of PP2 and PP2C family genes upon CD40L/IL-4 co-stimulation in

SLE and HD CD19+ B cells. Differential expression of selcted PSP PP2 and PP2C family genes was analyzed from publicly

available data (lines 1-4) and upon co-stimulation with CD40L/IL-4 (lines 4-7). Data show SLE vs. HD CD20+ B cells (6 SLE,

7 HD), MS vs. HD CD19+ B cells (10 MS, 10 HD), SLE vs. HD CD4+ (53 SLE, 41 HD) and CD8+ T cells (22 SLE, 31 HD)

and differential gene expression from un-stimulated SLE vs. HD and CD40L/IL-4 stimulated for SLE vs. un-stimulated SLE

or HD CD19+ B cells, respectively (n(HD/SLE) = 1/2).

127

12 Publications, Presentations and Poster

2020

Article: Aue, A., Szelinski, F., Weißenberg S. Y., Wiedemann, A., Rose T., Lino A. C., Dörner T. 2020.

“Elevated STAT1 expression but not phosphorylation in lupus B cells correlates with disease activity

and increased plasmablast susceptibility”. Rheumatology (Oxford).

2019

Article: Weißenberg, S. Y., Szelinski, F., Schrezenmeier, E., Stefanski, A. L., Wiedemann, A., Rincon-

Arevalo, H., Welle, A., Jungmann, A., Nordstrom, K., Walter, J., Imgenberg-Kreuz, J., Nordmark, G.,

Ronnblom, L. Bachali, P., Catalina, M. D., Grammer, A. C., Lipsky, P. E., Lino, A. C. & Dörner, T. 2019.

„Identification and Characterization of Post-activated B Cells in Systemic Autoimmune Diseases”. Front

Immunol, 10, 2136.

Article: Schrezenmeier, E., Weißenberg, S. Y., Stefanski, A. L., Szelinski, F., Wiedemann, A., Lino, A.

C., Dorner, T. 2019. „Postactivated B cells in systemic lupus erythematosus: update on translational

aspects and therapeutic considerations”. Curr Opin Rheumatol, 31, 175-184.

2017

Poster: Weißenberg, S. Y., Szelinski F., Dörner, T. “Altered B Cell Receptor Signaling in Patients with

Systemic Lupus Erythematosus and Primary Sjögren‘s Syndrome”, 6th DGfI Translational Immunology

School, 2017, Potsdam.

2016

Poster: Weißenberg, S. Y., Fleischer, S. J., Dörner, T. „B Cell Receptor Signaling is Imbalanced in

Patients with Systemic Lupus Erythematosus and Primary Sjögren‘s Syndrome“, 8th DGfI Autumn

School‚ 2016, Merseburg.

Poster: Wiedemann, A., Weißenberg, S. Y., Kruck, I., Fleischer, S. J., Reiter, K., Dörner, T. & Mei, H.

E. “Delineation of Human Plasma Cell Subsets And Their Bone Marrow Niche”, IMMUNOBONE Annual

Meeting 2016, Hamburg.

2015

Oral presentation about previous work on the project and recent publication: Mei, H. E., Wirries, I.,

Frölich, D., Brisslert, M., Giesecke, C., Grün, J. R., Alexander, T., Schmidt, S., Luda, K., Kühl, A. A.,

Engelmann, R., Dürr, M., Scheel, T., Bokarewa, M., Perka, C., Radbruch, A., Dörner, T. “Characteristics

of human CD19- Plasma Cells”, IMMUNOBONE Annual Meeting 2015, Dresden.

129

13 Acknowledgements

First, I thank Prof. Dr. Thomas Dörner for supervising me during my whole PhD time at the Charité-

Universitätsmedizin Berlin and DRFZ. Many thanks for providing the topic, the intellectual input, and

constructive discussions. Also, I thank Prof. Dr. Roland Lauster for supervision at the TU Berlin. I thank

the whole AG Dörner group for their great scientific and personal support during the whole time: Karin

Reiter, Dr. Ana-Luisa Stefanski, Dr. Eva Schrezenmeier, Dr. Thomas Rose, Dr. Sarah Fleischer, Annika

Wiedemann, Franziska Szelinski, Dr. Andreia Lino, Mariele Gatto, Hector Rincon-Arevalo, Anna Lisney,

Nadja Nomovi, Arman Aue, Cindy Schilling, Sylvia, Kirsten Langpap and Lindsay Serene. Thank you

for sharing your knowledge, providing help with sample acquisition and being there for all those

everyday problems. Thank you for the great time and the wonderful atmosphere in the lab! Special

thanks go to Franziska Szelinski for helping me out in the lab when I was handy capped. Also, many

thanks to Franziska Szelinski and Dr. Eva Schrezenmeier for sharing your knowledge and data about

phosphatases.

Many thanks go to the cooperation partners and co-authors of my first author research paper: The

collegues from the department of ‘medical sciences’ at the ‘rheumatology and science for life laboratory’

at Uppsala University (Uppsala, Sweden): Prof. Dr. Lars Rönnblom, Dr. Juliana Imgenberg-Kreuz and

Dr. Gunnel Nordmark; the department of ‘genetics and epigenetics’ at Saarland University

(Saarbrücken, Germany): Prof. Dr. Jörn Walter, Anna Welle, Annemarie Jungmann and Dr. Karl

Nordström; and the ‘RILITE research institute’ (Charlottesville, VA, USA): Dr. Peter E. Lipsky,

Prathyusha Bachali, Dr. Michelle D. Catalina and Dr. Amrie C. Grammer. Thank you for sharing your

data and doing the meta-analysis of epigenetic data sets and the analysis of the RNA sequencing data.

Everyone did a great job.

I thank Andreas Hutloff from the ‘chronic immune reactions’ group at the DRFZ (Berlin, Germany), who

kindly shared his knowledge and materials about CD40 stimulation on B cells. Also, the lab manager,

kitchen team and particularly Tuula Geske who tried everything to label the SHP-1 and PI3K antibodies.

Furthermore, I thank all collegues from der Charité clinic including physicians, surgeons, and nurses,

who helped with sample acquisition.

Thank you! It has been a pleasure working with you!

Last, but not least: I thank all patients and healthy volunteers. Without their kind donations, this work

would not have been possible. I thank Dr. Alexander Weißenberg for critical reading of this work. Special

thanks go to my family and friends for their great mental support.

131

14 Eidesstattliche Erklärung

Ich versichere, dass die vorliegende Arbeit mit dem Titel “CD40 Stimulation Activates ‘Post-Activated’

B cells which are Hyporesponsive to B Cell Receptor and Toll-like Receptor 9 Stimulation in

Autoimmunity”, von mir persönlich mittels der angegebenen Methoden, Hilfsmittel und Literatur erstellt

wurde. Beteiligungen von Kollegen und Kooperationspartnern sind an geeigneter Stelle erwähnt. Des

Weiteren gab es keine unzulässigen Hilfestellungen Dritter.

Ich versichere, dass ich bisher an keiner in- oder ausländischen Fakultät ein Gesuch auf Zulassung zur

Promotion, noch die vorliegende oder eine andere Arbeit zu Promotionszwecken eingereicht habe.

Ort, Datum, Unterschrift