Next Article in Journal
A Comparative Analysis of Strain and 2D Shear Wave Elastography in the Diagnosis of Autoimmune Thyroiditis in Pediatric Patients
Next Article in Special Issue
The Multifaceted Role of Osteopontin in Prostate Pathologies
Previous Article in Journal
Adult IDH Wild-Type Glioblastoma Ultrastructural Investigation Suggests a Possible Correlation between Morphological Biomarkers and Ki-67 Index
Previous Article in Special Issue
Plasma Osteopontin Reflects Tissue Damage in Acute Pancreatitis
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Biomedicines
Volume 11
Issue 7
10.3390/biomedicines11071969
biomedicines-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

A Dual Role of Osteopontin in Modifying B Cell Responses

by
Rittika Chunder
1,2,3,
Verena Schropp
1,2,3,
Manuel Marzin
4,
Sandra Amor
4,5 and
Stefanie Kuerten
1,2,3,*
1
Faculty of Medicine, Institute of Neuroanatomy, University of Bonn, 53115 Bonn, Germany
2
University Hospital Bonn, 53127 Bonn, Germany
3
Institute of Anatomy and Cell Biology, Friedrich-Alexander-Universität Erlangen-Nürnberg, 91054 Erlangen, Germany
4
Department of Pathology, Amsterdam University Medical Center, 1007 MB Amsterdam, The Netherlands
5
Institute of Anatomy, Rostock University Medical Center, 18057 Rostock, Germany
*
Author to whom correspondence should be addressed.
Biomedicines 2023, 11(7), 1969; https://doi.org/10.3390/biomedicines11071969
Submission received: 26 May 2023 / Revised: 6 July 2023 / Accepted: 7 July 2023 / Published: 12 July 2023
(This article belongs to the Special Issue 30 Years of OPN Milestones and Future Avenues 2.0)
Browse Figures
Review Reports Versions Notes

Abstract

:
The occurrence of B cell aggregates within the central nervous system (CNS) has prompted the investigation of the potential sources of pathogenic B cell and T cell responses in a subgroup of secondary progressive multiple sclerosis (MS) patients. Nevertheless, the expression profile of molecules associated with these aggregates and their role in aggregate development and persistence is poorly described. Here, we focused on the expression pattern of osteopontin (OPN), which is a well-described cytokine, in MS brain tissue. Autopsied brain sections from MS cases with and without B cell pathology were screened for the presence of CD20+ B cell aggregates and co-expression of OPN. To demonstrate the effect of OPN on B cells, flow cytometry, ELISA and in vitro aggregation assays were conducted using the peripheral blood of healthy volunteers. Although OPN was expressed in MS brain tissue independent of B cell pathology, it was also highly expressed within B cell aggregates. In vitro studies demonstrated that OPN downregulated the co-stimulatory molecules CD80 and CD86 on B cells. OPN-treated B cells produced significantly lower amounts of IL-6. However, OPN-treated B cells also exhibited a higher tendency to form homotypic cell aggregates in vitro. Taken together, our data indicate a conflicting role of OPN in modulating B cell responses.

1. Introduction

Multiple sclerosis (MS) is a chronic demyelinating disease of the central nervous system (CNS), which typically manifests in young adults. Although B cells are not the first responders of neuroinflammation, their dichotomous role, especially in the chronic stage of MS has gained increasing attention [1]. Ectopic lymphoid follicles (eLFs), which are a common feature of several chronic autoimmune diseases [2], have been detected in the meninges of some but not all secondary progressive MS patients [3,4,5]. More recent reports have demonstrated the presence of B cell aggregates in other stages of MS [6,7,8]. Furthermore, multiple lines of evidence suggest that the presence of B cell aggregates within the CNS tissue in MS patients positively correlates with a more severe disease pathology [9,10,11].
Nevertheless, there remains a crucial gap in our knowledge regarding the precise molecular and cellular landscape of these aggregates [12]. On the one hand, molecules expressed within the B cell aggregates that may function as positive regulators of disease [13] remain to be clearly defined. On the other hand, the identification of molecules that facilitate B cell aggregation [14,15,16] is an important step to specifically block those pathways that negatively affect the severity of disease progression.
In the current study, we set out to investigate the expression of SPP1—secreted phosphoprotein-1—an extracellular matrix (ECM) glyco-phosphoprotein also described as osteopontin (OPN) [17] within B cell aggregates in MS patients. OPN has been identified as the fifth most common transcript in MS brain tissue [18] and its role in several pathologic and inflammatory processes [19] has been described over the last decades. Furthermore, the involvement of OPN in T cell-mediated CNS pathology has been emphasized in different EAE models [20,21], and very recently, the role of OPN in controlling and compartmentalizing brain T cells has been suggested [22]. While OPN has also been implicated in several diseases with a B cell component [23,24], its expression within eLFs or B cell aggregates in MS patients is unknown.
To this end, we used immunohistochemistry to determine the expression of OPN in MS brain tissue that contained CD20+ B cell aggregates. In vitro, human recombinant OPN (rOPN) downregulated the co-stimulatory molecules CD80 and CD86 on human B cells from peripheral blood. Conversely, the stimulation of B cells with rOPN increased the number of B cell aggregates in vitro suggesting that OPN has opposing effects that may have an impact on the pathogenesis of B cell-mediated diseases.

2. Materials and Methods

2.1. Human Tissue

The MS brain sections used in this study were from the same cohort reported by Chunder et al. [25]. Paraffin-embedded brain tissue sections were received from the Multiple Sclerosis and Parkinson’s Tissue Bank, Center for Brain Sciences, Imperial College London (file number 258/14, approved by the Ethics Committee of the University of Würzburg), or from the Netherlands Brain Bank (NBB; co-ordinator Prof. I. Huitiga) in Amsterdam with approval of the Medical Ethics Committee of the Amsterdam UMC. All participants or the next of kin had given informed consent for an autopsy and the use of tissues for research purposes. MS brain samples from the NBB were selected from regions of interest (ROI) after ex vivo MRI for the detection of lesions. Tissue blocks containing the ROI were cut in half and half fixed in 10% formalin and embedded in paraffin while the other half was snap-frozen and stored in liquid nitrogen. General information on the patient samples is listed in Table 1. n = 16 MS patients including n = 7 patients with a high B cell pathology were included in the study. Synovial tissues from n = 3 patients with rheumatoid arthritis (RA) that were obtained from the Department of Rheumatology and Immunology of University Hospital Erlangen were also included in this study (file number 334_18B, approved by the Ethics Committee of the University Hospital Erlangen).

