EZH2 represses the B cell transcriptional program and regulates antibody secreting cell metabolism and antibody production

Abstract

Epigenetic remodeling is required during B cell differentiation. However, little is known about direct functions of epigenetic enzymes in antibody secreting cells (ASC) in vivo. Here, we examined ASC differentiation independent of T cell help and germinal center reactions using mice with inducible or B cell-specific deletions of EZH2. Following stimulation with influenza virus or lipopolysaccharide, Ezh2-deficient ASC poorly proliferated and inappropriately maintained expression of inflammatory pathways, B cell lineage transcription factors, and Blimp-1 repressed genes, leading to fewer and less functional ASC. In the absence of EZH2, genes that normally gained H3K27me3 were dysregulated and exhibited increased chromatin accessibility. Furthermore, EZH2 was also required for maximal antibody secretion by ASC, in part due to reduced mitochondrial respiration, impaired glucose metabolism, and poor expression of the unfolded-protein response pathway. Together, these data demonstrate that EZH2 is essential in facilitating epigenetic changes that regulate ASC fate, function, and metabolism.

INTRODUCTION

The humoral immune response is initiated when B cells are stimulated to differentiate into antibody secreting cells (ASC), also known as plasma cells. Irrespective of how they are activated or the availability of T cell help, a distinct set of reprogramming events are required to terminate the B cell fate program and initiate a new gene expression program that supports enhanced metabolism and antibody secretion (1–3). The ASC transcriptional program is enabled by the expression of transcription factors, such as Blimp-1, XBP1, and IRF4, which reinforce and support ASC transcriptional changes (2, 4), that are coupled to a reorganization of the epigenome (5–7). Although the transcription factors and genes they regulate have been studied biochemically and genetically, little is known about the role for epigenetic modifiers in ASC function and programming.

Epigenetic modifications are dynamic during distinct stages of B cell differentiation. In both mice and humans, DNA methylation is primarily lost as B cells differentiate to ASC in response to both T cell dependent and independent stimuli (8–10). Deletion of the maintenance methyltransferase Dnmt1 leads to a reduction in germinal center (GC) B cells (11) but whether de novo DNA methylation is required for B cell differentiation is not known. Histone modifications, characterized by ChIP-seq, have cell-type specific patterns in naïve B cells, ex vivo differentiated ASC, and in GC B cells (12–16). However, few studies have examined the role of histone modifying enzymes using genetic approaches (5). Deletion of the histone acetyltransferase, MOZ, reduces GC B cells and skews responding B cells towards low affinity IgM⁺ memory B cells (17). Additionally, treatment of mice with histone deacetylase inhibitors reduces B cell responses (18), indicating that both erasing and writing de novo epigenetic modifications is an essential process in B cell differentiation. Importantly, epigenetic modifiers are frequent targets of both activating and inactivating mutations in lymphomas (19, 20). Therefore, a full understanding of epigenetic mechanisms and targets for distinct enzymes is important to manipulate B cell differentiation and understand the effects of therapeutics targeting these enzymes.

One of the best characterized repressive epigenetic histone modifications is the trimethylation of histone H3 at lysine 27 (H3K27me3), which is mediated by the polycomb repressive complex 2 (PRC2) (21, 22). Enhancer of zest 2 (EZH2) is the catalytic subunit of the PRC2 complex and functions as an essential transcriptional silencer (23–25). EZH2 is upregulated in pre-B cells, in which it is necessary for VDJ recombination during B cell development (26) and to repress germline Igκ transcription (27). EZH2 is expressed at low levels in quiescent, naïve B cells, but is highly upregulated in GC B cells where it facilitates cellular proliferation, protects from activation-induced cytidine deaminase (AID) off target activity, and represses the differentiation of GC B cells into ASC (15, 16, 28, 29). EZH2 interacts with distinct sets of transcription factors, such as BCL6 in GC B cells (29) and Blimp-1 in ASC (30), to direct cell-type specific gene repression programs. B cell specific-deletion of EZH2 leads to a loss of GC formation, thereby leading to defects in the formation of ASC (15, 16). However, no studies have directly assessed whether or how EZH2 functions in ASC.

Here we tested the role of EZH2 in two T-independent models of ASC differentiation, one initiated by the T-independent antigen, LPS, and the other initiated by influenza infection in the absence of CD4 T cells. We found that EZH2 was progressively upregulated in stimulated B cells, with expression peaking in ASC. In addition, B cell specific genes gained H3K27me3 in their promoters as ASC differentiation progressed, indicating that EZH2 may repress these genes. Following immunization with the T-independent antigen, LPS, or infection with influenza virus in the absence of T cells, mice with a tamoxifen-inducible Ezh2 deletion generated fewer ASC. The EZH2-dependent defect was cell intrinsic to B cells and resulted in the enhanced expression and increased chromatin accessibility of B cell genes that gain H3K27me3 and are normally repressed in ASC, including Blimp-1 target genes and inflammatory genes. Ezh2-deficient ASC failed to upregulate oxidative phosphorylation and glycolysis pathways, as well as the unfolded protein response, resulting in decreased secreted immunoglobulin. Together, these data demonstrate a critical role for EZH2 in the programming of T-independent B cell differentiation and define specific roles for EZH2 in regulating ASC function.

MATERIALS AND METHODS

Mice

Ezh2^fl/fl (JAX, 022626) (31), Rosa26^CreERT2 (JAX, 08463) (32), CD19^Cre (JAX, 06785) (33), CD45.1 (JAX, 002014), C57BL/6J (JAX, 00664) and μMT mice (JAX, 02288) (34) were purchased from Jackson lab and bred on site. CD45.2 μMT mice were bred onto the CD45.1 background. All animal protocols were approved by the Emory Institutional Animal Care and Use Committee (IACUC). Mice used for experiments were between 6.5-10 weeks old and were age and gender matched. Cre-mediated deletion was induced by the treatment of tamoxifen (Alfa Aesar, J63509) by daily i.p. injection for 5 consecutive days of 100 μl of 40 mg/ml. For LPS experiments, 50 μg (Enzo Life Sciences, ALX-581-008) was administered i.v., and mice were analyzed 3 days after inoculation. For mixed bone marrow chimera experiments, 10 × 10⁶ bone marrow cells from Ezh2^fl/+CD45.1/2 and Ezh2^fl/flRosa26^CreERT2/+CD45.2 were mixed at 1:1 ratios, transferred to lethally irradiated CD45.1 hosts, and the immune system allowed to reconstitute for 6 weeks. For wild-type cell division experiments, 20 × 10⁶ splenic CD45.1 B cells were labeled with CFSE and adoptively transferred into CD45.2 μMT hosts. For competitive cell division experiments, 10 × 10⁶ splenic B cells from Ezh2^fl/+CD45.1/2 and Ezh2^fl/flRosa26^CreERT2/+CD45.2 mice were mixed at a 1:1 ratio, labeled with CTV, and adoptively transferred to CD45.1 μMT hosts.

CD4⁺ T cell depletion and influenza infection

For depletion of CD4⁺ T cells, mice were treated with 200 μg anti-mouse CD4 (GK1.5, Bio X Cell, # BE0003-1) by i.p. injection 3 and 1 days before infection. Mice were infected intranasally with 15,000 v.f.u. of A/PR8/34 influenza virus and analyzed 7 days later.

