Abstract
Differentiation of naïve peripheral B cells into terminally differentiated plasma cells is characterized by epigenetic alterations, yet the epigenetic mechanisms that control B cell fate remain unclear. Here we identified a central role for the histone H3K79 methyltransferase DOT1L in controlling B cell differentiation. Murine B cells lacking Dot1L failed to establish germinal centers (GC) and normal humoral immune responses in vivo. In vitro, activated B cells showed aberrant differentiation and prematurely acquired plasma cell features. Mechanistically, combined epigenomics and transcriptomics analysis revealed that DOT1L promotes expression of a pro-proliferative, pro-GC program. In addition, DOT1L supports the repression of an anti-proliferative, plasma cell differentiation program by maintaining expression of the H3K27 methyltransferase Ezh2, the catalytic component of Polycomb Repressor Complex 2 (PRC2). Our findings show that DOT1L is a central modulator of the core transcriptional and epigenetic landscape in B cells, establishing an epigenetic barrier that warrants B cell naivety and GC B cell differentiation.
INTRODUCTION
B lymphocytes are key cellular components of the adaptive immune system and their functional deregulation is associated with immune deficiencies and autoimmunity1, 2. Several well-coordinated processes during B cell differentiation coincide with specific adaptations of the epigenome3, 4, 5. Given the critical contribution of B cells to the immune system, it is important to understand the molecular mechanisms underlying the epigenetic programming during their differentiation.
We previously identified DOT1L as a conserved epigenetic writer that catalyzes mono-, di-, or tri-methylation of lysine 79 of histone H3 (H3K79me)6, 7. DOT1L-mediated H3K79me resides on the nucleosome core surface away from histone tails 8 and is associated with active transcription. However, its function in gene regulation remains unclear9, 10, 11. DOT1L has gained wide attention as a specific drug target in the treatment of Mixed Lineage Leukemia (MLL) characterized by rearrangements of the MLL gene. Oncogenic MLL-fusion proteins recruit DOT1L, leading to hypermethylation of H3K79 and increased expression of MLL-target genes, thereby introducing a druggable dependency on DOT1L activity12, 13, 14, 15, 16, 17, 18. In addition, we recently observed a similar dependency in a mouse model of thymic lymphoma caused by loss of the histone deacetylase HDAC119. While DOT1L is emerging as an appealing drug target, the role of DOT1L in gene regulation during normal lymphocyte development is not known. Analysis of publicly-available RNA-sequencing data shows that Dot1L expression is regulated during B cell development (see below).
An active humoral immune response is initiated by the expansion of clonally selected, antigen-primed B cells within secondary lymphoid organs. This results in the formation of a specific micro-environment, known as the germinal center (GC) 20, 21. Rapidly proliferating GC B cells pass through the process of somatic hypermutation that lays the molecular basis of antibody affinity maturation22, 23, 24, 25, 26. Ultimately, B cells selected on the basis of antibody affinity may differentiate either into memory B cells to establish long-term immunological memory or via a plasma blast stage into terminally differentiated, antibody secreting plasma cells. Development and functionality of B lymphocytes is associated with dynamic changes in the epigenetic landscape27. Recent studies indicate that specific alterations in B cell function and identity are intimately linked with well-established histone modifications such H3K4 trimethylation (H3K4me3) related with active gene promoters28, 29, and H3K27me3 associated with gene repression30. Furthermore, the H3K27 methyltransferase EZH2, the catalytic component of the Polycomb repressor complex 2 (PRC2) has been shown to have an essential role in establishing GC B cells31. Here we determined the role of the H3K79 methyltransferase DOT1L in normal murine B cell development by deleting Dot1L early in the B cell lineage and investigating specific dependencies of B lineage cells on DOT1L. Our findings show that DOT1L fine-tunes the core transcriptional and epigenetic landscape of B cells and in doing so establishes a critical epigenetic barrier coordinating the stepwise transitions towards terminally differentiated plasma cells.