2.2. Immunohistochemistry

The protocol for immunohistochemical staining has been previously described by our group [25]. Briefly, following deparaffinization of the brain sections, heat-induced antigen retrieval was performed in 10 mM sodium citrate buffer (pH 6.0). Sections were washed with tris-buffered saline + 0.05% Tween 20 (TBS-T) between every incubation step. After blocking with 5% milk blocking buffer at room temperature for 1 h, tissue sections were incubated with primary antibodies diluted in 0.5% blocking buffer at 4 °C overnight. The appropriate secondary antibodies diluted in 0.5% blocking buffer were applied to the sections at room temperature for 2 h in the dark. Double stainings were carried out sequentially where the tissue sections were incubated with the second primary antibody for 3 h at room temperature following completion of the first staining. The corresponding secondary antibody was diluted as mentioned above and incubated at room temperature for 1 h. Human brain sections were finally mounted using Fluoroshield mounting medium containing 4′,6-diamidino-2-phenylindole (DAPI) (Abcam, Cambridge, UK). Every staining contained a secondary antibody-only control. Additionally, a rabbit polyclonal IgG control was used to confirm primary antibody binding specificity (Supplementary Figure S1). The primary and secondary antibodies that were used are listed in Table 2. Images were acquired using a Leica DM6 fluorescence microscope (Leica Microsystems, Wetzlar, Germany) equipped with Las X software (version 5.1.0, Leica Microsystems, Wetzlar, Germany).

2.3. B Cell Isolation and Cell Culture

For the in vitro B cell studies, blood was collected from healthy controls between the ages of 22 and 35. The study was performed pseudonymized and approved by the Ethics Committee of Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany (files 185_18B and 74_18B). Written informed consent was obtained from all volunteers.
The protocol used for isolating and culturing B cells has been previously described by our group [25]. Briefly, 30 mL of peripheral blood per person was collected using S-Monovette™ (Sarstedt Inc., Newton, MA, USA) tubes containing lithium heparin. Whole blood was incubated with RosetteSep™ Human B Cell Enrichment Cocktail (STEMCELL Technologies, Vancouver, BC, Canada) and purified by density centrifugation according to the manufacturer’s instructions. Isolated B cells were counted and resuspended in the appropriate B cell medium at a concentration of 150,000 cells/200 μL for all downstream applications. The B cell medium was prepared using Roswell Park Memorial Institute (RPMI)-1640 medium supplemented with 0.3 g/L L-glutamine, 10% fetal bovine serum (FBS) (ThermoFisher, Waltham, MA, USA), 1% penicillin/streptomycin (P/S), 50 μM β-mercaptoethanol, and 10 mM HEPES. An aliquot of 450,000 freshly isolated B cells was set aside for purity check by flow cytometry.
B cells that had a purity of >80% as determined by flow cytometry were cultured in the presence or absence of stimulation (15 ng/mL interleukin (IL)-2 (PeproTech, Rocky Hill, NJ, USA) and 1 μg/mL synthetic TLR 7/8 agonist R-848 (ENZO Life Sciences, Farmingdale, NY, USA)) in 96-well plates. B cells that were stimulated with IL-2 and R-848 are referred to as pre-stimulated B cells, which were incubated at 37 °C and 5% CO2 for 24 h before the addition of rOPN. Freshly isolated B cells, which did not receive any stimulation, are mentioned as unstimulated B cells and were directly incubated with rOPN. For every culture condition and all downstream applications, B cells from every donor were plated, measured, and analyzed in duplicates.

2.4. Stimulation of B Cells with rOPN

A dose-titrated amount of 2 μg/well (1 μg/mL) human rOPN (R&D Systems, Minneapolis, MN, USA) was added to pre-stimulated or unstimulated B cells, which were cultured for 40 h at 37 °C and 5% CO2. The amount of rOPN added to the B cells was optimized to 2 μg/well based on recommendations in the literature [26,27].

2.5. Flow Cytometry

2.5.1. Purity Check of B Cells

The purity of the enriched B cell population was measured by flow cytometry as previously described by us [25]. The isolated cell suspensions were incubated with BD Horizon® Fixable Viability Stain 780 (FVS780) (BD Biosciences, Franklin Lakes, NJ, USA) at 4 °C for 30 min in the dark. Cells were then washed, centrifuged, and incubated with anti-human anti-CD19 and anti-CD45 antibodies at 4 °C in the dark for 30 min. Following a washing step, cells were resuspended in an appropriate volume of FACSFlow™ (BD Biosciences) for measurement of the samples. Data were acquired on a CytoFLEX S flow cytometer (Beckman Coulter, Brea, CA, USA) equipped with CytExpert software (version 2.2, Beckman Coulter, Brea, CA, USA), and analysis was performed with FlowJo software (version 10.8.0, BD Biosciences, Franklin Lakes, NJ, USA). A table corresponding to the B cell purities from the different donors used in this study is shown in Supplementary Table S1.

2.5.2. B Cell Activation

To check the activation status of pre-stimulated or unstimulated B cells that were treated with human rOPN for 40 h, the following cell surface markers were used: CD3, CD20, CD80, and CD86. Live cells were discriminated from dead ones using FVS780. Staining was performed as described above. The gating strategy used for the measurement of B cell activation status has been previously described by our group [25] and is shown in Supplementary Figure S2. Unstained, isotype staining controls and fluorescence minus one (FMO) samples were included.
Cases where either rOPN-treated or untreated B cells showed a coefficient of variation (CV) higher than 20% between the technical replicates for any condition were excluded from the analysis. Materials and methods with an overlap between the current manuscript and that reported in Chunder et al. [25] have been summarized in Supplementary Figure S3.

2.6. Antibody Array and ELISA

To investigate the cytokine secretion profile of pre-stimulated B cells after incubation with rOPN, a human cytokine antibody array kit with 23 targets (Abcam) was used (Supplementary Figure S4). An equal volume of culture supernatant from either rOPN-treated or untreated pre-stimulated B cells was used for the array and the assay was performed according to the manufacturer’s instructions. The integrated density of the dot blots was analyzed using Image J (NIH). Based on the preliminary findings using the antibody array, quantitative analysis of IL-6 and IL-10 was performed on the B cell culture supernatant. Both ELISAs were performed as per the manufacturer’s protocol (ThermoFisher, Waltham, MA, USA).