Magnetic enrichment procedures

B cells were enriched from splenocytes from naïve mice by negative selection using CD43 microbeads (Miltenyi Biotec, #130-090-862). LPS induced ASC were enriched by positive selection of CD138⁺ cells from the spleens of mice 3 days post-LPS inoculation. Splenocytes were first stained with CD138-APC (Biolegend, #14205, Clone 281-2), and immunomagnetic enrichment was performed using anti-APC microbeads (Miltenyi Biotec, #130-090-855). Enriched populations were analyzed for purity by flow cytometry (Supplemental Figure 1A, 1B). For FACS sorting cellular division samples in Figure 1, following three days LPS inoculation, adoptively transferred CD45.1 cells were stained with CD45.1-PE (Bioscience, #12-0453-82, Clone A20) and immunomagnetic enrichment performed using anti-PE microbeads (Miltenyi Biotec, #130-048-801) prior to FACS sorting as previously described (8).

Figure 1. EZH2 is progressively upregulated during B cell differentiation in response to TI T-independent stimuli.

(A) The indicated divisions were isolated by FACS (left) and Ezh2 mRNA levels (right) quantitated by RT-qPCR and expressed relative to 18s rRNA as mean ±SD. *p < 0.05 by Student’s two-tailed T-test. These data are representative of three independent experiments. (B) Protein levels of EZH2 in naive B cells (nB) and LPS induced activated B cells (actB) and CD138⁺ antibody secreting cells (ASC). FMO, fluorescence minus one. Data is representative of two experiments. (C) Scatter plot of the average promoter H3K27me3 in nB and ASC versus the log2 fold change of H3K27me3 as determined by ChIP-seq. ChIP-seq data is summarized from 2 biological replicates of nB and ASC. (D) REVIGO (50) plot summarizing Gene Ontology terms for the 1,623 genes that gain promoter H3K27me3 in ASC from C.

Flow cytometry and cell sorting

For staining, cells were resuspended at 1 × 10⁶ cells/100 μl in FACS buffer (1× PBS, 1% BSA, 2 mM EDTA) and blocked with anti-Fc (Tonbo Biosciences, 2.4G2) at a concentration of 0.25 μg per 1 × 10⁶ cells for 15 min on ice. The following antibodies were used for FACS analysis: B220-PE-Cy7 (Tonbo Biosciences, #60-0452-U100, Clone RA3-6132), CD43-FITC (BD Pharmingen, #553270, Clone S7), CD19-PerCP-Cy5.5 (Tonbo Biosciences, #65-0193-U100, Clone 1D3), CD138-BV711 (BD Horizon, #563193, Clone 281-2), GL7-eFlour 660 (Invitrogen, #50-5902-82, Clone GL-7), CD45.1-FITC (Tonbo Biosciences, #35-0453-U500, Clone A20), CD45.2-PerCP-Cy5.5 (Tonbo Biosciences, #65-0454-U100, Clone 104), CD23-eFlour 450 (eBioscience, #48-0232-80, Clone B3B4), CD21-APC-Cy7 (eBioscience, #47-0211-80, Clone eBio8D9), IgM-FITC (eBioscience, #11-5890-85, Clone eB121-15F9), IgD-BV605 (BD Horizon, #583003, 11-26c.2a), CD11b-APC-Cy7 (Tonbo Biosciences, #25-0112-U100, Clone M1/70), F4/80-APC-Cy7 Biolegend, #123118, Clone BM8), Thy1.2-APC-Cy7 (Biolegend, #105328, Clone 30-H12), Ezh2-PE (BD Pharmingen, #562478, Clone 11/Ezh2), Annexin V-FITC (eBioscience, BMS500FI/100), Annexin V-APC (Invitrogen, 17-8007-74), Viability Ghost Dye-Red 780 (Tonbo Biosciences, 13-0865-T500), and Zombie yellow die (Biolegend, 77168). Influenza-specific PE-conjugated HA tetramers were previously described (35). Cells were stained for 30 min on ice protected from light and fixed with 1% paraformaldehyde. Intracellular staining was performed with the Fixation/Permeabilization kit (BD Biosciences, #555028) following the manufacturer`s protocol. Flow cytometry was performed on a Becton Dickinson (BD) LSRII using FACSDiva (v6.2). Flow cytometry data was processed by Flowjo (V9.9.6). Sorting of naïve B cells and ASC by FACS was performed on a BD FACSAriaII at the Emory Flow Cytometry Core. The following gating strategy preceded all flow cytometry analyses presented. Cells were gated on 1) lymphocytes (FSC-A x SSC-A); 2) singlets (FSC-W x FSC-H and SSC-W x SSC-H); and 3) live cells (Viability Dye⁻). Finally, non-B cell lineage cells were removed from the analyses based on the presence of Thy1.1, F4/80, and CD11c.

Deletion genotyping

DNA was extracted from purified splenic B cells following tamoxifen injection using the DNeasy Blood and Tissue kit (Qiagen, inc). 45 ng was used in a 35 cycle PCR reaction with a three-primer design that amplified either the wild-type or deleted alleles. PCR products were resolved on a 1.5% agarose gel. The following primers were used: Ezh2.del-fwd 5’-GCTAGGCCTGCTGGTAAATA-3’; Ezh2-del-rev 5’-AGGAAATGGCAGGGTCTTTAG-3’; Ezh2-del 5’-CAGTACAATCTCCTGTGTC-3’.

Enzyme-linked immunosorbent assay (ELISA)

ELISA plates (Evergreen Scientific, 52-333801301F) were coated with 5 μg/ml capture antibody (Southern Biotech, 5300-01B) or 1 μg/ml influenza hemagglutinin (HA) at 4°C overnight and blocked with 1% non-fat dry milk at room temperature for 2 hours. Standard antibodies and serum were bound to the plates at 4°C overnight, plates were washed, and secondary HRP-conjugated goat anti-mouse IgM or IgG antibodies were added for 2 hours at room temperature. Plates were developed with TMB ELISA peroxidase substrate (Rockland, #800-666-7625) and the reaction stopped with 0.2 M sulphuric acid. Plates were read at 450 nm with the Gen5 software.

RT-qPCR analysis

Total RNA was extracted from B cells and ASC using the RNeasy Mini Kit (Qiagen) and cDNA synthesized with SuperScriptII reverse transcriptase (Invitrogen) as described (36). qPCR was performed using SybrGreen incorporation on a BioRad CFX96 Thermocycler measuring the deleted exon of Ezh2 (Ezh2-del-fwd 5’-CAGGATGAAGCAGACAGAAGAG-3’; Ezh2-del-rev 5’-TTGTTGCCCTTTCGGGTT-3’) and normalized to 18S ribosomal RNA (18s-fwd 5’-GTAACCCGTTGAACCCCATT-3’; 18s-rev 5’-CCATCCAATCGGTAGTAGCCG-3’).

