In systemic lupus erythematosus (SLE), type I IFNs promote induction of type I IFN–stimulated genes (ISG) and can drive B cells to produce autoantibodies. Little is known about the expression of distinct type I IFNs in lupus, particularly high-affinity IFN-β. Single-cell analyses of transitional B cells isolated from SLE patients revealed distinct B cell subpopulations, including type I IFN producers, IFN responders, and mixed IFN producer/responder clusters. Anti-Ig plus TLR3 stimulation of SLE B cells induced release of bioactive type I IFNs that could stimulate HEK-Blue cells. Increased levels of IFN-β were detected in circulating B cells from SLE patients compared with controls and were significantly higher in African American patients with renal disease and in patients with autoantibodies. Together, the results identify type I IFN–producing and –responding subpopulations within the SLE B cell compartment and suggest that some patients may benefit from specific targeting of IFN-β.

Activation of the type I IFNs, consisting of 13 IFN-α subtypes and one high-affinity IFN-β subtype, is highly associated with the development of systemic lupus erythematosus (SLE) as well as clinical disease manifestations (1). Type I IFNs can be produced by most cell types, although their activity in SLE is most often measured indirectly using the presence of specific type I IFN–inducible transcripts, termed the type I IFN signature (1, 2). Previous studies have identified unique type I IFN signatures among different immune cell populations (37), but cell-specific expression patterns and roles of distinct type I IFNs in SLE, especially high-affinity IFN-β, remain elusive (8), largely because of their low levels of transcription and circulation (9).

In autoimmune mice, IFNαR1 deficiency ameliorates germinal center and autoantibody development (10, 11). Although a previous study in NZB mice reported no difference in anti-chromatin Abs or renal disease in Ifnb–⁄– mice (12), these findings have been challenged by reports that IFN-β is elevated and dysregulated in SLE (13, 14) as well as the identification of distinct IFN signatures not restricted to IFN-α (15). Serum detection of IFN-β was recently associated with disease flares, particularly in African American (AA) patients, a population with increased disease prevalence, severity, and robust type I IFN dysregulation (14, 16). Autocrine IFN-β signaling has been identified as a mechanism of type I IFN dysregulation in SLE mesenchymal stem cells (13), and B cells have also been shown to produce type I IFNs in SLE and other diseases (9, 17, 18). In this study, we examined expression patterns of type I IFNs and their target type I IFN–stimulated genes (ISGs) in circulating B cells and identified a potential role for B cell–associated IFN-β in SLE.

All SLE subjects met the American College of Rheumatology 1997 revised criteria for SLE (19) and were recruited from the University of Alabama at Birmingham (UAB) Lupus Clinic. PBMCs were isolated by density gradient centrifugation (Lymphoprep/SepMate; STEMCELL Technologies). Clinical data were determined by the UAB clinical laboratory and attending physician. All flow cytometry and bulk cell gene expression data were collected in a double-blinded manner.

These studies were conducted in compliance with the Helsinki Declaration and approved by the institutional review board at UAB. All participants provided informed consent.

Human Abs included BioLegend BV510–anti-CD24 (ML5), PE–anti-CD303 (clone 201A), BV510–anti-IgM (clone MHM-88), Pacific Blue–anti-CD4 (clone RPA-T4), PE-Cy7–anti-CD10 (clone HI10a), BV650–anti-CD27 (O323), Pacific Blue–anti-CD19 (HIB19), PE-Cy7–anti-CD38 (HB-7); SouthernBiotech PE-IgD (IADB6); and PBL Assay Science FITC–anti–IFN-β (MMHB-3). Dead cells were excluded from analysis with Fixable Viability Dye eFluor 780 (eBioscience). For intracellular staining, cells were stained with eFluor 780 viability dye, followed by fixation in 2% PFA and 70% ice-cold methanol permeabilization prior to staining. Purity was validated by postsort analysis of FACS-sorted cells to verify that >99% of cells fell into the sort gate after resorting. FACS data were acquired with an LSR II FACS analyzer (BD Biosciences) and analyzed with FlowJo software (Tree Star, Ashland, OR).