2.7. Aggregation Assay

Aggregation assays using purified B cells were performed as described earlier [28]. Briefly, pre-stimulated B cells that were treated with rOPN for 40 h were incubated with mouse anti-human CD19 at a concentration of 1 μg/mL for 2 h at 37 °C and 5% CO2. Mouse anti-human IgG1 was used as an isotype control antibody. Five images were acquired from each well using a Leica DMIL LED microscope (Leica Microsystems, Wetzlar, Germany). B cell aggregation was quantified with Fiji (version 2.3.1, National Institutes of Health (NIH), Bethesda, MD, USA), with at least three images/well included in the analysis. Images/wells where a bubble or the edge of the well was photographed were excluded from the analysis.

2.8. Statistical Analysis

Statistical analysis was performed using GraphPad Prism (version 8.0, GraphPad Software Inc., San Diego, CA, USA). A Shapiro–Wilk normality test was used to test the Gaussian distribution of every dataset. Differences between parametric groups were assessed using either a t test or a one-way ANOVA, while for non-parametric datasets, the Wilcoxon test was used. The level of significance was set at 5%.

3. Results

3.1. OPN Is Expressed within B Cell Aggregates in Human Tissues

We checked for the expression pattern of OPN in MS brain sections from a cohort of patients that had already been characterized by our group [25]. As expected, the expression of OPN was not limited to sections with a prominent B cell pathology (Figure 1A). Tissue sections from patients that were positive only for T cells (CD3+ staining) and those without any CD3/CD20 staining (“No T cell and B cell” infiltration) also expressed high amounts of OPN. However, the results also demonstrated that this molecule is strongly expressed within CD20+ B cell aggregates (Figure 1B). Furthermore, we confirmed previous findings [29] using synovial tissue from RA patients to demonstrate that OPN is also expressed within B cell aggregates in the periphery (Figure 1C). Control stainings are shown in Supplementary Figure S1.

3.2. B Cells Treated with OPN Downregulate the Co-Stimulatory Molecules CD80 and CD86

Having shown that OPN is expressed within B cell aggregates, we wanted to investigate whether it had any effect on the activation status of B cells. To demonstrate the influence of OPN on B cells, we studied the expression pattern of CD80 and CD86 as two co-stimulatory molecules that are expressed on activated B cells and also play a crucial role in T cell activation [30,31]. Unstimulated peripheral blood B cells from n = 6 healthy donors treated with human rOPN for 40 h in culture significantly downregulated CD80 (p = 0.027) as determined by flow cytometry (Figure 2A). Flow cytometric analysis of B cells that were first pre-stimulated with R-848 and IL-2 and then treated with rOPN (n = 6 healthy donors) demonstrated a significantly lower expression of both co-stimulatory molecules (p = 0.003 for CD80; p = 0.010 for CD86) (Figure 2B) compared to the vehicle (i.e., medium or R-848 + IL-2 only, respectively).

3.3. OPN Has Differential Effects on IL-6 and IL-10 Secretion by B Cells

To investigate if rOPN also had an effect on the cytokine profile of B cells, a dot blot antibody array was performed. Supernatants of B cells that had been pre-stimulated with R-848 and IL-2 only or pre-stimulated and then treated with rOPN from n = 1 donor were used. Based on the integrated density of the dots (Supplementary Table S2), two of the cytokines that triggered our interest were IL-10 and IL-6, which showed increased or decreased secretion by rOPN-treated B cells, respectively (Figure 3A), compared to the vehicle. An IL-6/IL-10-producing B cell ratio to predict active disease in MS patients has been studied earlier [32]. Although no statistics could be performed on the dot blot with n = 1 patient, we verified the influence of rOPN on IL-6 and IL-10 secretion by B cells using ELISA. A supernatant of pre-stimulated B cells (of >80% purity) treated with rOPN from a cohort of n = 6 healthy donors was tested for both cytokines. There was significant downregulation in the synthesis of IL-6 (p = 0.020) in rOPN-treated B cells vs. the untreated group, but no significance was achieved in IL-10 production between the groups.
An estimation plot was created to document the concurrent IL-6 and IL-10 synthesis profile of B cells treated with rOPN from each individual donor. Although no statistical significance was observed (p = 0.062), rOPN-treated B cells from 5/6 donors that had decreased levels of IL-6 produced an increased amount of IL-10 (Figure 3C), while this was not the case in the group that was treated with R-848 and IL-2 alone.

3.4. OPN Significantly Increases the Potential of B Cells to Form Aggregates

Given the expression of OPN within B cell aggregates, we assessed the impact of rOPN on homotypic B cell aggregation. Accordingly, we used the in vitro B cell aggregation assay model initially described by Smith, Rigley, and Callard [33] (Figure 4A). The number of B cell aggregates induced by anti-CD19 antibody in rOPN-treated B cells was significantly higher (p = 0.019) than in the control group (Figure 4B). However, the size of the aggregates formed was comparable between the two groups.