RNA-seq

Tamoxifen treated Ezh2^fl/fl (Ctl) and Ezh2^fl/flRosa26^CreERT2/+ (KO) CD138⁺ ASC were magnetically enriched three days following LPS inoculation. Three independent replicates were generated for Ctl and KO ASC. RNA was isolated using the RNeasy Mini Kit (Qiagen, Inc) and sequencing libraries generated using the mRNA HyperPrep kit with polyA selection beads (KAPA Biosystems) using 500 ng total RNA as input according to the manufacturer’s instructions. Final libraries were quality checked on an Bioanalyzer, quantitated by qPCR, pooled at equimolar ratio, and sequenced on a HiSeq2500 using paired-end 50 bp sequencing chemistry. Raw fastq files were mapped to the mm9 version of the mouse genome using Tophat2 (37) (v2.0.13) with the UCSC mm9 Known Gene table (38) as the reference transcriptome. PCR duplicates were removed from all downstream analyses with Picard (http://broadinstitute.github.io/picard/). Reads that overlapped exons were summarized into unique EntrezID genes using the GenomicRanges (39) (v1.22.4) package in R/Bioconductor. Genes that were not expressed at 1 read per million in at least three samples were discarded for low expression. Differential expression was tested using a pairwise test in edgeR (40) (v3.12.1). For GSEA, all detected genes were ranked by multiplying the sign of the fold change (+/-) by the –log10 of the p-value. This ranked gene list was used as input for the GSEA Preranked analysis. To determine genes involved in protein secretion and transport the UPR and XBP1 up gene lists were annotated using the Gene Ontology Consortium web portal (41). Genes categorized into protein transport (GO:0015031), protein localization (GO:0008104), or golgi vesicle transport (GO:0048193) biological processes were annotated. Sequencing depth for each gene was normalized to fragments per kilobase per million (FPKM) using custom scripts implemented in R/Bioconductor.

Preparation of Tn5 for ATAC-seq

In-house purification of adapter-loaded Tn5 transposase was performed as previously described (42). Briefly, the pTXB1-Tn5 plasmid (Addgene #60240) was transformed into C3013 cells (C3013l, NEB Inc) and a single colony grown in 250 mL of LB with 100 μg/ml Ampicillin at 37°C until the culture reached an A600 of 0.75-0.9. To induced Tn5 expression, isopropyl β-D-1-thiogalactopyranoside (IPTG) was added to a final concentration of 0.25 mM for 4 hours at 23°C. Cells were then pelleted at 2800 rpm for 15 minutes, resuspended in 15 mL HEGX (20 mM HEPES-KOH at pH 7.2, 0.8 M NaCl, 1 mM EDTA, 0.2% Triton X-100, 10% glycerol, complete with Roche protease inhibitors), and lysed with a French pressure cell (9,000 lb/in²). The resulting lysate was pelleted at 15,000 rpm for 30 minutes, and 550 μl of 10% PEI was added to the supernatant on a magnetic stirrer. The precipitate was removed via centrifugation at 12,000 rpm for 10 minutes. The supernatant was then loaded onto a 1 mL chitin column (S6651S, NEB Inc) and washed with 20 mL HEGX. On-column loading of Tn5 with pre-annealed Mosaic End double-stranded (MEDS) oligonucleotides was achieved by adding 60 nmoles of mixed and annealed Tn5 MED-p7/-p5 (ME-p7 = TCGTCGGCAGCGTCAGATGTGTATAAGAGACAG; ME-p5 = GTCTCGTGGGCTCGGAGATGTGTATAAGAGACAG; ME-rev = /5Phos/CTGTCTCTTATACACATCT) to the column in 1.2 mL HEGX buffer. After 48 hours, the column was washed with 20 mL of HEGX to remove unbound MEDS and cleavage of Tn5-MEDS was initiated by adding 1.2 mL HEGX, 100 mM DTT to the column. After 48-72 hours, small elution fractions were collected and those with the highest protein concentration were pooled and dialyzed overnight versus 2X Tn5 dialysis buffer (100 mM HEPES at pH 7.2, 0.2M NaCl, 0.2 mM EDTA, 2 mM DTT, 0.2% Triton X-100, 20% glycerol). Following dialysis, 0.6 volumes of glycerol was added to make the final storage buffer (50mM HEPES at pH 7.2, 0.1M NaCl, 0.1 mM EDTA, 1 mM DTT, 0.1% Triton X-100, 50% glycerol). Tn5 was dispensed into 50 μl aliquots and placed at -80°C for long-term storage.

ATAC-seq

Tagmentation was performed as described in detail previously(43, 44). Briefly, 2,000-4,000 cells from Ezh2^fl/fl (Ctl) and Ezh2^fl/flRosa26^CreERT2/+ (KO) nB and ASC from tamoxifen treated bone marrow chimeras three days following LPS inoculation were FACS sorted and tagmentation performed using 2.5 μl of Tn5 in 1× TD Buffer (Illumina, Inc) in 25 μl total volume for 1 hr at 37°C. Tagmented nuclei were lysed, DNA purified using a double SPRI-bead size selection (0.7× negative followed by 1× positive selection), and PCR amplified using Nextera Indexing Primers (Illumina, Inc) and the HiFi HotStart polymerase (KAPA Biosystems) for 14 cycles of PCR. Final libraries were purified using a second double SPRI-bead size selection (0.2× negative followed by 1× positive selection), quantitated using the Illumina qPCR Quant Kit (KAPA Biosystems), and sequenced using 50 bp paired-end chemistry on a HiSeq2500.

ATAC-seq data analysis

Raw ATAC-seq reads were mapped to the mm9 version of the mouse genome using Bowtie (45) (v1.1.1) with the default parameters. PCR duplicates were removed from all downstream analyses with Picard (http://broadinstitute.github.io/picard/). Enriched regions were identified using MACS2 (46) (v2.1.0.20140616). A composite list of all identified peaks in any sample was generated using the HOMER (47) (v4.8.2) ‘mergePeaks’ function. The read depth for each sample was then annotated for all peaks and differential accessibility calculated using the GLM function of edgeR (40) (v3.12.1) controlling for the mouse each sample originated from. PCA plots were generated using all differentially accessible region (DAR) and the vegan (v2.4-3) package in R/Bioconductor. Genomic annotation of peaks was performed using HOMER (47) (v4.8.2). Peaks that overlapped a promoter (+500, -2000 bp surrounding the TSS) were K-means clustered using the Biganalytics package (https://CRAN.R-project.org/package=biganalytics). Enriched transcription factor motifs were identified using HOMER (47) (v4.8.2) and the findMotifsGenome.pl script. Histograms of read depth surrounding each motif were generated using custom R/Bioconductor scripts.

ChIP-seq

ChIP was performed as described previously (48). For each immunoprecipitation, 10×10⁶ CD43⁻ splenic B cells or 1×10⁶ CD138⁺ splenic ASC were fixed in 1% formaldehyde for 10 min, chromatin isolated, and sonicated to an average size of 400 bp. 1 μg of anti-H3K27me3 (07-449, EMD Millipore) was prebound to Dynal Protein G magnetic beads (ThermoFisher Scientific) and DNA-chromatin complexes immunoprecipitated overnight at 4°C. DNA was reverse cross-linked and purified using a PCR cleanup kit (Qiagen). ChIP-DNA was diluted 1:20 and enrichment of the Hoxa9 (positive) and Actb (negative) loci tested by qPCR. Remaining ChIP-DNA was used as input for the KAPA HyperPrep kit (KAPA Biosystems, Inc). ChIP-seq libraries were sequenced on a HiSeq2500 using 50bp paired-end chemistry. Raw sequencing reads were mapped to the mm9 version of the mouse genome using Bowtie (45). Uniquely mappable and non-redundant reads were used for subsequent analyses. HOMER (47) software was used for peak calling and annotation. Data were normalized to reads per peak per million as previously described (44) using equation (1).

$$\mathit{rppm}=\mathit{reads}\times \left(\frac{1\times {10}^6}{\mathit{Unique Reads}\times \mathit{FRiP}}\right)$$

For the generation of scatter plots between nB and ASC samples the rppm read depth was quantile normalized and log2 fold change and the average log2 rppm between nB and ASC samples calculated.