Negative selection–purified B cells (STEMCELL Technologies) were fixed in 2% paraformaldehyde and permeabilized with Triton X-100, followed by blocking with 2% BSA. Cells were stained with AF647 goat anti-human IgM (SouthernBiotech), FITC mouse anti-human IFN-β (clone MMHB-3; PBL Assay Science), or polyclonal rabbit anti-human IFN-β (Abcam), followed by anti-rabbit IgG AF488 secondary Ab. DAPI nuclear stain was included for nucleus determination (200 ng/ml).

Superresolution imaging was carried out using the Nikon N-SIM E superresolution microscope (resolution capable of 120 nm xy and 300 nm z). Images were acquired with a 100× 1.49 numerical aperture objective; ORCA-Flash 4.0 v2 scientific complementary metal oxide semiconductor camera (Hamamatsu); 488-, 561-, and 640-nm laser excitation; a multipass dichroic cube; and specific emission filters. DAPI images were acquired with a widefield excitation and are at a conventional resolution. Images were acquired and reconstructed with Nikon Elements software. Staining intensity and localization of IFN-β were carried out using Fiji/ImageJ.

RNA isolation, cDNA synthesis, and real-time PCR reactions were carried out as described previously (20, 21). Primers for GAPDH are as follows: forward, 5′-GCACTCACTGGAATGACCTC-3′; backward, 5′-TTCTTCGCACTGACACACTG-3′. All primers used for single-cell analysis are described in Supplemental Table I.

Gene expression analysis of single transitional (Tr) B cells (CD24+CD38+IgD+CD27) obtained from SLE PBMCs was performed using the Fluidigm single-cell capture and BioMark RT-PCR analysis system (Fluidigm, South San Francisco, CA) as described in detail previously (22). Single-cell gene expression clustering analysis was carried out using the ClustVis online web tool (23). Single-cell gene expression data can be retrieved at https://biit.cs.ut.ee/clustvis/?s=zlbtSCZKfAcPrUg.

B cell production of functional type I IFNs was analyzed using coculture of purified primary B cells (5.0 × 105 cells per well) with HEK-Blue IFN-α/β cells that expressed an inducible secreted embryonic alkaline phosphatase (SEAP) (InvivoGen, San Diego, CA). B cells purified using the Human Pan B Cell Isolation Kit (Miltenyi Biotec) were unstimulated or stimulated for 10 min with an F(ab')2 anti-hIg (IgM + IgG) Ab (Thermo Fisher Scientific) (10 μg/ml) plus 5 μg/ml poly(I:C) or 5 μg/ml CL264 (InvivoGen) before HEK-Blue IFN-α/β cells (2.5 × 104 cells per well) were added into the medium. Supernatants were collected at the 24-h time point and were incubated for 1 h with the QUANTI-Blue colorimetric enzyme assay reagent for determination of absorbance at OD650.

Results are mean ± SD or mean ± SEM as described in the figure legends. The p values <0.05 were considered significant. Unless otherwise indicated, all analyses were performed using GraphPad Prism software (La Jolla, CA).

We previously showed that type I IFN expression is a prominent feature of transitional stage 1 B cell development in BXD2 autoimmune mice and that T1 B cell IFN-β acts in an autocrine priming mechanism to promote Ifna and ISGs expression (22). Analysis of type I IFN gene expression from SLE patients revealed a significant increase in the expression of IFNB, IFNA1, IFNA14, IFNA17, and MX1 in Tr B cells from AA patients with SLE (Supplemental Fig. 1A). To determine whether distinct type I IFN and type I ISG gene expression patterns were present in SLE B cells, Tr B cells from three female AA SLE subjects as described in Supplemental Fig. 1B were FACS sorted and analyzed for expression of IFNB, IFNA, and ISGs (Fig. 1A). Hierarchical clustering analysis revealed three prominent clusters with distinct gene signatures, including a mixed IFN and ISG producer/responder signature (IFNP/R), an IFN-responder signature (IFNR), and an IFN-producing signature (IFNP) (Fig. 1A, 1B, Supplemental Table I). Cells from all three patients were equally represented in each cluster, revealing the presence of these major clusters in different SLE patients (Fig. 1C).