4. Discussion

In this study, we show that OPN is expressed within B cell aggregates in MS brain tissue and uncover a conflicting role of this molecule in its association with B cells. On the one hand, OPN has the potential to dampen B cell activity by downregulating the co-stimulatory molecules CD80 and CD86. On the other hand, B cells have an increased tendency to form aggregates when treated with OPN.
First, we demonstrate strong expression of OPN within B cell aggregates in human brain tissues. Using MS brain tissues that were positive for B cell aggregates, we extend previous findings that OPN expression is associated with B cell clusters not only in peripheral inflammatory autoimmune diseases [34,35] but also in the event of chronic neuroinflammation.
In autoimmune diseases, OPN is widely considered to be a pro-inflammatory cytokine that enhances the production of IL-6 [29] and (auto)antibodies [24] by B cells. However, OPN also has anti-inflammatory properties and is known to regulate tissue repair [36]. Our study demonstrates that OPN has the potential to regulate the activation status of B cells and therefore possibly also plays an important role in modulating T cell activation.
CD27+ memory B cells are not only aberrantly outnumbered in the peripheral blood and cerebrospinal fluid (CSF) of MS patients [37] but have also been detected within MS lesions [7]. Furthermore, it has been demonstrated that memory B cells can function as potent antigen-presenting cells (APCs) [38] with pro-inflammatory tendencies [39] and are the main pathogenic subset of B cells [40]. Therefore, given the relevance of memory B cells in MS, we investigated the effects of OPN on B cells stimulated with a combination of R-848 and IL-2 as polyclonal activators that prompt efficient proliferation and differentiation of memory B cells [41].
Our data indicate that OPN significantly downregulated both CD80 and CD86 on B cells pre-stimulated with R-848 and IL-2 while only affecting CD80 expression on unstimulated B cells. CD80 and CD86 are co-stimulatory molecules that are overexpressed on B cells in MS patients [42] and are involved in immune regulation [43]. Future studies focusing on a more comprehensive phenotype characterization will allow us to confirm the nature of the effect of OPN on different subtypes of B cells. Nevertheless, our results suggest that OPN reduces the overall activation status of B cells through modulation of its co-stimulatory molecules CD80/CD86.
Additionally, on the one hand, we show a significant downregulation of IL-6 secretion by pre-stimulated B cells treated with rOPN and an upregulation of IL-10 synthesis by the same cells in 83.3% of our cohort. On the other hand, as expected, we also confirm that pre-stimulated B cells that were left untreated concurrently secreted high levels of IL-6 and low levels of IL-10 in all six donors tested. Despite the small sample size, the data strongly support an overall tendency of OPN to polarize B cells to a more anti-inflammatory phenotype. The therapeutic benefit of neutralizing the effects of the pro-inflammatory cytokine IL-6 has been suggested for different autoimmune diseases such as RA [44,45], and harvesting the potential of B cell-derived IL-10 in controlling autoimmunity, such as in MS, has also been widely discussed [46,47].
Of note, in contrast to our finding, other groups have suggested that OPN not only inhibits IL-10 secretion in macrophages [48] but OPN-deficient mice produce an enhanced level of IL-10 compared to wild-type mice [49]. This suggests that OPN most likely exerts differential effects on distinct cell populations in a context-dependent manner. One caveat of this study is that we cannot exclude the possibility of a small number of IL-6/IL-10 secreting contaminating cell populations in our B cell culture that contributed to the signal detected by the different ELISAs. Therefore, taking the heterogeneity of the immune repertoires between donors into account, in vitro treatment of B cells with rOPN using a larger cohort of donors would verify the beneficial effect of this molecule in limiting inflammation. Furthermore, the choice of cytokines used to demonstrate the anti-inflammatory effect of rOPN on B cells (i.e., IL-6 and IL-10) was shortlisted from a cohort of only n = 1 donor. Hence, a more comprehensive screening of pro- and anti-inflammatory cytokines secreted by OPN-stimulated B cells using a larger cohort of donors would strengthen our current findings.
Finally, the high level of OPN expression within the B cell aggregates in the human brain sections of MS patients led us to question whether OPN also influenced the formation of B cell aggregates. Surprisingly, B cells treated with rOPN had a significantly higher tendency to form aggregates than the control. An earlier study, however, argued against the nature of OPN to induce homotypic aggregation formation [50]. Using CD44-transfected cell lines, Weber et al. showed that the interaction between OPN and its receptor CD44 did not induce homotypic aggregation [50]. Despite the conflicting findings, it is plausible that in our in vitro system, OPN-stimulated B cells have a higher tendency to form aggregates that may be dependent on another receptor–ligand interaction. Identifying the precise receptor–ligand interaction, which results in OPN-dependent B cell aggregation, would be a necessary step in the future.
One of the limitations of our short-term in vitro assay is that it does not mimic the chronic aggregation of B cells. Furthermore, B cell aggregates found in chronically inflamed tissues, such as in MS or RA, do not contain a pure population of B cells but are rather clusters of B cells with T cells, as shown by us and others [27,51]. Therefore, future studies using a mixed lymphocyte population to observe the effect of OPN on facilitating B cell aggregation longitudinally would validate the role of this molecule in the development of aggregates in chronic neuroinflammation.

5. Conclusions

To conclude, the pleiotropic nature of OPN is well known [52] given its capacity to interact with multiple receptors [53]. Exploiting the interaction between OPN and its receptors that results in polarizing B cells to a less activated phenotype could open up new therapeutic possibilities in chronic (neuro)inflammatory diseases. Similarly, inhibiting the interaction between OPN and possible putative ligands that enhance B cell aggregate formation could limit an ongoing antigen-specific immune response within tissues.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/biomedicines11071969/s1, Figure S1: Control stainings for immunohistochemistry; Figure S2: Representation of the gating strategy for B cell activation; Figure S3: Materials and methods with an overlap in two different studies; Figure S4: Layout of the antibody array used for investigating cytokines; Table S1: Percent purity of B cells isolated from different donors; Table S2: Integrated densities of the dot blot array.

Author Contributions

R.C., V.S. and S.K. were responsible for conceptualization; R.C. and V.S. conducted the experiments and analyzed the data; M.M. and S.A. provided materials; R.C. prepared the original draft of the paper; S.K. and S.A. revised the manuscript for intellectual content and S.K. funded and supervised the study. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by a research grant from the DFG (KU2760/4-1) to S.K.

Institutional Review Board Statement

Approval for this study was given by the Ethics Committee of the University of Würzburg (file number 258/14), the Medical Ethics Committee of the Amsterdam UMC, the Ethics Committee of the University Hospital Erlangen (file number 334_18B), and the Ethics Committee of Friedrich-Alexander-Universität Erlangen-Nürnberg (files 185_18B and 74_18B).

Informed Consent Statement

Not applicable.

Data Availability Statement

The original contributions presented in the study are included in the article/Supplementary Material, and further inquiries can be directed to the corresponding author.

Acknowledgments

We would like to thank Samir Jabari and Stefanie Schliwa for acquiring healthy control blood samples. We thank Markus Hoffmann for providing us with the RA patient tissues. We also wish to thank all participants who generously donated their blood for this study. Excellent technical assistance was provided by Stephanie Link and Birgit Blanck.

Conflicts of Interest

The authors declare that they have no competing interest.