Data Availability

All sequencing data is available at the NCBI GEO database (https://www.ncbi.nlm.nih.gov/geo/) under the accession GSE103195. All code and data processing scripts are available upon request.

Extracellular Flux Assays

A Seahorse Bioanalyzer XFe96 instrument was used for all extracellular flux assays. A FluxPak cartridge was hydrated at least 12 hours prior to running each assay with 200 μl dH2O in 37°C non-CO₂ incubator. 1 hour prior to each assay, dH2O was removed and 200 μl pre-warmed Seahorse calibrant solution (Agilent 103059-000) was added to all experimental wells. For the Mitochondrial stress test and measurement of oxygen consumption, purified cell populations were washed in Seahorse XF Assay media pH 7.4 ±0.1, supplemented with 1 mM sodium pyruvate, 2 mM L-glutamine (Sigma G7513), and 5.5 mM glucose at 37°C. For the Glycolysis stress test and extracellular acidification measurements, purified cell populations were washed in Seahorse XF Assay media pH 7.4 ±0.1 supplemented with 2 mM L-glutamine. Cells were washed 1× in appropriate media and counted by flow cytometry using AccuCheck counting beads (Invitrogen PCB100). Prior to each experiment, CellTak (Corning 354420) was diluted in sterile 1× PBS to a final concentration of 22.4 μg/ml and 25 μl added to each well of a Seahorse XFe96 cell culture plate, incubated for 20 mins at room temperature. The plates were washed with 200 μl dH2O and then 400,000 cells per well were plated and incubated in a 37°C non-CO2 incubator for 45 minutes prior to beginning the assay. The indicated drugs were diluted in assay-specific media for injection into each port. For the Mitochondrial stress test the ports were as follows: Port A, oligomycin (Sigma 75351), was used at a final concentration of 1 μM; Port B, FCCP (Sigma C2920) was used at a final concentration of 2.5 μM; and Port C injected a combination of Rotenone (Sigma R8875) and Antimycin A (Sigma A8674), each at a final concentration of 1 μM. For the Glycolysis stress test the ports were as follows: Port A, glucose (Sigma G8270), used at a final concentration of 10 mM; Port B, oligomycin used at a final concentration of 1 μM; and Port C, 2-deoxyglucose (Sigma D8375) at a final concentration of 50 mM.

RESULTS

EZH2 is progressively upregulated during Type I T-Independent B cell differentiation

Ezh2 is progressively upregulated during ex vivo B cell differentiation in response to LPS (49). To assess its expression pattern in vivo, we transferred CFSE-labeled CD45.1 B cells into CD45.2 μMT mice and subsequently inoculated the recipients with LPS to induce differentiation (8). Distinct divisions (Div0, 1, 3, 5, 8+) were FACS isolated and gene expression quantitated by qRT-PCR. For consistency across the differentiation models, we define plasma cells that have acquired CD138 expression as ASC. Ezh2 mRNA was upregulated during the divisions peaking in CD138⁺ ASC at Div8+ (Figure 1A). EZH2 protein levels were quantified in naïve splenic B cells (nB) and three days post LPS stimulation in B220⁺GL7⁺CD138⁻ activated B cells (actB) and CD138⁺ ASC. Similar to previous reports (15), EZH2 protein was relatively low in nB, elevated in actB, and peaked in ASC (Figure 1B).

To determine what genes might be affected by EZH2-mediated histone methylation, we performed ChIP-seq for H3K27me3 in nB and ASC, which were enriched to >94% purity (Supplemental Figure 1A and 1B). We found that 1623 gene promoters gained H3K27me3 in ASC (Figure 1C), suggesting these were targets of EZH2 mediated repression. Gene Ontology functional analysis summarized and condensed by REVIGO (50) (Figure 1D) indicated that these genes were enriched in pathways associated with B cell functions that are repressed in ASC, such as cell cycle (e.g., Cdkn1a), response to LPS (e.g., Nfkb1 and Tnf), and antigen presentation by MHC (e.g., H2-Ab1 and Cd74). Thus, these data indicate that the progressive upregulation of Ezh2 during B cell differentiation coincides with repression of the B cell transcriptional program in ASC.

ASC differentiation in response to Type I T-independent stimuli requires EZH2

To determine the role of Ezh2 in vivo, we crossed Ezh2^fl/fl mice (31) with tamoxifen inducible Rosa26^CreERT2 mice (32). Following tamoxifen treatment, we observed genomic rearrangement of the Ezh2 locus in splenic B cells and a significant reduction in Ezh2 transcripts and protein was observed (Supplemental Figure 1C-E). Ezh2 is essential for B cell development (26, 51); however, it is dispensable for peripheral B cell homeostasis (26). Consistent with previous findings, following tamoxifen induced deletion of Ezh2, a block in B cell development at the pre-B stage was observed (Supplemental Figure 1F). However, in the short time frame following deletion, no defect was observed in the viability of peripheral splenic B cells or in the frequency of marginal zone or follicular B cells (Supplemental Figure 1G-I).

To test the function of EZH2, Ezh2^fl/flRosa26^CreERT2/+ (ER^T2-Ezh2KO) and Ezh2^fl/fl (control) mice were treated with tamoxifen and subsequently inoculated with LPS to induce B cell differentiation. In ER^T2-Ezh2KO mice, we observed a significant reduction in the frequency and absolute numbers of splenic and lymph node ASC and actB cells (Figure 2A-E). These differences were not due to changes in the viability of ER^T2-Ezh2KO splenocytes (Figure 2G). Following LPS inoculation, a sharp increase in IgM titers occurred in control mice, however; ER^T2-Ezh2KO mice failed to reach the same titers of serum IgM (Figure 2H), a reduction that correlated with the decreased ASC response. IgG levels were also measured by ELISA and showed a similar reduction in ER^T2-Ezh2KO mice; however, the overall levels of IgG were very low in response to LPS (data not shown).

Figure 2. Maximal ASC differentiation in response to T-independent stimuli requires EZH2.

Ezh2^fl/fl (Ctl) and Ezh2^fl/flRosa26^CreERT2/+ (KO) mice were treated with tamoxifen followed by inoculation with LPS and analyzed as follows. (A) Frequency and (B) absolute number of splenic CD138⁺ ASC three days post LPS inoculation. A representative example is plotted on the left and the mean ±SD of 4 biological replicates are shown on the right. (C) Frequency of CD138⁺ ASC from the lymph nodes of mice treated as above. (D) Frequency and (E) absolute number of splenic B220⁺GL7⁺ actB cells. (F) Frequency of B220⁺GL7⁺ actB cells from the lymph nodes of mice treated above. (G) Frequency of viable cells from the spleen. (H) Serum IgM titers measured before (D0) and three days after LPS inoculation (D3) for the indicated genotype. Ezh2^fl/fl (Ctl) and Ezh2^fl/flCD19^Cre/+ (KO) mice were analyzed by flow cytometry as follows. (I) Frequency and (J) absolute numbers of splenic CD138⁺ ASC. (K) Frequency and (L) absolute numbers of splenic B220⁺GL7⁺ actB cells. See also Supplemental Figure 2. Significance was determined by Student’s two-tailed T-test. Each point represents independent biological samples and data is summarized as mean ±SD. The data presented represent between 2 and 5 groups of mice containing 3-4 mice per cohort.