FIGURE 1.

Type I IFN and ISG gene expression in single Tr B cells from SLE patients. Tr B cells (CD24+CD38+IgD+CD27) isolated from PBMCs of three SLE patients (see Supplemental Fig. 1B) were prepared for single-cell gene expression analysis. (A) Heat map of hierarchically clustered type I IFN gene expression clustering in individual B cells (n = 207). The top row above the heat map is color coded to denote cell clustering and SLE patient origin. (B) Principal component (PC) analysis of SLE Tr B cell clusters. The x- and y-axis show PC1 and PC2 that explain 15.9 and 9.3% of the total variance, respectively. PC analysis was carried out based on PC1 and PC2 segregation of 32 genes in the IFNP/R, IFNP, or IFNR B cell clusters. Prediction ellipses are such that with p = 0.95, a new observation from the same group will fall inside the ellipse. (C) Bar graph showing the number of single cells designated to each type I IFN cluster based on the gene expression profile from each individual SLE patient (χ2 analysis). (DF) Dot plots showing the normalized expression of representative genes in the IFNP/R cluster (D), the IFNR cluster (E), and the IFNP cluster (F) of B cells as defined by hierarchical clustering. All results are mean ± SD. Significant differences among means were analyzed using a one-way ANOVA test with the p value shown on the top of each graph. Differences between groups were analyzed using Tukey multiple comparisons test. Results are shown as mean ± SD. *p < 0.05, **p < 0.01, *** p < 0.005 between the indicated groups.

FIGURE 1.

Type I IFN and ISG gene expression in single Tr B cells from SLE patients. Tr B cells (CD24+CD38+IgD+CD27) isolated from PBMCs of three SLE patients (see Supplemental Fig. 1B) were prepared for single-cell gene expression analysis. (A) Heat map of hierarchically clustered type I IFN gene expression clustering in individual B cells (n = 207). The top row above the heat map is color coded to denote cell clustering and SLE patient origin. (B) Principal component (PC) analysis of SLE Tr B cell clusters. The x- and y-axis show PC1 and PC2 that explain 15.9 and 9.3% of the total variance, respectively. PC analysis was carried out based on PC1 and PC2 segregation of 32 genes in the IFNP/R, IFNP, or IFNR B cell clusters. Prediction ellipses are such that with p = 0.95, a new observation from the same group will fall inside the ellipse. (C) Bar graph showing the number of single cells designated to each type I IFN cluster based on the gene expression profile from each individual SLE patient (χ2 analysis). (DF) Dot plots showing the normalized expression of representative genes in the IFNP/R cluster (D), the IFNR cluster (E), and the IFNP cluster (F) of B cells as defined by hierarchical clustering. All results are mean ± SD. Significant differences among means were analyzed using a one-way ANOVA test with the p value shown on the top of each graph. Differences between groups were analyzed using Tukey multiple comparisons test. Results are shown as mean ± SD. *p < 0.05, **p < 0.01, *** p < 0.005 between the indicated groups.

Close modal

Cells within the IFNP/R cluster expressed the highest levels of Tr B cell marker CD24 (Fig. 1D, upper left). Cells within the IFNP/R cluster also expressed higher levels of IFNB, IFIT1, IRF7, IRF9, ZBP1, IFNA1, IFNA7, and CCND1 compared with the IFNR or IFNP cluster or both (Fig. 1D, Supplemental Table I). This is consistent with our previous observations in BXD2 mice in which IFNB expression was upregulated in early T1 B cells (22). Cells within the IFNR cluster expressed higher levels of IFNAR1, MX1, IFIT2, PKR, RIG1, and CCND2 (Fig. 1E). The IFNP cluster was characterized by higher levels of IFNA4, IFNA5, IFNA10, IFNA14, IFNA16, and IFNA17 (Fig. 1F). Expression of TLR3 and TLR7 but not TLR9 was different among the groups (Supplemental Fig. 1C). Single-cell gene expression and cell identities were validated by analysis of CD20, CD3, and CD303 expression (Supplemental Fig. 1D). Together, the results reveal heterogeneous type I IFN–producing and –responding signatures in circulating Tr B cells, suggesting that B cells are not only type I IFN targets but also producers of type I IFNs in SLE.