References

  1. Jain, R.W.; Yong, V.W. B cells in central nervous system disease: Diversity, locations and pathophysiology. Nat. Rev. Immunol. 2022, 22, 513–524. [Google Scholar] [CrossRef]
  2. Corsiero, E.; Nerviani, A.; Bombardieri, M.; Pitzalis, C. Ectopic lymphoid structures: Powerhouse of autoimmunity. Front. Immunol. 2016, 7, 430. [Google Scholar] [CrossRef] [Green Version]
  3. Serafini, B.; Rosicarelli, B.; Magliozzi, R.; Stigliano, E.; Aloisi, F. Detection of ectopic B-cell follicles with germinal centers in the meninges of patients with secondary progressive multiple sclerosis. Brain Pathol. 2004, 14, 164–174. [Google Scholar] [CrossRef]
  4. Magliozzi, R.; Howell, O.; Vora, A.; Serafini, B.; Nicholas, R.; Puopolo, M.; Reynolds, R.; Aloisi, F. Meningeal B-cell follicles in secondary progressive multiple sclerosis associate with early onset of disease and severe cortical pathology. Brain 2007, 130, 1089–1104. [Google Scholar] [CrossRef] [PubMed]
  5. Howell, O.W.; Reeves, C.A.; Nicholas, R.; Carassiti, D.; Radotra, B.; Gentleman, S.M.; Serafini, B.; Aloisi, F.; Roncaroli, F.; Magliozzi, R.; et al. Meningeal inflammation is widespread and linked to cortical pathology in multiple sclerosis. Brain 2011, 134, 2755–2771. [Google Scholar] [CrossRef] [Green Version]
  6. Lucchinetti, C.F.; Popescu, B.F.G.; Bunyan, R.F.; Moll, N.M.; Roemer, S.F.; Lassmann, H.; Brück, W.; Parisi, J.E.; Scheithauer, B.W.; Giannini, C.; et al. Inflammatory cortical demyelination in early multiple sclerosis. N. Engl. J. Med. 2011, 365, 2188–2197. [Google Scholar] [CrossRef] [Green Version]
  7. Machado-Santos, J.; Saji, E.; Tröscher, A.; Paunovic, M.; Liblau, R.; Gabriely, G.; Bien, C.G.; Bauer, J.; Lassmann, H. The compartmentalized inflammatory response in the multiple sclerosis brain is composed of tissue-resident CD8+ T lymphocytes and B cells. Brain 2018, 141, 2066–2082. [Google Scholar] [CrossRef] [PubMed]
  8. Moccia, M.; Haider, L.; Eshaghi, A.; van de Pavert, S.H.P.; Morra, V.B.; Patel, A.; Wheeler-Kingshott, C.A.M.; Barkhof, F.; Ciccarelli, O. B cells in the CNS at postmortem are associated with worse outcome and cell types in multiple sclerosis. Neurol.—Neuroimmunol. Neuroinflamm. 2022, 9, e1108. [Google Scholar] [CrossRef] [PubMed]
  9. Choi, S.R.; Howell, O.W.; Carassiti, D.; Magliozzi, R.; Gveric, D.; Muraro, P.A.; Nicholas, R.; Roncaroli, F.; Reynolds, R. Meningeal inflammation plays a role in the pathology of primary progressive multiple sclerosis. Brain 2012, 135, 2925–2937. [Google Scholar] [CrossRef] [Green Version]
  10. Reali, C.; Magliozzi, R.; Roncaroli, F.; Nicholas, R.; Howell, O.W.; Reynolds, R. B cell rich meningeal inflammation associates with increased spinal cord pathology in multiple sclerosis. Brain Pathol. 2020, 30, 779–793. [Google Scholar] [CrossRef] [Green Version]
  11. Ahmed, S.M.; Fransen, N.L.; Touil, H.; Michailidou, I.; Huitinga, I.; Gommerman, J.L.; Bar-Or, A.; Ramaglia, V. Accumulation of meningeal lymphocytes correlates with white matter lesion activity in progressive multiple sclerosis. JCI Insight 2022, 7, e151683. [Google Scholar] [CrossRef] [PubMed]
  12. Chunder, R.; Schropp, V.; Kuerten, S. B cells in multiple sclerosis and virus-induced neuroinflammation. Front. Neurol. 2020, 11, 591894. [Google Scholar] [CrossRef] [PubMed]
  13. Jones, G.W.; Jones, S.A. Ectopic lymphoid follicles: Inducible centers for generating antigen-specific immune responses within tissues. Immunology 2016, 147, 141–151. [Google Scholar] [CrossRef] [Green Version]
  14. Negron, A.; Stüve, O.; Forsthuber, T.G. Ectopic lymphoid follicles in multiple sclerosis: Centers for disease control? Front. Neurol. 2020, 11, 607766. [Google Scholar] [CrossRef] [PubMed]
  15. Pikor, N.B.; Prat, A.; Bar-Or, A.; Gommerman, J.L. Meningeal tertiary lymphoid tissues and multiple sclerosis: A gathering place for diverse types of immune cells during CNS autoimmunity. Front. Immunol. 2016, 6, 657. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  16. Uccelli, A.; Aloisi, F.; Pistoia, V. Unveiling the enigma of the CNS as a B-cell fostering environment. Trends Immunol. 2005, 26, 254–259. [Google Scholar] [CrossRef]
  17. Sodek, J.; Ganss, B.; McKee, M.D. Osteopontin. Crit. Rev. Oral Biol. Med. 2000, 11, 279–303. [Google Scholar] [CrossRef]
  18. Steinman, L. A molecular trio in relapse and remission in multiple sclerosis. Nat. Rev. Immunol. 2009, 9, 440–447. [Google Scholar] [CrossRef]
  19. Cantor, H.; Shinohara, M.L. Regulation of T-helper-cell lineage development by osteopontin: The inside story. Nat. Rev. Immunol. 2009, 9, 137–141. [Google Scholar] [CrossRef] [Green Version]
  20. Jansson, M.; Panoutsakopoulou, V.; Baker, J.; Klein, L.; Cantor, H. Cutting Edge: Attenuated experimental autoimmune encephalomyelitis in Eta-1/osteopontin-deficient mice. J. Immunol. 2002, 168, 2096–2099. [Google Scholar] [CrossRef]
  21. Hur, E.M.; Youssef, S.; Haws, M.E.; Zhang, S.Y.; Sobel, R.A.; Steinman, L. Osteopontin-induced relapse and progression of autoimmune brain disease through enhanced survival of activated T cells. Nat. Immunol. 2007, 8, 74–83. [Google Scholar] [CrossRef] [PubMed]
  22. Hsiao, C.-C.; Engelenburg, H.J.; Jongejan, A.; Zhu, J.; Zhang, B.; Mingueneau, M.; Moerland, P.D.; Huitinga, I.; Smolders, J.; Hamann, J. Osteopontin associates with brain TRM-cell transcriptome and compartmentalization in donors with and without multiple sclerosis. iScience 2023, 26, 105785. [Google Scholar] [CrossRef] [PubMed]