The expression of Cre recombinase can negatively impact rapidly-proliferating cells (52). To ensure that the observed phenotype was specific to deletion of Ezh2, we compared hemizygous Ezh2^fl/+Rosa26^CreERT2/+ (ER^T2-Cre Ctl) mice with ER^T2-Ezh2KO and the Cre⁻ control mice described above. Three days post-LPS inoculation, ER^T2-Cre Ctl mice had similar frequencies of splenic actB and ASC as control mice and significantly more of each population than ER^T2-Ezh2KO mice (Supplemental Figure 2A, 2B). To further assess this system, the Cre recombinase expressed from the Cd19 locus was used (33), which bypasses the developmental defects observed in the ER^T2-Ezh2KO strain, allowing normal B cell development to occur (26) and facilitating B cell specific deletion. Here, Ezh2^fl/flCD19^Cre/+ (CD19-Ezh2KO), CD19^Cre/+ (CD19-Cre Ctl) and Ezh2^fl/fl (Ctl) mice were inoculated with LPS and differentiation tested as above. Similar to tamoxifen induced Ezh2 deletion, CD19-Ezh2KO mice formed 50% fewer ASC and actB cells compared to controls (Figure 2I-L, and Supplemental Figure 2C, 2D). Together, these data demonstrated that Ezh2 was required for efficient ASC differentiation in response to Type I T-independent stimuli.

EZH2 controls the early T-independent burst of influenza-specific ASC

During the humoral response to protein antigens and pathogens, a burst of antibody secreting ASC provides an initial surge of serum antibodies before T-cell dependent processes facilitate affinity maturation and class switched B cell responses (53, 54). In response to the hapten NP, EZH2-deficient B cells displayed reduced NP-specific serum antibody titers as early as day 7 (15), suggesting defects in early ASC responses. To assess the early T-cell independent differentiation events, CD4 T cells were first depleted from CD19-Ezh2KO and control cohorts of mice using an anti-CD4 antibody and subsequently infected with the A/PR8/34 (PR8) strain of influenza. CD4 T cells were fully depleted at both the time of PR8 infection and the assay end-point at day 7, at which no germinal center B cells were detected (Supplemental Figure 3A, 3B). At day 7, control mice exhibited expanded lymph node CD138⁺ ASC, whereas the frequency and absolute number of ASC were significantly reduced in CD19-Ezh2KO mice (Figure 3A, 3B). Antigen-specific PR8 responding cells were identified using B-cell tetramers against HA (35), and the frequency of HA⁺ ASC, HA⁺ actB, and total HA⁺ cells was significantly reduced in CD19-Ezh2KO compared to control mice (Figure 3C–3G and Supplemental Figure 3C, 3D). Additionally, assessment of antibody levels revealed an increase in HA-specific IgM titers from day 0 to 7 in control mice but significantly reduced levels in CD19-Ezh2KO at mice at day 7 (Figure 3H). Together, these data define an essential role for EZH2 in the formation of T-independent ASC in response to both non-protein and protein antigens.

Figure 3. EZH2 is required for the early burst of Influenza-specific ASC in the absence of CD4 T cells.

Ezh2^fl/fl (Ctl) and Ezh2^fl/flCD19^Cre/+ (KO) mice were CD4 T cell depleted and infected with influenza PR8 and analyzed by flow cytometry 7 days post infection. (A) Frequency and absolute number (B) of CD138⁺ ASC in the bronchial lymph node. (C) Frequency and absolute number (D) of HA-specific ASC cells. (E) Frequency of B220⁺GL7⁺ actB cells in the bronchial lymph node. (F) Frequency of HA-specific actB. (G) Frequency of HA-specific lineage negative (Thy1.1⁻F4/80⁻CD11c⁻) B cells. (H) ELISA for HA-specific IgM in naive (D0) and seven days (D7) post PR8 infection. See also Supplemental Figure 3. Significance was determined by Student’s two-tailed T-test. Each point represents independent biological samples and data is summarized as mean ±SD. The data presented represent between 2 and 5 groups of mice containing 3-4 mice per cohort.

Cell intrinsic requirement for EZH2 in ASC differentiation

To determine a cell intrinsic role for Ezh2 in ASC differentiation, bone marrow from CD45.2 ER^T2-Ezh2KO and CD45.1/2 control mice were mixed 1:1 and transferred into lethally irradiated CD45.1 hosts. At 4 weeks, the percentages of CD45.2 and CD45.1/2 donor cells in the periphery of recipient mice were similar (Figure 4A). After six weeks, mice were treated with tamoxifen (as above) to induce EZH2 deletion and subsequently inoculated with LPS. Three days post-LPS, both ER^T2-Ezh2KO (CD45.2) and control cells were identified (Figure 4B) and a significant reduction in CD138⁺ ASC in the spleen (Figure 4C) and lymph nodes (Figure 4D) was observed in cells transferred from ER^T2-Ezh2KO mice. Additionally, the frequency of actB cells was significantly reduced (Figure 4E, 4F). These data indicate that EZH2 performs an essential cell intrinsic function during LPS-induced B cell differentiation.

Figure 4. Cell intrinsic requirement for EZH2 in ASC differentiation.

The bone marrow from Ezh2^fl/+CD45.1/2 (Ctl) and Ezh2^fl/flRosa26^CreERT2/+CD45.2 (KO) mice were transferred to lethally irradiated CD45.1 wild-type hosts and analyzed at 4 weeks for chimerism (A). At 6 weeks, the mice were treated with tamoxifen and inoculated with LPS and analyzed three days later. (B) Frequencies of chimeric populations following LPS treatment. Quantitation of CD138⁺ ASC frequencies from the (C) spleen and (D) lymph nodes of LPS inoculated mice. Quantitation of B220⁺GL7⁺ actB cell frequencies from the (E) spleen and (F) lymph nodes of LPS inoculated mice. Significance was determined by Student’s two-tailed T-test. Each point represents independent biological samples and data is summarized as mean ±SD. Data is representative of two independent experiments with 4-5 mice per group.

EZH2 represses B cell transcription factor networks

Transcriptome profiling was performed on tamoxifen treated ER^T2-Ezh2KO or control ASC following LPS stimulation to determine the molecular consequences of Ezh2 deletion. In ER^T2-Ezh2KO ASC 1498 genes were significantly upregulated (FDR < 0.05, logFC > 1) while only 79 were down regulated (Figure 5A). Although not entirely, these data are largely consistent with a repressive function for EZH2. Confirming the tamoxifen-induced deletion in ER^T2-Ezh2KO ASC, an 18-fold reduction in the transcripts across Ezh2’s deleted exons was observed compared to wild type (Supplemental Figure 4A). Moreover, in ER^T2-Ezh2KO ASC, Ezh2 was the most significantly down regulated gene by an FDR differential of 10¹¹³. Gene set enrichment analysis (GSEA) (55, 56) indicated that in the absence of Ezh2, genes involved in the regulation of inflammation and NF-κB mediated TNFα signaling, and the p53 pathway were upregulated (Figure 5B). During B cell development EZH2 repressed the cell cycle inhibitor Cdkn2a and prevented p53 activation (51); thus, EZH2 may be performing a similar role in ASC.

Figure 5. EZH2 is a transcriptional repressor in ASC.

