Comprehensive analyses of B-cell compartments across the human body reveal novel subsets and a gut-resident memory phenotype

Abstract

Although human B cells have been extensively studied, most reports have used peripheral blood as a source. Here, we used a unique tissue resource derived from healthy organ donors to deeply characterize human B-cell compartments across multiple tissues and donors. These datasets revealed that B cells in the blood are not in homeostasis with compartments in other tissues. We found striking donor-to-donor variability in the frequencies and isotype of CD27+ memory B cells (MBCs). A comprehensive antibody-based screen revealed markers of MBC and allowed identification of novel MBC subsets with distinct functions defined according to surface expression of CD69 and CD45RB. We defined a tissue-resident MBC phenotype that was predominant in the gut but absent in blood. RNA-sequencing of MBC subsets from multiple tissues revealed a tissue-resident MBC gene signature as well as gut- and spleen-specific signatures. Overall, these studies provide novel insights into the nature and function of human B-cell compartments across multiple tissues.

Graphical abstract

Figure 1.

Multicolor flow analysis of B-cell compartments in spleen, blood, BM, and gut. Splenocytes, blood, BM, or intestinal tissue cells (gut) were stained with flow panels 1 or 2 (supplemental Tables 2 and 3), respectively. (A) Gating strategy for 10-color panel “Stain 1” flow cytometric analysis of donor D215 splenocytes to identify CD27^– (referred to as “naive B cells”) and CD27⁺ (referred to as “MBC,” acknowledging the generally accepted but imprecise convention^,) and their isotype distribution. Transitional B cells were identified as CD10^hi CD38^hi B cells. AFCs of the plasmablast/plasma cell lineage were identified in a broader forward scatter/side scatter (FSC/SSC) gate as CD38^brightCD138⁺ in the right panel. The latter expressed CD27 and displayed a range of CD19 expression, with most cells being positive, consistent with a plasmablast identity rather than a fully differentiated plasma cell (bottom right panel). MBCs showed clear surface IgM⁺ and IgG⁺ populations, which were less clear among these AFCs, likely due to reduced levels of surface immunoglobulin expression. Arrows indicate subsequent gating of populations, and numbers next to outlined areas indicate percentages of parent gate cells in gated populations. Key gated populations are labeled. (B) Distribution of B- cell compartments across human tissues (for gut data, after careful removal of mucosal epithelia and Peyer’s patches individually isolated cells from jejunum, ileum, and colon were analyzed and compiled, as these showed no significant differences among each other). The graphs show the percentages for CD27^–, CD27⁺, and transitional B cells of CD19⁺ live singlet lymphocytes (top panel), the percentages for total CD19⁺ lymphocytes and AFCs as percentage of all live cells cross indicated tissues (middle panel) and GC cells, which were gated as CD38^int or CD38^hi cells of all live CD19⁺ IgD^– CD10⁺ cells across tissues (for gating, see supplemental Figure 1). The blue numbers in the graphs represent the mean of the depicted population, also shown as purple lines in the graph. (C) Surface immunoglobulin isotype distribution of human organ donor samples. Upper panel: percentage of switched (IgG⁺; blue) and unswitched (IgM⁺ IgD⁺; red) CD27^– and CD27⁺ cells of CD19⁺ singlets with mean and standard deviation. Lower panel: graphing of data in upper panel with lines linking data from same samples. (D) “Inferred” IgA/IgE frequencies across tissues of CD27⁺ cells of CD19⁺ singlets with mean and standard deviation plotted as difference from 100% using the measured IgG and IgM/IgD frequencies depicted in panel C. (E) Correlation analysis between blood and spleen of CD27⁺, AFCs, and IgM⁺ IgD⁺ B-cell compartments within the same donors. P values were calculated as paired two-tailed Student t test (B-C) or linear regression (E).

Figure 2.

Effect of age, sex, race, and body mass index (BMI) on distribution of MBCs. Splenocytes, blood, BM, or intestinal tissue cells were stained as in Figure 1. (A) The frequencies of CD19⁺ CD27⁺ MBCs in these samples were correlated with age. Using the unpaired one-way analysis of variance with Tukey’s correction or the unpaired two-tailed Student t test analysis with Welch’s correction, no significant difference was found for spleen (P = .65), blood (P = .53), or BM (P = .86). For donors aged 18 to 49 years, there was a significant difference (*P = .036) in the gut compared with older donors. (B) Correlation of frequencies of CD19⁺ CD27⁺ MBCs with sex. (C) Correlation of frequencies of CD19⁺ CD27⁺ MBCs with race. The blood of white donors had significantly more MBCs than the blood of Hispanic donors (*P = .0391). (D) The resulting ratio of CD19⁺ CD27⁺ (memory) to CD19⁺ CD27^– (naive) B cells in spleen was further correlated with the BMI of the donors analyzed. Significance was tested by linear regression (slope, −0.06; R² = 0.047;P = .23, ns).

Figure 3.