  23. Guo, B.; Tumang, J.R.; Rothstein, T.L. B cell receptor crosstalk: B cells express osteopontin through the combined action of the alternate and classical BCR signaling pathways. Mol. Immunol. 2009, 46, 587–591. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  24. Rittling, S.R.; Singh, R. Osteopontin in immune-mediated diseases. J. Dent. Res. 2015, 94, 1638–1645. [Google Scholar] [CrossRef] [Green Version]
  25. Chunder, R.; Schropp, V.; Jabari, S.; Marzin, M.; Amor, S.; Kuerten, S. Identification of a novel role for matrix metalloproteinase-3 in the modulation of B cell responses in multiple sclerosis. Front. Immunol. 2022, 13, 1025377. [Google Scholar] [CrossRef]
  26. Wada, T.; McKee, M.D.; Steitz, S.; Giachelli, C.M. Calcification of vascular smooth muscle cell cultures: Inhibition by osteopontin. Circ. Res. 1999, 84, 166–178. [Google Scholar] [CrossRef]
  27. Rabenstein, M.; Hucklenbroich, J.; Willuweit, A.; Ladwig, A.; Fink, G.R.; Schroeter, M.; Langen, K.-J.; Rueger, M.A. Osteopontin mediates survival, proliferation and migration of neural stem cells through the chemokine receptor CXCR4. Stem Cell Res. Ther. 2015, 6, 99. [Google Scholar] [CrossRef] [Green Version]
  28. Rovituso, D.M.; Scheffler, L.; Wunsch, M.; Kleinschnitz, C.; Dörck, S.; Ulzheimer, J.; Bayas, A.; Steinman, L.; Ergün, S.; Kuerten, S. CEACAM1 mediates B cell aggregation in central nervous system autoimmunity. Sci. Rep. 2016, 20, 29847. [Google Scholar] [CrossRef] [Green Version]
  29. Take, Y.; Nakata, K.; Hashimoto, J.; Tsuboi, H.; Nishimoto, N.; Ochi, T.; Yoshikawa, H. Specifically modified osteopontin in rheumatoid arthritis fibroblast-like synoviocytes supports interaction with B cells and enhances production of interleukin-6. Arthritis Rheum. 2009, 60, 3591–3601. [Google Scholar] [CrossRef]
  30. Bar-Or, A.; Oliveira, E.M.; Anderson, D.E.; Krieger, J.I.; Duddy, M.; O’Connor, K.C.; Hafler, D.A. Immunological memory: Contribution of memory B cells expressing costimulatory molecules in the resting state. J. Immunol. 2001, 167, 5669–5677. [Google Scholar] [CrossRef]
  31. Hathcock, K.S.; Laszlo, G.; Pucillo, C.; Linsley, P.; Hodes, R.J. Comparative analysis of B7-1 and B7-2 costimulatory ligands: Expression and function. J. Exp. Med. 1994, 180, 631–640. [Google Scholar] [CrossRef] [PubMed]
  32. Guerrier, T.; Labalette, M.; Launay, D.; Lee-Chang, C.; Outteryck, O.; Lefèvre, G.; Vermersch, P.; Dubucquoi, S.; Zéphir, H. Proinflammatory B-cell profile in the early phases of MS predicts an active disease. Neurol.—Neuroimmunol. Neuroinflamm. 2017, 5, e431. [Google Scholar] [CrossRef] [Green Version]
  33. Smith, S.H.; Rigley, K.P.; Callard, R.E. Activation of human B cells through the CD19 surface antigen results in homotypic adhesion by LFA-1-dependent and -independent mechanisms. Immunology 1991, 73, 293–297. [Google Scholar] [PubMed]
  34. Stott, D.I.; Hiepe, F.; Hummel, M.; Steinhauser, G.; Berek, C. Antigen-driven clonal proliferation of B cells within the target tissue of an autoimmune disease. The salivary glands of patients with Sjögren’s syndrome. J. Clin. Investig. 1998, 102, 938–946. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  35. Carlsen, H.S.; Baekkevold, E.S.; Johansen, F.E.; Haraldsen, G.; Brandtzaeg, P. B cell attracting chemokine 1 (CXCL13) and its receptor CXCR5 are expressed in normal and aberrant gut associated lymphoid tissue. Gut 2002, 51, 364–371. [Google Scholar] [CrossRef] [Green Version]
  36. Lund, S.A.; Giachelli, C.M.; Scatena, M. The role of osteopontin in inflammatory processes. J. Cell Commun. Signal. 2009, 3, 311–322. [Google Scholar] [CrossRef] [Green Version]
  37. DiSano, K.D.; Gilli, F.; Pachner, A.R. Memory B cells in multiple sclerosis: Emerging players in disease pathogenesis. Front. Immunol. 2021, 12, 676686. [Google Scholar] [CrossRef]
  38. Harp, C.T.; Ireland, S.; Davis, L.S.; Remington, G.; Cassidy, B.; Cravens, P.D.; Stuve, O.; Lovett-Racke, A.E.; Eagar, T.N.; Greenberg, B.M.; et al. Memory B cells from a subset of treatment-naïve relapsing-remitting multiple sclerosis patients elicit CD4+ T-cell proliferation and IFN-γ production in response to myelin basic protein and myelin oligodendrocyte glycoprotein. Eur. J. Immunol. 2010, 40, 2942–2956. [Google Scholar] [CrossRef] [Green Version]
  39. Duddy, M.; Niino, M.; Adatia, F.; Hebert, S.; Freedman, M.; Atkins, H.; Kim, H.J.; Bar-Or, A. Distinct effector cytokine profiles of memory and naive human B cell subsets and implication in multiple sclerosis. J. Immunol. 2007, 178, 6092–6099. [Google Scholar] [CrossRef]
  40. Jelcic, I.; Al Nimer, F.; Wang, J.; Lentsch, V.; Planas, R.; Jelcic, I.; Madjovski, A.; Ruhrmann, S.; Faigle, W.; Frauenknecht, K.; et al. Memory B cells activate brain-homing, autoreactive CD4+ T cells in multiple sclerosis. Cell 2018, 175, 85–100. [Google Scholar] [CrossRef] [Green Version]
  41. Pinna, D.; Corti, D.; Jarrossay, D.; Sallusto, F.; Lanzavecchia, A. Clonal dissection of the human memory B-cell repertoire following infection and vaccination. Eur. J. Immunol. 2009, 39, 1260–1270. [Google Scholar] [CrossRef] [PubMed]
  42. Fraussen, J.; Claes, N.; Van Wijmeersch, B.; van Horssen, J.; Stinissen, P.; Hupperts, R.; Somers, V. B cells of multiple sclerosis patients induce autoreactive proinflammatory T cell responses. Clin. Immunol. 2016, 173, 124–132. [Google Scholar] [CrossRef] [PubMed]