RNA-seq was performed on enriched splenic ASC from tamoxifen treated Ezh2^fl/fl (Ctl) and Ezh2^fl/flRosa26^CreERT2/+ (KO) mice three days post LPS inoculation. (A) Volcano plot summarizing differentially expressed genes (DEG) (FDR < 0.05, log2FC > 1) between Ctl and KO ASC. RNA-seq data represents three biological replicates of Ctl and KO ASC. (B) Top GSEA gene sets. (C) The log2FC for DEG was plotted versus the log2 fold change in promoter H3K27me3 enrichment between nB and ASC. (D) Heatmap of H3K27me3 enrichment for 2 kb surrounding promoters of 1,498 upregulated DEG. Data were ranked by the change in H3K27me3 in ASC versus nB. Color bars map distinct clusters of genes from C. ATAC-seq was performed on Ctl and KO nB and ASC from tamoxifen treated bone marrow chimeras three days following LPS inoculation (See Figure 4). (E) Promoter accessibility (ATAC-seq) Heatmap for genes in D was categorized using K-means clustering (k = 3). Three independent replicates of Ctl nB, Ctl ASC, and KO ASC, and two replicates of KO nB are shown. (F) ATAC-seq derived volcano plot showing differentially accessible regions (DAR) (FDR < 0.05, log2FC > 1) comparing KO and Ctl ASC. (G) For the indicated genes, the change in expression by RNA-seq are plotted with a genome plot depicting chromatin accessibility and H3K27me3 enrichment data for each locus. ATAC-seq data is summarized as mean of three biological replicates for Ctl nB, Ctl ASC, and KO ASC, and two replicates for KO nB. H3K27me3 ChIP-seq data represents the mean of two biological replicates for nB and ASC. Promoter regions are highlighted. FPKM, fragments per kilobase per million; rpm, reads per million; rppm, reads per peak per million. (See also Supplemental Figure 4)

To determine if the differentially expressed genes (DEG) were direct targets of EZH2, we compared the change in promoter H3K27me3 enrichment between nB cells and ASC with the change in expression between ER^T2-Ezh2KO versus control ASC. We found that 923 genes were upregulated in ER^T2-Ezh2KO ASC and gained promoter H3K27me3 in ASC compared to nB cells (Figure 5C, 5D), indicating that these DEG are direct repression targets of EZH2. Bcl6 was among the top genes that gained promoter H3K27me3 in wild-type ASC and was increased in expression in ER^T2-Ezh2KO ASC, suggesting that other B cell transcription factors could be dysregulated. GSEA analysis was performed using a set of transcription factors specifically expressed in Follicular B cells (FoB) compared to bone marrow ASC (57) and showed that this set of transcription factors were significantly upregulated in ER^T2-Ezh2KO ASC (Figure 5B). Other examples included, the developmental transcription factor Klf4; inflammatory genes Ifit3, and Lta; and cell cycle inhibitors Cdkn1a and Slfn1 were significantly upregulated in ER^T2-Ezh2KO ASC and demonstrated extensive gains in H3K27me3 in ASC (Figure 5G and Supplemental Figure 4B). These results indicate that EZH2 functions to epigenetically silence key B cell genes involved in inflammatory responses.

EZH2 controls chromatin accessibility in ASC

The derepression of 923 genes could be directly attributed to a failure to gain H3K27me3 in ASC. However, an additional 575 DEG gained expression and were marked by H3K27me3 in both nB and ASC, suggesting they are normally repressed in both cell types. To further understand the consequences of Ezh2 deletion, we performed the assay for transposase accessible sequencing (ATAC-seq) (43, 44) on nB cells and ASC from ER^T2-Ezh2KO and control mice. Principle component (PC) analysis of all differentially accessible loci (DAR) revealed a large difference between nB and ASC regardless of EZH2 status defined by PC1 (Supplemental Figure 4C), indicating that in the absence of EZH2, most differentiation associated chromatin accessibility changes occurred normally. PC2 separated control and ER^T2-Ezh2KO ASC but not nB, which contained minimal DAR (Supplemental Figure 4D), indicating chromatin accessibility differences were primarily specific to Ezh2-deficient ASC.

Promoter accessibility of genes upregulated in ER^T2-Ezh2KO ASC was annotated in nB and ASC and the patterns categorized by k-means clustering. Three distinct patterns of promoter chromatin accessibility were observed: k1, promoters that lost accessibility between nB and ASC; k2, promoters that were minimally accessible in nB, remained such in control ASC yet gained accessibility in ER^T2-Ezh2KO ASC; and k3, promoters that were inaccessible in nB and control ASC and only gained accessibility in ER^T2-Ezh2KO ASC (Figure 5E). We found that promoters of DEG in ER^T2-Ezh2KO ASC were more accessible than those in control ASC. Direct comparison to control ASC revealed 1317 loci that gained accessibility in ER^T2-Ezh2KO ASC compared to only 347 that decreased (Figure 5F). Examples of chromatin accessibility changes include specific regions located in Bcl6 and Klf4 (k1), Hoxa1 (k2), and Eml6 (k3) (Figure 5G).

The failure to repress key B cell transcription factors suggested that such factors may contribute to a unique accessibility footprint in ER^T2-Ezh2KO ASC. Analysis of DNA sequence motifs within regions of increased accessibility revealed an enrichment for CTCF, ETS, OCT, and IRF family transcription factor binding sites (Figure 6A). Although CTCF was expressed at similar levels in nB and ASC, the presence of CTCF sites within DAR suggests a potential defect in rearranging the 3D genome during ASC differentiation (58). Transcription factor footprinting for the occurrence of each motif revealed unique patterns at each binding site and clear increases in accessibility surrounding each motif in ER^T2-Ezh2KO compared to control ASC (Figure 6A). Increased accessibility could be due to an increase in expression of a transcription factor family member that binds to a specific motif, such as the ETS factor SPIB that is upregulated, or due to a failure to recruit EZH2 to a region. Thus, these data depict the epigenetic derepression of loci controlled by EZH2 through increases in gene expression and chromatin accessibility at sites normally repressed in ASC.

Figure 6. Blimp-1 target genes are upregulated in EZH2-deficient ASC.

(A) ATAC-seq based transcription factor footprinting histograms for motifs enriched in KO versus Ctl ASC from Figure 5F. The significance of enrichment for each motif is indicated and the enriched motif is displayed. Histograms summarize three independent replicates of ATAC-seq data from Ctl and KO ASC. (B) GSEA assessing the enrichment of Blimp-1 repressed genes (30) in Ctl and KO RNA-seq data. (C) Representative RNA-seq data summaries for the indicated genes. Data is representative of three biological replicates and is summarized as mean ±SD. FPKM, fragments per kilobase per million. (D) Genome plots depicting the loci in C. ASC-Blimp-1 data was previously reported and was normalized to reads per million (30). H3K27me3 ChIP-seq data represents the mean of two biological replicates for nB and ASC. rppm, reads per peak per million.

Blimp-1 repressed genes are upregulated in the absence of EZH2

Blimp-1 can elicit gene repression through physical interactions with epigenetic modifiers (59–61), including EZH2 (30). GSEA was performed using a high-confidence set of Blimp-1 repressed target genes derived from transcriptional profiling of genetic deletions and ChIP-seq data (30). Of the 109 genes that overlapped in the datasets, 96% demonstrated higher expression in the absence of EZH2 (Figure 6B). Examples included the ETS family transcription factor gene Spib, which was upregulated and contained one of the strongest Blimp-1 binding sites (Figure 6C, 6D). Additionally, genes for Klf2, a transcription factor involved in B cell homing and migration (62), the toll-like receptor Tlr9, and Btg1, which functions as a negative regulator of cellular proliferation and apoptosis (63, 64), all contained Blimp-1 binding sites at regions that gained H3K27me3 in ASC and were upregulated in the absence of EZH2. These data provide an in vivo link between EZH2 and Blimp-1 in ASC and demonstrate that epigenetic modifications via EZH2 may be required for the Blimp-1 mediated gene repression program.

