Patients diagnosed with SLE according to the 1997 American College of Rheumatology classification criteria (22) were recruited at Tohoku University Hospital, Japan. The disease activities of SLE were assessed using the SLEDAI scoring system. Healthy donors were recruited from the Department of Hematology and Rheumatology, Tohoku University Graduate School of Medicine, Japan. The present study was approved by the Medical Ethical Review Board at Tohoku University School of Medicine. The donor profiles of SLE patients used in the clinical correlation (SLE1–SLE8) and microarray analysis (SLE9–SLE12) were presented in Supplementary Tables 1 and Table 1, respectively.

The following antibodies were utilized for cell surface staining (fluorescence-labeled monoclonal antibodies against human were obtained from BD Biosciences, unless otherwise stated): PE anti-CD43, APC anti-CD38, V500 anti-CD27, PerCP-Cy5.5 anti-CD19, V450 anti-CD3, V450 anti-CD14, and V450 anti-CD16 (all from BD Biosciences). The following antibodies were utilized for intracellular staining: Zenon Alexa Fluor 488 Rabbit IgG Labeling Kit (Invitrogen), rabbit IgG isotype control (Cell Signaling Technology, Danvers, MA). For phosphoprotein analysis, resting or stimulated B cells were fixed with BD Phosflow Fix Buffer I (BD Bioscience) and permeabilized with Perm Buffer III (BD Bioscience). Subsequently, the B cells were stained with Violet Fluorescent Cell Barcoding Dye 450 and 500 (BD Bioscience) to be distinguished by different stimuli and time points. After washing, cells were stained with the following Alexa Fluor 647-conjugated antibodies: anti-PTEN (Phosphatase and Tensin Homolog Deleted from Chromosome 10), anti-Syk (Spleen tyrosine kinase) (pY352), anti-Btk (Bruton’s tyrosine kinase) (pY223), anti-ERK (extracellular signal-regulated kinase)1/2 (pT202/pY204), anti-p38 (pT180/pY182), anti-NF-κB (nuclear factor-kappa B) p65 (pS529), anti-IκBα (NF-κB inhibitor α), anti-Akt (protein kinase B) (pS473), anti-mTOR (mammalian target of rapamycin) (pS2448), anti-S6 (ribosomal S6 kinase) (pS235/pS236), mouse IgG1 isotype, and mouse IgG2b isotype (all from BD Biosciences). For the detection of apoptotic cells, Near SR LIVE/DEAD fixable dead cell stains (Thermo Fisher Scientific) and APC-Annexin V (BD Biosciences) were used. Flow cytometry was performed using the FACSCanto II system (BD Biosciences), and data were analyzed using the FlowJo Software (BD Biosciences) and the Cytobank platform (Cytobank Inc.).

Peripheral blood mononuclear cells (PBMCs) were freshly isolated from healthy donors or SLE patients via Ficoll (GE Healthcare, Uppsala, Sweden) gradient centrifugation. For the microarray analysis, first, B cells were positively isolated with CD19 microbeads (Miltenyi Biotec, Auburn, CA), then CD19⁺CD27⁻ CD38⁻CD43⁻CD3⁻CD14⁻CD16⁻(naïve B cell), CD19⁺CD27⁺ CD38⁻CD43⁻CD3⁻CD14⁻CD16⁻ (memory B cell), and CD19⁺CD38⁺CD43⁺CD3⁻CD14⁻CD16⁻ (CD38⁺CD43⁺ B cell) were gated and isolated using FACSAria II (BD). For B cell cultures, B cells were isolated from PBMCs using the B Cell Isolation Kit II (Miltenyi Biotec).

For culture medium preparation, we used RPMI 1640 (Sigma–Aldrich, Saint Louis, MI) supplemented with 10% (v/v) heat-inactivated fetal bovine serum (FBS) (Biological Industries, Cromwell, CT), 100 U/ml penicillin, and 100 µg/ml streptomycin. F (ab′)₂ Fragment Goat Anti-human IgG + IgM (H + L) (Jackson ImmunoResearch, West Grove, PA) was added at a final concentration of 50 µg/ml. Human IFNα A/D (Bg/II) was obtained from PBL Assay Science (Piscataway, NJ), and MEGACD40L was purchased from Enzo Life Science (NY) and added to the culture to stimulate CD40. The FOXM1 inhibitor FDI-6 was purchased from Axon Medchem (Groningen, Netherlands). Freshly isolated B cells were incubated in 96-well U-bottom plates (Falcon, Durham, NC) at a concentration of 1 × 10⁵ cells/200 µl. B cells were stimulated with anti-IgG/IgM (50 µg/ml) 6 h after B cell isolation. For pretreatment with IFNα (pre-IFN), 1,000 U/ml of IFNα was added 6 h before and during anti-IgG/IgM stimulation. In some experiments, 100 ng/ml MEGACD40L (Enzo Life Sciences) was simultaneously added with stimulation with anti-IgG/IgM. All culture experiments were conducted in triplicate.