  43. Menezes, S.M.; Decanine, D.; Brassat, D.; Khouri, R.; Schnitman, S.V.; Kruschewsky, R.; López, G.; Alvarez, C.; Talledo, M.; Gotuzzo, E.; et al. CD80+ and CD86+ B cells as biomarkers and possible therapeutic targets in HTLV-1 associated myelopathy/tropical spastic paraparesis and multiple sclerosis. J. Neuroinflamm. 2014, 11, 18. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  44. Arkatkar, T.; Du, S.W.; Jacobs, H.M.; Dam, E.M.; Hou, B.; Buckner, J.H.; Rawlings, D.J.; Jackson, S.W. B cell-derived IL-6 initiates spontaneous germinal center formation during systemic autoimmunity. J. Exp. Med. 2017, 214, 3207–3217. [Google Scholar] [CrossRef]
  45. Maeda, K.; Mehta, H.; Drevets, D.A.; Coggeshall, K.M. IL-6 increases B-cell IgG production in a feed-forward proinflammatory mechanism to skew hematopoiesis and elevate myeloid production. Blood 2010, 115, 4699–4706. [Google Scholar] [CrossRef] [Green Version]
  46. Ran, Z.; Yue-Bei, L.; Qiu-Ming, Z.; Huan, Y. Regulatory B cells and its role in central nervous system inflammatory demyelinating diseases. Front. Immunol. 2020, 11, 1884. [Google Scholar] [CrossRef]
  47. Radomir, L.; Kramer, M.P.; Perpinial, M.; Schottlender, N.; Rabani, S.; David, K.; Wiener, A.; Lewinsky, H.; Becker-Herman, S.; Aharoni, R.; et al. The survival and function of IL-10-producing regulatory B cells are negatively controlled by SLAMF5. Nat. Commun. 2021, 12, 1893. [Google Scholar] [CrossRef] [PubMed]
  48. Renkl, A.C.; Wussler, J.; Ahrens, T.; Thoma, K.; Kon, S.; Uede, T.; Martin, S.F.; Simon, J.C.; Weiss, J.M. Osteopontin functionally activates dendritic cells and induces their differentiation toward a Th1-polarizing phenotype. Blood 2005, 106, 946–955. [Google Scholar] [CrossRef] [Green Version]
  49. Chabas, D.; Baranzini, S.E.; Mitchell, D.; Bernard, C.C.A.; Rittling, S.R.; Denhardt, D.T.; Sobel, R.A.; Lock, C.; Karpuj, M.; Pedotti, R.; et al. The influence of the proinflammatory cytokine, osteopontin, on autoimmune demyelinating disease. Science 2001, 294, 1731–1735. [Google Scholar] [CrossRef]
  50. Weber, G.F.; Ashkar, S.; Glimcher, M.J.; Cantor, H. Receptor-ligand interaction between CD44 and osteopontin (Eta-1). Science 1996, 271, 509–512. [Google Scholar] [CrossRef]
  51. Kee, R.; Naughton, M.; McDonnell, G.V.; Howell, O.W.; Fitzgerald, D.C. A review of compartmentalised inflammation and tertiary lymphoid structures in the pathophysiology of multiple sclerosis. Biomedicines 2022, 10, 2604. [Google Scholar] [CrossRef] [PubMed]
  52. Kahles, F.; Findeisen, H.M.; Bruemmer, D. Osteopontin: A novel regulator at the cross roads of inflammation, obesity and diabetes. Mol. Metab. 2014, 3, 384–393. [Google Scholar] [CrossRef] [PubMed]
  53. Clemente, N.; Raineri, D.; Cappellano, G.; Boggio, E.; Favero, F.; Soluri, M.F.; Dianzani, C.; Comi, C.; Dianzani, U.; Chiocchetti, A. Osteopontin bridging innate and adaptive immunity in autoimmune diseases. J. Immunol. Res. 2016, 2016, 7675437. [Google Scholar] [CrossRef] [PubMed] [Green Version]
Biomedicines 11 01969 g001 550
Figure 1. Expression of OPN in human tissue sections with or without B cell pathology. (A) OPN expression in brain tissue from a CD20+ B cell aggregate-positive patient, a CD20+ B cell aggregate-negative patient, and a patient without any observable CD3/CD20 infiltration. Expression of OPN within a CD20+ B cell aggregate in a (B) patient with MS vs. (C) a patient with RA. Scale bars represent either 50 μm (A and B) or 100 μm (C). MS = multiple sclerosis; OPN = osteopontin; RA = rheumatoid arthritis.
Figure 1. Expression of OPN in human tissue sections with or without B cell pathology. (A) OPN expression in brain tissue from a CD20+ B cell aggregate-positive patient, a CD20+ B cell aggregate-negative patient, and a patient without any observable CD3/CD20 infiltration. Expression of OPN within a CD20+ B cell aggregate in a (B) patient with MS vs. (C) a patient with RA. Scale bars represent either 50 μm (A and B) or 100 μm (C). MS = multiple sclerosis; OPN = osteopontin; RA = rheumatoid arthritis.
Biomedicines 11 01969 g001
Biomedicines 11 01969 g002 550
Figure 2. Analysis of co-stimulatory molecules on B cells after rOPN stimulation. (A) Expression of CD80 and CD86 by unstimulated B cells following incubation with medium only or rOPN (cells isolated from n = 6 healthy donors). (B) Expression of CD80 and CD86 by B cells pre-stimulated with R-848 + IL-2 and incubated with or without rOPN (cells isolated from n = 6 healthy donors). Every data point on the graphs corresponds to the percentage of either CD80+ or CD86+ B cells under different conditions. Graphs show mean values ± standard error of mean (SEM). * p < 0.05, ** p < 0.01, *** p < 0.001, paired t test. IL = interleukin; R-848 = synthetic toll-like receptor 7/8 agonist; rOPN = recombinant osteopontin.
Figure 2. Analysis of co-stimulatory molecules on B cells after rOPN stimulation. (A) Expression of CD80 and CD86 by unstimulated B cells following incubation with medium only or rOPN (cells isolated from n = 6 healthy donors). (B) Expression of CD80 and CD86 by B cells pre-stimulated with R-848 + IL-2 and incubated with or without rOPN (cells isolated from n = 6 healthy donors). Every data point on the graphs corresponds to the percentage of either CD80+ or CD86+ B cells under different conditions. Graphs show mean values ± standard error of mean (SEM). * p < 0.05, ** p < 0.01, *** p < 0.001, paired t test. IL = interleukin; R-848 = synthetic toll-like receptor 7/8 agonist; rOPN = recombinant osteopontin.