Deletion of Ezh2 impairs the proliferation of activated B cells

Recent studies in B cells and B-cell derived lymphomas demonstrated that inhibition or depletion of EZH2 resulted in cell cycle arrest, impaired proliferation, and apoptosis (16, 28, 65–67). Indeed, a cell cycle gene set was one of the most down regulated gene sets in ER^T2-Ezh2KO ASC (Figure 5B). Additionally, the EZH2 target gene Cdkn1a (16), which encodes the P21 cell cycle inhibitory kinase, is upregulated in ER^T2-Ezh2KO ASC (Supplemental Figure 4B). These data suggest that the observed decrease in actB and ASC was due to an EZH2-mediated defect in the proliferative phase of B cell differentiation. To test this hypothesis, tamoxifen treated CD45.2 ER^T2-Ezh2KO and CD45.1/2 control B cells were labeled with CTV, transferred into congenically marked CD45.1 μMT hosts, and stimulated to differentiate by inoculation with LPS. After three days, ER^T2-Ezh2KO and control B cells were analyzed for their ability to divide and differentiate (Figure 7A). Consistent with previous results (8), eight cellular division were typically observed with control B cells (Figure 7B, 7C). In contrast, ER^T2-Ezh2KO B cells initially proliferated normally through three cellular divisions but were reduced in number at all subsequent divisions. The B cell activation marker GL7 was progressively upregulated in control cells through 8 divisions. However, ER^T2-Ezh2KO B cells failed to gain additional GL7 expression after 3 divisions (Figure 7D, 7E). Analysis of differentiation kinetics through expression of CD138 revealed that B cells from control and ER^T2-Ezh2KO mice both achieved 7-8 divisions before an accumulation of CD138⁺ ASC were observed, however the ER^T2-Ezh2KO CD138⁺ cells were reduced in frequency (Figure 7F, 7G). These data indicated that in the absence of EZH2, a defect in the ability to proliferate, possibly through the failure to repress negative regulators of the cell cycle, contributes to the reduced numbers of differentiated ASC.

Figure 7. Deletion of Ezh2 impairs B cell activation and proliferation in vivo.

B cells isolated from tamoxifen treated Ezh2^fl/+CD45.1/2 (Ctl) and Ezh2^fl/flRosa26^CreERT2/+CD45.2 (KO) mice were labeled with CTV, transferred into CD45.1 μMT mice, and inoculated with LPS as above. (A) Frequencies of transferred populations in the spleens of mice three days following LPS treatment. (B) Histograms and (C) absolute numbers of CTV labeled in Ctl and KO cells. (D) Representative flow cytometry plot and summary of the frequency of GL7⁺ cells. (E) The absolute number of B220⁺GL7⁺ cells in each division from D. (F) Representative and summary of the frequency of CD138⁺ cells from the above cells. (G) The absolute number of CD138⁺ cells in each division from F. Significance was determined by paired Student’s T-test. For summary graphs, the mean ±SD is shown. Data is representative from two independent experiments containing cohorts of 5 animals each.

EZH2 is required for the metabolic programming of ASC

Although a subset of ER^T2-Ezh2KO B cells could undergo eight rounds of division and differentiate into ASC, the molecular phenotype of these cells indicated that they were likely dysfunctional (Figure 5). To directly measure the antibody secreting capacity of these cells, control and ER^T2-Ezh2KO ASC, derived following LPS induced differentiation in vivo were purified, equal numbers cultured for 3.5 hrs, and antibody titers from the resulting supernatant measured by ELISA. On a per cell basis, ER^T2-Ezh2KO ASC secreted 50% fewer molecules of IgM (Figure 8A). However, no difference in the levels of IgM mRNA transcripts (Figure 8B) or intracellular IgM protein levels (Figure 8C) were observed between control and ER^T2-Ezh2KO ASC, indicating that the IgM deficiency may lie in protein secretion.

Figure 8. EZH2 is required for maximal Ab secretion and ASC metabolism.

Ezh2^fl/fl (Ctl) and Ezh2^fl/flRosa26^CreERT2/+ (KO) mice were treated with tamoxifen and inoculated with LPS as above and analyzed as follows. (A) ELISA measuring IgM titers at 3.5 hrs of culture from 1×10⁶ LPS-induced splenic CD138⁺ ASC from Ctl and KO mice. (B) Expression of IgM transcripts measured by RNA-seq from splenic Ctl and KO CD138⁺ cells following LPS inoculation. See Figure 5. (C) Measurement of intracellular IgM in Ctl and KO CD138⁺ ASC. Representative flow cytometry data is plotted and the MFI summarized as mean ±SD. (D) GSEA assessment of RNA-seq data from Figure 5A for the indicated gene sets. “Xbp1 up” genes were previously described (68). False discovery corrected q-value is shown. Genes involved in protein secretion and transport and indicated in red below. (E) GSEA assessment of RNA-seq data from Figure 5A for the indicated gene sets. (F) Extracellular flux analysis of Ctl and KO ASC described above. Oxygen consumption rate (OCR) before and after treatment with the indicated pharmacological inhibitors. Data represents the combination of two independent experiments containing cohorts of 4 animals. Each point represents the mean ±SD. (G) Extracellular acidification rate of ASC as in F measured at steady state without glucose, after addition of glucose, oligomycin, and 2-deoxy-D-glucose (2DG). Data represents the combination of two independent experiments containing cohorts of 4 animals. Each point represents the mean ±SD. Significance determined by Student’s two-tailed T-test.

Consistent with this idea, GSEA indicated that the unfolded protein response (UPR) and genes upregulated by the transcription factor XBP1 (68) failed to be induced in ER^T2-Ezh2KO ASC (Figure 8D). Annotation of genes involved in protein secretion and transport revealed that these genes were more highly expressed in control than ER^T2-Ezh2KO ASC, consistent with decreased IgM levels in the cultures of ER^T2-Ezh2KO ASC. XBP1-mediated induction of the UPR pathway is also important for increased mitochondrial function (69) and ASC require a high metabolic capacity to support synthesis and secretion of antibody molecules (70). Indeed, GSEA revealed the expression of oxidative phosphorylation and glycolysis metabolic pathways were enriched in control but not ER^T2-Ezh2KO ASC (Figure 8E). Moreover, EZH2 regulates the mTOR pathway in follicular lymphoma (71), suggesting the reduced IgM secretion in ASC may be due to a metabolic defect.