Detection of morphologic differences within B-cell compartments across different tissues using viSNE analysis. (A) viSNE analysis was performed on total live, single B lineage cells by using default parameters in Amir et al. θ = 0.5, perplexity = 30; iterations = 1000. B cells from each donor were downsampled to 2000 events to assure equal weighting in the subsequent analysis. Concatenated fetal calf serum files from blood (n = 14 donors) and BM (n = 14) tissues were further downsampled to 22 000 cells to be equivalent to SP (n = 11). All markers from “Stain 1” (supplemental Table 2) except for the viability dye were included in viSNE clustering. The merged file is depicted at far left, followed by the individual tissues. Manual gate overlays are shown at the far right. Population definitions for manual gating are: naive B cell, CD19⁺ CD27^– CD95^– CD38^–; memory B cell, CD19⁺ CD27⁺ CD38^–; antibody- secreting cells (ASC), CD38^hi CD138⁺ CD27⁺; Ag-experienced, CD19⁺ CD27^– CD95⁺ CD38^–. (B) Heatmap profile of the individual markers as expressed in the concatenation of all 39 samples.

Figure 4.

Combination of surface markers CD45RB and CD69 defines new MBC subsets in tissues. Splenocytes were stained for flow cytometric analysis with “Stain 2” (supplemental Table 2). (A) Distribution of CD45RB and CD69 of CD19⁺ CD27^– and CD19⁺ CD27⁺ B cells of depicted donor spleens. The magenta letters and numbers show the sex (F = female; M = male) and the age (in years) of the donor. Numbers next to outlined areas indicate percentage of cells in gated populations. The indicated staining results in up to 4 different subsets, CD45RB SP, CD45/CD69 DP, CD69 SP, and CD45/CD69 DN. (B, left panel) CD45RB/CD69 distribution of human CD19⁺ CD27⁺ singlets within spleen, blood, BM, lymph nodes (LN), tonsil, or intestinal tissue (Gut) of indicated donors by utilizing “Stain 2” and “Stain 3” (supplemental Table 2). (B, right panel) shows the summary of CD45RB/CD69 distribution of CD19⁺ CD27⁺ MBCs within 21 spleen, 15 blood, 18 BM, 10 LN, 3 tonsil, and 14 gut samples. Asterisks indicate significant differences in CD45RB/CD69 subset distribution of indicated tissues compared with spleen using the unpaired two-tailed Student t test with Welch’s correction.

Figure 5.

Functional characterization of splenic CD45RB/CD69 MBC subsets. Splenocytes of indicated phenotype of NBCs (blue) and MBCs (red) were sort-purified and cultured for 5 days in the presence of ODN2006. (A) After 5 days of stimulation, cells were harvested, and activation markers CD25 and CD86 were analyzed by using flow cytometry. (B) Cells were subjected to flow cytometric analysis to measure AFC (CD27⁺ CD38⁺ of live singlets) frequencies. (C) Graphs show the AFC response measured by Enzyme-Linked ImmunoSpot assay for IgM (left panel) and IgG (right panel) isotype for the different subsets. D315 (blue), D443 (orange), D424 (purple), D269 (mustard), and D462 (red); P values for multiple comparisons were adjusted by using a Bonferroni correction (**q < 0.05; *0.05 ≤ q < 0.15).

Figure 6.

Gene expression analysis of CD45RB/CD69 subsets of spleen (SPL) and gut. Single-cell suspensions of SPL and ileum (ILE) were stained for RNA extraction after BD FACS Aria sorting of naive and MBC subsets defined by CD45RB and CD69 expression. (A) PC analysis of MBC subsets from SPL and ILE with genes that are differentially expressed between splenic DP and DN MBCs. The dotted ellipses represent the 95% confidence interval boundary for cell clusters. (B) PC analysis of MBC subsets from SPL and ILE with genes that are differentially expressed between CD69⁺ and CD69^– MBCs. (C) Heatmap of top 40 DEGs between CD69⁺ and CD69^– MBCs ranked by adjusted P value for all splenic MBC subsets. (D) Heatmap of differentially expressed TFs between splenic DP and DN MBCs. (E) Analysis of tissue-specific genes in DP and DN MBCs. Scatterplots display log2 fold-change of SPL DP vs DN samples on the x-axis and ILE DP samples vs SPL DN samples on the y-axis. Gray dots represent genes with significant (P adjusted <.1 and absolute value of log2 fold-change >1) differential expression in at least one of the 2 DP vs DN comparisons. Magenta dots denote “ILE-specific” and purple dots denote “SPL-specific” genes. Light blue and blue dots represent genes that are upregulated or downregulated, respectively, in both comparisons. (F) GSEA for ILE DP vs SPL DN on the TRM gene signature of CD8⁺ T-cell lineage (left panel) and CD4⁺ T-cell lineage (right panel) in lung tissue. In each plot, the x-axis shows the genes ranked by log fold-change between ILE DP vs SPL DN, and the y-axis shows the running enrichment score on the signature gene set with nominal P value indicated for 1000 permutations.