FACS staining (Fig. 2A) and confocal imaging (Fig. 2B) of IFN-β revealed increased levels of IFN-β in B cells from SLE patients compared with healthy controls (HCs). Quantification of IFN-β mean fluorescence intensity (MFI) revealed that although Tr and naive B cells from SLE patients exhibited significantly increased IFN-β compared with HCs, in CD4 T cells and CD303+CD4low plasmacytoid dendritic cells (24), IFN-β levels were not significantly increased in SLE compared with HCs (Fig. 2A). Staining of IFN-β was specifically inhibited by preincubation with human IFN-β but not mouse IFN-α (Supplemental Fig. 2A). We next determined the subcellular localization of IFN-β in SLE B cells. Two anti–IFN-β Abs detected a mainly cytoplasmic distribution of IFN-β in IgM+ B cells (Fig. 2C, Supplemental Fig. 2B). Although significantly less prominent compared with the cytoplasmic localization, IFN-β was also detected in the nucleus (Fig. 2C) as previously reported for other cell types (25, 26). Western blot analysis of cytoplasmic extracts from isolated SLE B cells ex vivo further confirmed the presence of a 25- and 50-kDa band (Supplemental Fig. 2C) consistent with the predicted molecular mass of human IFN-β monomer and dimer (27, 28). Together, these results confirm the presence of cytoplasmic IFN-β in SLE B cells.

FIGURE 2.

Increased expression of intracellular IFN-β in B cells from a subset of SLE patients. (A) Gating strategy (upper left), representative histograms (lower left), and summary of IFN-β MFI (right) in circulating Tr B cells, naive B cells, CD4 T cells, and plasmacytoid dendritic cells (pDCs) in SLE compared with HC. (B) Confocal microscopy imaging (left) and bar graph quantitation of IFN-β intensity (right) in purified B cells from a representative HC or an SLE patient (objective lens ×20). (C) Structured illumination microscopy superresolution imaging and analysis of IFN-β intracellular localization in representative B cells from SLE patients. Top, Representative images showing intra- versus extranuclear staining of IFN-β. The nucleus–cytoplasmic border was defined by DAPI staining (dotted white line) (objective lens ×100). Bottom, ImageJ quantitation of intra- and extranuclear intensity (left) and distribution (right) of IFN-β (n = 22 cells from three SLE patients). (D) HEK-Blue reporter cell analysis of type I IFN secretion by B cells from SLE (n = 9) or HC (n = 3) under the indicated conditions of stimulation. (E) Correlation of FACS detection of baseline (ex vivo) B cell IFN-β (MFI) with HEK-Blue analysis of IFN-β secretion from anti-Ig plus poly(I:C) stimulated B cells. All results are shown as mean ± SD (unpaired Student t test or Mann–Whitney U test for nonnormally distributed data). *p < 0.05, **p < 0.01, ***p < 0.005.

FIGURE 2.

Increased expression of intracellular IFN-β in B cells from a subset of SLE patients. (A) Gating strategy (upper left), representative histograms (lower left), and summary of IFN-β MFI (right) in circulating Tr B cells, naive B cells, CD4 T cells, and plasmacytoid dendritic cells (pDCs) in SLE compared with HC. (B) Confocal microscopy imaging (left) and bar graph quantitation of IFN-β intensity (right) in purified B cells from a representative HC or an SLE patient (objective lens ×20). (C) Structured illumination microscopy superresolution imaging and analysis of IFN-β intracellular localization in representative B cells from SLE patients. Top, Representative images showing intra- versus extranuclear staining of IFN-β. The nucleus–cytoplasmic border was defined by DAPI staining (dotted white line) (objective lens ×100). Bottom, ImageJ quantitation of intra- and extranuclear intensity (left) and distribution (right) of IFN-β (n = 22 cells from three SLE patients). (D) HEK-Blue reporter cell analysis of type I IFN secretion by B cells from SLE (n = 9) or HC (n = 3) under the indicated conditions of stimulation. (E) Correlation of FACS detection of baseline (ex vivo) B cell IFN-β (MFI) with HEK-Blue analysis of IFN-β secretion from anti-Ig plus poly(I:C) stimulated B cells. All results are shown as mean ± SD (unpaired Student t test or Mann–Whitney U test for nonnormally distributed data). *p < 0.05, **p < 0.01, ***p < 0.005.

Close modal

To determine if B cells produced biologically active type I IFNs, an HEK IFN-α/β reporter cell line assay was carried out. Stimulation of the human B cell lymphoma cell line Ramos with TLR3 ligand poly(I:C) induced the highest IFN-β response compared with a TLR7 ligand (CL264) and a TLR9 ligand (ODN-2006) as measured by both intracellular FACS for IFN-β (Supplemental Fig. 2D, left) and by the HEK reporter assay (Supplemental Fig. 2D, right). Stimulation of purified SLE B cells with anti-Ig plus TLR3 induced an increased HEK reporter response compared with B cells derived from HCs (Fig. 2D). As an additional control, levels of IFN-β measured in the FACS assay were correlated with IFN-β protein secretion as measured by the HEK IFN-α/β reporter assay (Fig. 2E). These results are consistent with previous findings by Gram et al. (29), which reported type I IFN secretion by human B cells upon poly(I:C) stimulation and further suggest the importance of further evaluation of in vivo TLR3 ligands, including U1 RNA that may be associated with B cell secretion of functional type I IFN in SLE patients (30).

Intracellular IFN-β is associated with autoantibody production, renal disease, and AA race.

The higher expression and production of IFN-β from SLE B cells suggest that B cell intracellular IFN-β may be an important factor associated with SLE pathogenesis. We identified that patients who were seropositive for anti-dsDNA at the time of specimen collection exhibited significantly increased levels of IFN-β (MFI) in Tr and CD27+ memory B cells compared with SLE patients who were seronegative for anti-dsDNA at the time of collection (Fig. 3A). Subjects who were positive for anti-Sm at any time during their disease course exhibited a significant increase in IFN-β levels in Tr and CD27+ memory B cells, whereas subjects who were seropositive for anti-SSA exhibited increased IFN-β expression in Tr, naive, and CD27+ B cells (Fig. 3B, 3C). These data suggest an association between IFN-β expression and enhanced survival of B cells exhibiting reactivity with nucleic acid/protein complexes able to coactivate BCR and TLR signaling (31).

FIGURE 3.

Elevated B cell IFN-β in autoantibody-positive AA SLE patients. The MFI of IFN-β in the indicated populations of B cells in HCs or in SLE patients, segregated by (A) positivity of anti-dsDNA, (B) historic positivity of anti-Sm or (C) anti-SSA, (D) the presence of renal disease, (E) race (non-AAs versus AAs), (F) complement (C3/C4) normal versus low, (G) SLE Disease Activity Index ≤4 versus >4, and (H) with or without hydroxychloroquine (HCL) treatment. All clinical characteristics, except anti-Sm and anti-SSA, were collected at the time of PBMC sample collection. Results are mean ± SD. Statistical differences were determined by Mann–Whitney U test. *p < 0.05, **p < 0.01, ***p < 0.005 between the indicated comparisons.

FIGURE 3.

Elevated B cell IFN-β in autoantibody-positive AA SLE patients. The MFI of IFN-β in the indicated populations of B cells in HCs or in SLE patients, segregated by (A) positivity of anti-dsDNA, (B) historic positivity of anti-Sm or (C) anti-SSA, (D) the presence of renal disease, (E) race (non-AAs versus AAs), (F) complement (C3/C4) normal versus low, (G) SLE Disease Activity Index ≤4 versus >4, and (H) with or without hydroxychloroquine (HCL) treatment. All clinical characteristics, except anti-Sm and anti-SSA, were collected at the time of PBMC sample collection. Results are mean ± SD. Statistical differences were determined by Mann–Whitney U test. *p < 0.05, **p < 0.01, ***p < 0.005 between the indicated comparisons.

Close modal

SLE subjects with a history of renal disease also exhibited a significant increase in IFN-β in Tr and naive B cells compared with SLE patients without a history of renal disease (Fig. 3D). Interestingly, intracellular IFN-β in Tr and naive B cells was significantly higher in AA compared with non-AA patients (Fig. 3E). Levels of IFN-β in SLE B cells were generally significantly higher compared with HCs, even in comparisons between autoantibody-negative or otherwise low-severity patients and HCs (Fig. 3A–E). B cell endogenous IFN-β levels were not significantly different in SLE subjects with low complement or other clinical parameters, including the SLE Disease Activity Index or hydroxychloroquine treatment, but were significantly higher compared with HCs (Fig. 3F–H).

These results suggest that B cell IFN-β is most strongly associated with increased autoantibodies and renal disease and that polymorphisms in the IFN-β enhanceosome genes or other upstream genes may predispose some patients to the development of type I IFN dysregulation and autoimmune disease (32). This notion is supported by recent population-level studies that identified the IFNB locus as a trans-regulatory hotspot that controlled antiviral networks enriched in genes differentially expressed in AA versus European American healthy volunteers (33). Together, the present findings support the importance of cell-specific analyses of both IFNs and IFN response genes in patients of defined ancestral backgrounds, as type I IFN expression may not be highlighted in analyses of patient groups with diverse genetic ancestry. It is important to note that the present PCR-based targeted single-cell gene expression analysis approach was selected in order to detect IFN pathway genes, which exhibit a broad expression range spanning from lower-expressed type I IFN genes to higher-expressed ISGs. The detection of type I IFN genes may be more challenging in conventional RNA-sequencing analyses as detection of these genes can be limited by read depth. The present single-cell analyses reveal a new level of understanding in type I IFN dysregulation, as the proper regulation of these type I IFN–producing and –responding populations in early B cells may influence functional cell trajectories.

This work was supported by National Institutes of Health (NIH) Grants R01-AI071110 and R01 AI134023, U.S. Department of Veterans Affairs/Biomedical Laboratory Research and Development Grants I01 BX004049 and I01 BX000600, and a Lupus Research Alliance (LRA) Distinguished Innovator Award (to J.D.M.); NIH Grant R01-AI-083705 and a LRA Novel Research Award (to H.-C.H.); NIH Immunology T32 Training Grant 2T32AI007051-39 and a Lupus Foundation of America Gina M. Finzi Memorial Student Summer Fellowship (to J.A.H.); NIH 5R37AI049660 (to I.S.); Autoimmunity Center of Excellence – Emory University U19 AI110483 (to I.S.); and NIH Grants P30-AR-048311 and P30-AI-027767 to support flow cytometry, single cell gene expression, and imaging analyses.

The online version of this article contains supplemental material.

Abbreviations used in this article:

     
  • AA

    African American

  •  
  • HC

    healthy control

  •  
  • IFNP

    IFN-producing signature

  •  
  • IFNP/R

    mixed IFN and ISG producer/responder signature

  •  
  • IFNR

    IFN-responder signature

  •  
  • ISG

    type I IFN–stimulated gene

  •  
  • MFI

    mean fluorescence intensity

  •  
  • SLE

    systemic lupus erythematosus

  •  
  • UAB

    University of Alabama at Birmingham.

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The authors have no financial conflicts of interest.

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