To test the hypothesis that ER^T2-Ezh2KO ASC were metabolically distinct, extracellular flux assays were performed to probe both mitochondrial respiration and glucose metabolism. The oxygen consumption rate was measured as a readout for mitochondrial respiration. At basal levels, ER^T2-Ezh2KO ASC consumed significantly less oxygen than control ASC (Figure 8F). Following inhibition of ATP synthase with oligomycin, similar declines were observed in oxygen consumption. Maximal respiration rates were also greater in control ASC compared to ER^T2-Ezh2KO as shown by the addition of carbonyl cyanide-4-(triflurome-thoxy) phenylhydrazone (FCCP) to the system. This suggests that control ASC are more capable of utilizing the oxidative phosphorylation metabolic pathway than ER^T2-Ezh2KO. Because metabolism is a balance between multiple metabolic pathways and the expression of the glucose transporter Glut1 was upregulated after LPS stimulation ex vivo (72), the ability of ASC to metabolize glucose was assessed. The extracellular acidification rate, which is measured by pH changes associated with excretion of lactic acid generated from pyruvate (73), can be used to measure rates of glucose metabolism. Addition of glucose to glucose-deprived ASC resulted in enhanced lactate secretion in control compared to ER^T2-Ezh2KO ASC, resulting in a significantly higher ability to perform glycolysis (Figure 8G). These data therefore define EZH2 as an essential upstream regulator of ASC metabolic potential.

DISCUSSION

Here, we tested whether EZH2 regulated ASC differentiation using both type I and type II T-independent B cell responses in vivo. Consistent with other data (26), we found that EZH2 is not required for homeostasis of naïve follicular and marginal zone B cells. However, immunization with T-independent antigens or protein antigens in the absence of T cell help generated poor B cell responses in Ezh2-deficient mice. The role of EZH2 was B cell-intrinsic, as Ezh2-deficient B cells also poorly differentiated into ASC in mixed bone marrow chimeric mice. As EZH2 is the continued target of therapeutic intervention, these data have implications for the effect of inhibitors on normal humoral immune responses.

The poor differentiation of Ezh2-deficient ASC could be in part, to a defect in the ability of Ezh2-deficient ASC to upregulate genes involved in the cell cycle. In fact, the top upregulated gene sets in Ezh2-deficient ASC were inflammatory and p53 pathways, with each consisting of genes that function to negatively regulate the cell cycle. Among the most induced genes within these sets was Cdkn1a, which encodes the G1/S cell cycle checkpoint inhibitor P21 (74). ChIP-seq data showed that Cdkn1a has increased H3K27me3 across its promoter and proximal upstream sequences, confirming a previously described direct role for EZH2 in its regulation (15, 16, 28). In vivo, B cells undergo approximately eight cell divisions before differentiating into ASC (8). Ezh2-deficient cells went through fewer divisions, resulting in fewer cells that acquired the actB cell phenotype (GL7⁺) and fewer CD138+ ASC, consistent with the continued activity of cell cycle inhibitors. This result is consistent with findings in multiple myeloma in which EZH2 is overexpressed and pharmacological inhibition limits cell growth (75, 76). Thus, the failure to repress cell cycle inhibitors, such as Cdkn1a, is a likely mechanism leading to decreased numbers of ASC observed.

Ezh2-deficient ASC also failed to repress the transcriptional program associated with mature B cells, including the accumulation of H3K27me3 at genes, such as Ciita that function in MHC-II antigen processing, B cell transcription factors like Bcl6, as well as NF-κB mediated inflammatory genes. Transcriptome profiling of discrete divisions in vivo following B cell activation with LPS revealed the third cell division following activation as the first stage in which gene repression occurred. This division also coincided with the down regulation of NF-κB regulated genes (8). Ezh2-defient cells displayed a proliferation defect at division three as well, suggesting that this stage may be an initial differentiation checkpoint requiring the repression of a set of genes to continue the process.

The failure to repress B cell-associated transcriptional programs was also associated with the enrichment of transcription factor binding motifs in regulatory regions of those genes. For example, in Ezh2-deficient ASC, CTCF and the ETS family transcription factor binding motifs were significantly more accessible. The chromatin landscape associated with CTCF within the MHC-II region is reorganized during B cell differentiation in response to LPS (58) and CTCF is known to function in the maintenance of GC B cells (77). It is possible that this architecture may not be properly organized in the absence of EZH2. The most differentially regulated ETS family member was Spib, which is normally silenced in ASC through direct repression by Blimp-1 (30, 78). Furthermore, genes normally repressed in both B cells and ASC and marked by H3K27me3, including Hoxa1 and Eml6, failed to remain repressed. Of note, classifying promoter accessibility changes of genes that failed to be repressed by EZH2 revealed a category of promoters that lost accessibility normally in ASC. This indicates that chromatin accessibility data derived from ATAC-seq may not correlate with failed epigenetic processes at all loci, and that additional epigenetic mechanisms are required for full repression of the B cell transcriptome.

Deficiencies in proliferation and repression of B cell fate accounted for reduced ASC numbers; however, Ezh2-deficient ASC secreted less IgM on a per cell basis, indicating that ASC-specific pathways were dysregulated. From the adoptive transfer proliferation experiment in which splenic B cells were transferred into μMT hosts (Figure 7), it is likely that the observed EZH2 defect lies in the marginal zone B cell compartment; however, we did not specifically assess the impact of EZH2 deletion on B1 B cells, which secrete IgM in response to LPS (79). ASC have enhanced metabolic potential and upregulate ER stress response pathways to facilitate antibody secretion (3, 8, 80). Transcriptome profiling demonstrated that both of these processes were altered in the absence of EZH2 with reduced expression of genes in the UPR, glycolysis, and oxidative phosphorylation pathways. Oxidative phosphorylation is fueled by pyruvate molecules derived from both glycolysis and fatty acid oxidation. Here only glycolysis was assayed; therefore, we cannot rule out a role for EZH2 in regulating fatty acid metabolism. Ezh2-deficient ASC failed to upregulate XBP-1 target genes, which is required for the induction of the UPR (81). Cellular metabolism is regulated through the PI3K signaling pathway with the mTORC1 and mTORC2 kinases representing essential nodes (3). ASC require the continued activity of mTORC1 to maintain maximal levels of antibody secretion (82). In the absence of EZH2, the ability of ASC to perform oxidative phosphorylation and metabolize glucose through the glycolysis pathway was reduced and correlated with reduced ability to secrete antibodies. These data converge with recent results describing a role for EZH2 mediated control of mTORC1 in follicular lymphoma (71) and indicate that there is an epigenetic component to the induction and/or maintenance of ASC metabolism. Therefore, Ezh2-dependent and possibly other epigenetic mechanisms are required to program ASC metabolic potential and facilitate antibody secretion.

Metabolic reprogramming following activation in immune cells is necessary for effector functions in both the myeloid and lymphoid lineages and epigenetic enzymes require cofactors synthesized during metabolism (83). However, it is less clear how the metabolic changes are programmed and inherited through cell fate transitions. While not essential for their survival, bone marrow ASC require the continued activity of Blimp-1 to sustain the UPR and secrete antibodies (68). These results pose that EZH2 may also be continually required for these ASC functions. If ASC require the constant activity of transcription factors and epigenetic enzymes to maintain metabolic potential, this suggests that throughout their lifetime ASC may be able to adapt to nutrient availability and respond to environmental cues. These data therefore identify an EZH2-dependent epigenetic process that facilitates ASC metabolism.

ABBREVIATIONS

actB

activated B cell

ASC

antibody secreting cell

CD19-Ezh2KO

CD19^CRE Ezh2 knock-out

DAR

differentially accessible loci

DEG

differentially expressed gene

ER^T2-Ezh2KO

ER^T2-CRE Ezh2 knock-out

GC

germinal center B cell

GSEA

gene set enrichment analysis

H3K27me3

histone H3 lysine 27 trimethylation

nB

naïve B cell

PR8

A/PR8/34 strain of influenza

UPR

unfolded-protein response