IgG secretion was determined by ELISPOT assay using Human IgG ELISpotBASIC kit (Mabtech, Cincinnati, OH). Mouse anti-human IgG antibodies (1.5 ug/ml) were coated on the PVDF-membrane in MultiScreen-IP plates (Merck Millipore, Carrigtwohill, Ireland) over night. After washing, the membranes were blocked with PBS containing 1% BSA. Subsequently, CD38⁻CD43⁻ B cells and CD38⁺CD43⁺ B cells isolated with flow cytometry were seeded onto each well with the cell number of 500, 100, 20/well. After 24 h incubation in RPMI1640 supplemented with 10% FBS, the membranes were washed, and biotinylated anti-IgG Fc antibodies (2 ug/ml) were added. After washing, the membranes were incubated with streptavidin-horseradish oxidase and developed with substrate for ELISpot (Mabtech).

Microarray data were collected from freshly isolated naïve B cells, memory B cells, and CD38⁺CD43⁺ B cells of four SLE patients and four healthy donors. After the isolation of each B cell subset, the total RNA was extracted in each B cell subset using TRIzol (Invitrogen, Carlsbad, CA) and RNeasy Mini Kit (QIAGEN, Hilden, Germany). Briefly, cell pellets were lysed in TRIzol and chloroform was added. After centrifugation, upper layers were mixed with equal volume of ethanol, and the mixtures were transferred to spin columns of RNAeasy Mini Kit. After washing the columns, total RNAs were eluted with RNAse free water. After amplification of targeted cRNA and labeling with Cyanine-3 using Low Input Quick Amp Labeling Kit (Agilent Technologies, Santa Clara, CA), fragmented cRNAs were applied to Whole Human Genome Oligo microarray 8 × 60 K v2 (Agilent Technologies) and then hybridized. The array slides were scanned using Agilent’s Microarray Scanner System (Agilent Technologies). The obtained microarray data were normalized using the GeneSpring 12.5 software (Agilent Technologies). Differentially expressed genes (DEGs) were determined by comparing the gene expression levels of each B cell subset (naïve, memory, and CD38⁺CD43⁺CD27⁺ B cells) between SLE patients and healthy donors. DEGs in each comparison were defined as significantly changed (p < 0.05, moderate t-test) and more than two-fold upregulated or less than 0.5-fold downregulated genes. Heat maps were generated after hierarchical clustering. Canonical pathway and upstream analyses of DEGs were conducted using the Ingenuity Pathway Analysis program (QIAGEN). Significantly activated pathways and upstream molecules (transcriptional factors) were defined as significantly different (p < 0.01) using Fisher’s exact test and a Z score > 2.0. Type I IFN signature genes (23 genes) (23) and cell cycle signature genes (231 genes) (24) were calculated as follows: first, the maximum value in any gene row was normalized to be 1. Then, the sum of the value of each sample was obtained to calculate the gene expression scores. To identify genes that specifically changed in the SLE plasmablast, similar entity analysis was conducted using the GeneSpring software with cutoff range of 0.6–1.0 using the DEGs of the plasmablast. The microarray data were deposited in Gene Expression Omnibus [GSE156751].

Isolated B cells were labeled using CellTrace Violet Cell Proliferation Kit (Invitrogen) and analyzed via flow cytometry after the culture was prepared. Cell proliferation was assessed using a proliferation index (PI). PI denotes the average number of cell divisions and is calculated using the following formula. PI = Σ 0 i N i Σ 0 i N i / 2 i

where N denotes the percentage of B cells in each generation, and i denotes the number of cell divisions.

After the total RNA was extracted from B cells using the RNeasy Mini Kit, cDNA was synthesized using the ReverTra Ace qPCR RT Kit (TOYOBO, Osaka, Japan). The following primers were used: 18S ribosomal RNA forward primer : 5′-AGGAATTCCCAGTAAGTGCG-3′, 18S ribosomal RNA reverse primer : 5′-GCCTCACTAAACCATCCAA-3′, FOXM1 forward primer : 5′-ATACGTGGATTGAGGACCACT-3′, FOXM1 reverse primer : 5′-TCCAATGTCAAGTAGCGGTTG-3′, CCNA2 forward primer : 5′-CGCTGGCGGTACTGAAGTC-3′, and CCNA2 reverse primer : 5′-GAGGAACGGTGACATGCTCAT-3′.

Quantitative real-time PCR (qPCR) was performed using the QuantiTect SYBR Green PCR Kit (QIAGEN) with the C1000 Thermal Cycler (Bio-Rad, Hercules, CA). The calculated copy numbers were normalized according to the 18S rRNA expression. The gene expression levels were standardized by each corresponding 18S rRNA expression level.

After 120 min stimulation of B cells isolated from healthy donors by anti-IgG/IgM antibody with or without pre-IFN treatment, cells were lysed with 1x SDS sample buffer (Cell Signaling Technologies) and sonicated. The cell lysates were electrophoresed on 12% polyacrylamide gel and then transferred onto Immobilon transfer membranes (Millipore). The membranes were treated with rabbit anti-phosphorylated Akt (Cell Signaling Technologies), rabbit anti-phoshorylated p38 (Cell Signaling Technologies), and rabbit anti-tubulin antibody (abcam, Cambridge, UK). IRDye 800CW-conjugated goat anti-rabbit (LI-COR Biosciences, Lincoln, NE) was used as a secondary antibody. Fluorescence intensity was measured, and densitometric analysis was performed with an Odyssey Infrared Imaging System (LI-COR Biosciences).

Data are expressed as mean ± SD. The statistical significance of the differences was determined via ANOVA, paired and unpaired t-test. Correlation coefficients and statistical significance between the frequencies of CD38⁺CD43⁺ B cells and SLEDAI scores were obtained with Spearman’s rank correlation analysis. Moreover, the differences were considered statistically significant for p-values less than 0.05. Statistical analyses were conducted using the GraphPad Prism 7 software (San Diego, CA).

Conventionally, plasmablasts are considered as CD19^loCD27^hiCD38^hi B cells (25). In flow cytometric analysis, CD19^loCD27^hiCD38^hi B cells were presumably overlapped with the population of CD19⁺CD27⁺ memory B cells and are difficult to be precisely gated or sorted from other cells. It has been reported that CD20⁺CD27⁺CD43⁺ B cells exhibit similar characteristics to those of plasmablasts (26). We compared CD38⁺CD43⁺ with CD19^loCD27^hi B cells via flow cytometry and found that CD38⁺CD43⁺ B cells were highly overlapped with CD19^loCD27^hi B cells (Figure 1A). The frequencies of CD38⁺CD43⁺ cells among CD19⁺ B cells were significantly elevated in active SLE than healthy controls (Figure 1B) and significantly reduced after intensification of the immunosuppressive therapy for active SLE and correlated with SLEDAI scores (Supplementary Figure 1). To determine whether CD38⁺CD43⁺ B cells are eligible for plasmablasts, we evaluated the cell size, gene expression, and antibody secreting capacity of the B cell subset. The cell size was prominently increased in CD38⁺CD43⁺ B cells of both healthy donors and SLE patients (Figure 1C). The expressions of IRF4 and PRDM1 were increased in plasmablasts (27) and, as revealed by microarray analysis, were significantly increased in CD38⁺CD43⁺ B cells of both healthy donors and SLE patients (Supplementary Figures 2A and B). Isolated CD38⁺CD43⁺ B cells were shown to have the capacity to secrete IgG, whereas CD38⁻CD43⁻ B cell not (Figure 1D). Additionally, CD38⁺CD43⁺ B cells can be clearly gated from other cells (Supplementary Figure 3). We considered CD38⁺CD43⁺ B cells as plasmablasts and gated and sorted CD38⁺CD43⁺ B cells for the analysis of plasmablasts in the following experiments.

To determine DEGs between healthy donors and SLE patients in naïve, memory, and CD38⁺CD43⁺ B cells, we compared the gene expression profiles of each B cell subset of SLE patients with those of healthy donors. The purity of the isolated cells was comparable between healthy donors and SLE patients (Supplementary Figure 3). Figure 2A presents the DEGs in each B cell subset. A total of 594 genes were upregulated, and 595 genes were downregulated in the naïve B cell subset; 527 genes were upregulated, and 381 genes were downregulated in the memory B cell subset; and 1,452 genes were upregulated, and 723 genes were downregulated in the CD38⁺CD43⁺ B cell subset. The top 30 upregulated or downregulated genes among the DEGs are presented in Supplementary Table 3.

Canonical pathway analysis on IPA revealed that several cell-cycle-related pathways were activated, as well as interferon signaling, whereas only the interferon signaling pathway was significantly activated in each of the naïve and memory B cell subset (Table 2). We calculated the gene expression scores (Figure 2B) after the selection of type I IFN signature genes (23 genes) (23) and cell cycle signature genes (231 genes) (24) from the microarray data of healthy donors and SLE patients. IFN signature gene expressions were significantly increased in each B cell subset of SLE patients compared with healthy donors (Figure 2B, upper). Moreover, the gene expressions of cell cycle signature were higher only in CD38⁺CD43⁺ B cells of SLE patients than in those of healthy donors (Figure 2B, lower). Upstream analysis revealed that several transcriptional factors related to cell cycle, as well as IFN-related factors, were significantly upregulated in CD38⁺CD43⁺ B cells of SLE patients more than in those of healthy donors (Table 1). Among the activated transcriptional factors, the expressions of E2F1, E2F2, and FOXM1 genes were shown to be more significantly upregulated in CD38⁺CD43⁺ B cells of SLE patients compared with other B cell subsets (Figure 2C and Supplementary Figure 4). We consider the gene expression pattern of FOXM1, which is a master regulator for cell cycle and cell survival (19), as a prototype of SLE plasmablast-specific genes; hence, we conducted an analysis of find similar entities for FOXM1 from DEGs in the CD38⁺CD43⁺ B cell subset to determine the genes that are significantly/uniquely upregulated in CD38⁺CD43⁺ B cells of SLE patients. Furthermore, 725 genes were chosen as similar entities to FOXM1 (Figure 2D). Canonical pathway analysis revealed that the genes of entities similar to FOXM1 strongly correlated with the cell cycle (Table 3).

We assessed the effects of pre-IFN on B cell activation following stimulation with anti-IgG/IgM antibody via flow cytometry. Pre-IFN significantly enhanced cell enlargement (Figure 3A) and cell division (Figure 3B) following stimulation with anti-IgG/IgM antibody.

The interaction of CD40 on B cell and CD40 ligand (CD40L) on T cell is one of the main systems providing T cell help to B cell activation (Quezada, ARI, 2004). To examine the effect of pre-IFN on T cell help, CD40L was co-added in B cell culture. CD40L counteracted the effects of pre-IFN on cell enlargement and cell division stimulated by anti-IgG/IgM antibody (Figures 3A, B), although co-stimulation with anti-IgG/IgM antibody and CD40L also enhanced B cell activation, as determined via the evaluation of cell size and cell division. Pre-IFN improved cell survival in unstimulated and activated B cells (Supplementary Figure 5). Subsequently, we compared the gene induction of FOXM1 and CCNA2 (a downstream molecule of FOXM1) between cultures with and without pre-IFN after stimulation with anti-IgG/IgM antibody. The expressions of FOXM1 and CCNA2 were significantly increased in IFNα pretreated B cells more than those cultures without IFNα (Figure 3C).

To examine the effects of pre-IFN on plasmablast differentiation, the induction of CD38⁺CD43⁺ B cells after stimulation with anti-IgG/IgM was evaluated via flow cytometry. Plasmablast differentiation required pre-IFN in B cells stimulated by anti-IgG/IgM (Supplementary Figure 6).

To determine what BCR (B cell receptor) signaling pathway was promoted by pre-IFNα, we examined the phosphorylation of BCR signaling proteins via flow cytometry. As presented in Figure 4, multiple proteins were prominently phosphorylated after BCR triggering with anti-IgG/IgM antibody. IκBα was reciprocally degraded by NF-κB phosphorylation, which indicated that stimulation with anti-IgG/IgM antibody also activated the NF-κB pathway. Contrary to the pan-activation of B cell signaling pathways with BCR triggering (except PTEN), pre-IFN preferentially enhanced the phosphorylation of Akt, mTOR, S6, and p38 (Figure 4B). Western blotting also revealed that pre-IFN increased phosphorylation of Akt and p38 after stimulation anti-IgG/IgM antibody. Pre-IFN enhanced the phosphorylation of Akt and S6 after stimulation with anti-IgG/IgM antibody and CD40L (Supplementary Figure 7), as well as without CD40L (Figure 4B). In addition, co-stimulation with CD40L significantly promoted the activation of p38 and NF-κB pathways stimulated with BCR, and the effects of pre-IFN on the activation of these pathways were blunted by co-stimulation with CD40L (Supplementary Figure 8).

Microarray data indicated that FOXM1, and its downstream molecules were significantly upregulated in CD38⁺CD43⁺ B cells of SLE patients (Figure 2). We assumed that FOXM1 can be a candidate molecule for plasmablast-targeting therapy in SLE, as it is considered as a multipotent master transcriptional factor for cell proliferation and apoptosis (19). Then, we examined the effects of FOXM1 inhibitor FDI-6 on cell division and apoptosis in stimulated B cells with or without pre-IFN. FDI-6 significantly downregulated the expressions of FOXM1 and CCNA2 in B cells activated by anti-IgG/IgM and pre-IFN (Figure 5A). Cell division after stimulation with anti-IgG/IgM was significantly inhibited with FDI-6 and prominently with IFNα pretreatment (Figure 5B). Next, we evaluated the effects of pre-IFN on FDI-6-induced apoptosis in B cells activated by anti-IgG/IgM via flow cytometry. FDI-6 had just mild effect on induction on early apoptosis of activated B cells (Figure 5C).