Biomedicines 11 01969 g002
Biomedicines 11 01969 g003 550
Figure 3. Cytokine profiling of rOPN-treated B cells. (A) IL-6 and IL-10 production by B cells from the same donor either with or without treatment with rOPN is shown. The amount of IL-6 and IL-10 production between the two groups was calculated by using the integrated density from n = 1 donor, measured in duplicates as shown in the black boxes. (B) IL-6 and IL-10 production of pre-stimulated B cells (n = 6 healthy donors), measured by ELISA. (C) An estimation plot demonstrating the level of IL-6 vs. IL-10 secretion by rOPN-treated and -untreated B cells are also shown. Bars display mean values ± SEM. * p < 0.05, paired t test. IL = interleukin; R-848 = synthetic toll-like receptor 7/8 agonist; rOPN = recombinant osteopontin.
Figure 3. Cytokine profiling of rOPN-treated B cells. (A) IL-6 and IL-10 production by B cells from the same donor either with or without treatment with rOPN is shown. The amount of IL-6 and IL-10 production between the two groups was calculated by using the integrated density from n = 1 donor, measured in duplicates as shown in the black boxes. (B) IL-6 and IL-10 production of pre-stimulated B cells (n = 6 healthy donors), measured by ELISA. (C) An estimation plot demonstrating the level of IL-6 vs. IL-10 secretion by rOPN-treated and -untreated B cells are also shown. Bars display mean values ± SEM. * p < 0.05, paired t test. IL = interleukin; R-848 = synthetic toll-like receptor 7/8 agonist; rOPN = recombinant osteopontin.
Biomedicines 11 01969 g003
Biomedicines 11 01969 g004 550
Figure 4. Aggregation of B cells in the presence of rOPN. (A) Representative images of aggregation of pre-stimulated B cells with or without rOPN treatment induced by anti-CD19 antibody. Scale bars represent 100 μm. (B) Number and size of the aggregates formed comparing control (R-848 + IL-2 stimulation only) and rOPN (in addition to R-848 + IL-2)-treated B cells. Bars display mean values ± SEM. * p < 0.05, paired t test. IL = interleukin; R-848 = synthetic toll-like receptor 7/8 agonist; rOPN = recombinant osteopontin.
Figure 4. Aggregation of B cells in the presence of rOPN. (A) Representative images of aggregation of pre-stimulated B cells with or without rOPN treatment induced by anti-CD19 antibody. Scale bars represent 100 μm. (B) Number and size of the aggregates formed comparing control (R-848 + IL-2 stimulation only) and rOPN (in addition to R-848 + IL-2)-treated B cells. Bars display mean values ± SEM. * p < 0.05, paired t test. IL = interleukin; R-848 = synthetic toll-like receptor 7/8 agonist; rOPN = recombinant osteopontin.
Biomedicines 11 01969 g004
Table
Table 1. Patient details [25].
Table 1. Patient details [25].
MS patients
NumberAgeSexMS TypeDisease Duration
(In Years)		Cause of DeathNumber of BlocksPatient Type
MS32551MPPMS2Bronchopneumonia2NI
MS34235FSPMS5MS2B cell
MS40246MSPMS20MS, bronchopneumonia1B cell
MS40744FSPMS19Sepsis, pneumonia1B cell
MS40839MSPMS10Sepsis, pneumonia1NI
MS43853FUnknown18MS2NI
MS44449MSPMS20Kidney failure2T cell
MS47339FPPMS13MS, bronchopneumonia2T cell
MS48557FPPMS29MS, bronchopneumonia2T cell
MS51038FSPMS22MS, pneumonia1T cell
MS52363FSPMS32Bronchopneumonia1T cell
MS52845FSPMS25Pneumonia1T cell
11-07766FPPMS32Euthanasia5B cell
14-00656FUnknown31Suicide by pentobarbital intoxication2B cell
15-04750FSPMS18Euthanasia2B cell
16-01948MUnknown15Ileus, dehydration4B cell
RA patients
NumberAgeSexTissue typeNumber of blocks
427-1957FSurgical biopsy1
470-19a74FSurgical biopsy1
471-19b82FSurgical biopsy1
F = female; M = male; MS = multiple sclerosis; NI= No CD3/CD20 infiltration; PPMS = primary progressive MS; SPMS = secondary progressive MS.
Table
Table 2. List of antibodies and their dilutions.
Table 2. List of antibodies and their dilutions.
Antibodies Used for Immunofluorescence
AntibodySourceHost SpeciesCloneDilution
Anti-CD20InvitrogenMouseL261:400
Anti-CD3AbcamRabbitSP1621:150
Anti-OPNPolyclonal1:100
Anti-human IgGAbcamRabbitPolyclonal1:200
Antibodies used for flow cytometry
BB700 Anti-CD3BD BiosciencesMouseSK71:20
APC Anti-CD19HIB191:5
APC Anti-CD202H71:5
BB515 Anti-CD45HI301:20
BV605 Anti-CD802D10.41:40
BB515 Anti-CD86FUN-11:20
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Chunder, R.; Schropp, V.; Marzin, M.; Amor, S.; Kuerten, S. A Dual Role of Osteopontin in Modifying B Cell Responses. Biomedicines 2023, 11, 1969. https://doi.org/10.3390/biomedicines11071969

AMA Style

Chunder R, Schropp V, Marzin M, Amor S, Kuerten S. A Dual Role of Osteopontin in Modifying B Cell Responses. Biomedicines. 2023; 11(7):1969. https://doi.org/10.3390/biomedicines11071969

Chicago/Turabian Style

Chunder, Rittika, Verena Schropp, Manuel Marzin, Sandra Amor, and Stefanie Kuerten. 2023. "A Dual Role of Osteopontin in Modifying B Cell Responses" Biomedicines 11, no. 7: 1969. https://doi.org/10.3390/biomedicines11071969

APA Style

Chunder, R., Schropp, V., Marzin, M., Amor, S., & Kuerten, S. (2023). A Dual Role of Osteopontin in Modifying B Cell Responses. Biomedicines, 11(7), 1969. https://doi.org/10.3390/biomedicines11071969

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop