Fig 2: SLE patient T-bethi BDN cells rapidly differentiate in ASCs in the absence of BCR stimulation.(a–d) ASC generation from SLE BN cells requires early but transient BCR activation. Cartoon (a) depicting in vitro stimulation conditions to activate sort-purified T-betlo BN cells from SLE patients. BN cells were stimulated for 3 days with R848, cytokines (IFN?, IL-2, IL-21, BAFF) ± anti-Ig (Step 1) and then washed and recultured for an additional 3 days with the same stimuli ± anti-Ig (Step 2). Cells were analyzed by flow cytometry on day 6 (b–d). Phenotypic characterization (b) of IgDnegCD27neg BDN cells in cultures containing anti-Ig for all 6 days showing expression of T-bet, CD11c, FcRL5, CD21 and CXCR5 by the T-bethi BDN subset. The frequency (c) and number (d) of CD38hiCD27+ ASCs in cultures lacking anti-Ig (-,-), containing anti-Ig for all 6 days (+,+) or exposed to anti-Ig for the first 3 days only (+,-). (e) SLE patient T-bethi BDN cells rapidly differentiate in ASCs. Purified SLE B cell subsets (T-betlo BN, T-betlo CD11cnegCXCR5+ CD27negIgDneg DN1 memory cells, T-betlo CD27+ memory B cells (Bmem) and T-bethi CD11c+CXCR5neg DN2 cells) were stimulated with cytokines (IFN?, IL-21, IL-2, BAFF) and R848 for 2.5 days then counted and transferred to anti-IgG ELISPOT plates for 6 hr. The frequency of IgG ASCs derived from each B cell subset is shown. See Figure 8—figure supplement 1 for gating strategy to purify B cell subsets from SLE patients. Data shown in (c–d) are from a single SLE individual and are representative of 2 independent experiments. Data reported in (e) are representative of 3 independent experiments using B cells sorted from 3 different SLE donors. Statistical analyses were performed using one-way ANOVA with Tukey’s multiple comparison test (d–e). P values *<0.05, **<0.01, ***<0.001, ****<0.0001.

Fig 3: Expansion of the T-bethi DN2 subset in SLE patients correlates with systemic inflammatory cytokine levels.(a–f) Characterization of T-bethi B cells in peripheral blood B cell subsets from healthy donor (HD) and SLE patients. Gating strategy to identify CD38hiCD27+ ASCs, B cells (non-ASCs) (a, left) and double negative IgDnegCD27neg (BDN) cells (a, right) from the peripheral blood of HD and SLE patients. Frequency of BDN cells (b) within the total B cells. Subdivision of the SLE BDN population into CXCR5+CD11clo DN1 and T-bethi CXCR5negCD11chi DN2 populations (c) with T-bet expression levels (d) in each subset shown as a histogram. Expression of BLIMP1 (e) and IRF4 (f) by ASCs, T-bethi BDN cells and T-betlo B cells from SLE patients. Representative flow plots and mean fluorescence intensity (MFI) expression of BLIMP1 and IRF4 in each population are shown. (g) Correlation analysis between frequency of circulating T-bethi BDN cells and anti-Smith autoAb titers in SLE patients. (h–k) Correlation (h) between plasma cytokine levels and frequency of T-bethi BDN cells in SLE patient peripheral blood. Plasma concentration of IFN? (i), CXCL10 (j) and TNFa (k) in HD (blue symbols) and SLE patients (red symbols). See Figure 1—figure supplement 1 for analysis of T-bet expressing B cells in the Yaa.Fcgr2b-/- SLE mouse model. See Figure 1—figure supplement 2a for additional phenotypic characterization of T-bethi B cells in SLE patients. See Figure 1—figure supplement 2b for gating strategy to identify T-bethi BDN cells (DN2 cells) in SLE patients. Individual human subjects in each analysis are represented by a symbol. Horizontal black lines represent the median (b,i–k) within the group. Data shown from n = 20 HD and 40 SLE patients (b), representative flow plots from 16 SLE patients (c–d), 3 SLE patients (e–f), 16–18 SLE patients (g–h) or 5 HD and 26 SLE patients (i–k). Statistical analyses were performed using a non-parametric Mann-Whitney test (b,i–k), a one-way paired T test (e–f) or Spearman Correlation test (g–h). Correlation P and r values listed in the figure. P values *=0.05, **<0.01, ***<0.001.

Fig 4: Multiple influenza antigen modalities induce GC reactions and specific antibody secretion in human tonsil organoids(A) Experimental design and workflow for tonsil organoids. Cells and supernatants were assessed using multiple readouts to define immune signatures. Created with Biorender.com.(B and C) Representative flow cytometry staining (B) and summary data (C) for total B cell (CD45+CD19+CD3-) phenotypes from day 14 organoids stimulated with different influenza Ag modalities.(D) Representative flow cytometry staining of HA+ (red) and nonspecific (gray) B cells from day 14 organoids. Numbers indicate frequency of HA+ B cells of a given phenotype out of total HA+ B cells.(E) HA+ B cell frequencies.(F) HA+ plasmablast frequencies.(G) Quantification of HA-specific antibodies in day 14 organoid culture supernatants.(H) Virus neutralization by day 14 organoid culture supernatants; neutralization quantification by area under the curve (AUC).(I) Frequency of activated CXCR5+CD4 T cells and activated CD8 T cells on day 7. Activation was defined by dual expression of CD38 and HLA-DR. n = 12 donors (one experiment) for all data shown. *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001 using a Kruskal-Wallis test followed by paired Mann-Whitney U tests to compare groups. p values shown are for comparisons against the unstimulated control unless otherwise indicated by lines. Boxplots show the median, with hinges indicating the first and third quartiles and whiskers indicating the highest and lowest value within 1.5 times the interquartile range of the hinges. See also Tables 1 and S5 and Figures S1 and S2.