RESULTS
Effective deletion of Dot1L in B-cell lineage cells
Given the DOT1L-dependencies in leukemia13, 14, 32, 33 and lymphoma19, we quantified the expression of Dot1L during normal B cell development using publicly available data34. We observed that Dot1L is transcriptionally regulated in B cell subsets and higher expressed in GC B cells (Fig. 1a). To determine the relevance of this regulation in controlling the development and differentiation of B lineage cells, we inactivated Dot1L during early B cell development by crossing the Mb1-Cre knock-in allele into a Dot1Lfl/fl background. DOT1L is the sole enzyme responsible for H3K79me; knock-out of Dot1L has been shown to lead to complete loss of H3K79me10, 19, 35, 36. However, loss of H3K79 methylation requires dilution of modified histones by replication–dependent and –independent mechanisms of histone exchange37, 38, 39. Mb1-Cre was chosen because it leads to deletion of Dot1L at an early stage in B cell development that is followed by successive rounds of replication. This ensures complete loss of H3K79me in all subsequent B cell subsets. Dot1L was specifically and efficiently deleted in B cells, as confirmed by intracellular staining for H3K79me2 in proB, preB, immature B cells, and mature B cells. While some proB cells retained H3K79me2, preB cells and all stages beyond, lacked detectable levels of H3K79me2 (Fig. 1b). As a control, the methylation mark remained unchanged between DOT1L-proficient and - deficient mature T cells (Fig. 1b). We refer to Mb1-Cre+/−;Dot1Lfl/fl and Mb1-Cre+/−;Dot1Lwt/wt B cells as Dot1L KO and WT cells, respectively. To study the impact of Dot1L ablation on the development of B cells in the bone marrow, we determined the cellularity of specific developmental subsets in the DOT1L-proficient and -deficient settings. Early ablation of Dot1L resulted in an overall 1.6-fold reduction of bone marrow B lineage cells. This reduction appeared to be caused primarily by an early differentiation block at the proB to preB cell stage; preB cell were reduced 1.8-fold in the Dot1L KO as compared to WT and proB cells were increased by 2.0-fold. In line with this partial developmental inhibition, the cellularity of all subsequent stages of development including immature B and mature B cells were significantly reduced in the bone marrow (Fig. 1c and Supplementary Fig. S1a). Reduced preB cells could be a result of impaired VDJ recombination in absence of DOT1L-dependent pro-recombinogenic H3K79me marks40, 41, but other causative factors cannot be excluded. Regardless of this partial developmental block, B cells could mature in the absence of DOT1L and H3K79 methylation, providing a system to study the role of this epigenetic mark in B cell differentiation.
Lack of DOT1L prohibits differentiation of germinal-center B cells
In the spleen of Mb1-Cre+/−;Dot1Lfl/fl mice, B cell cellularity decreased 3.5-fold while T cell numbers remained unaffected, resulting in a 2.0-fold decreased overall cellularity (Fig. 2a-b). Among the various peripheral B cell subsets, the strongest reduction was found in marginal zone B cells and GC B cells to the extent that they were nearly absent (Fig. 2c-i and Supplementary Fig. S1b). The reduction of GC B cells was of particular interest given the highest levels of Dot1L mRNA expression in this subset (Fig. 1a and 2i), and strongly suggested that the formation of germinal centers critically depends on DOT1L. Indeed, in situ histological analyses also revealed the absence of GCs in the spleen of Dot1L-KO mice (Fig. 2j and 2k). Similarly, lack of DOT1L resulted in a marked reduction of GC B cells in Peyer’s patches (Supplementary Fig. S2).
Dot1L deletion impairs proliferation in vitro
Following B-cell priming, B cells undergo class switch recombination (CSR) and form GCs. CSR is an important feature of humoral immunity and is dependent on B cell activation and initiation of proliferation. Given the critical role of DOT1L in GC B cell differentiation, we here examined the CSR potential and proliferative capacity of naïve splenic B cells stimulated in vitro with LPS alone or in combination with IL-4, to induce switching to IgG3 or IgG1, respectively. Compared to Dot1L-proficient B cells, the lack of Dot1L was associated with a reduced frequency of class-switched IgG3 and IgG1 cells (Fig. 3a-b, and Supplementary Fig. S3a-b). Similar observations were made using the T-cell dependent mimetic anti-CD40 and IL-4 as stimuli (Fig. 3c and Supplementary Fig. S3c). Mechanistically, this reduction in CSR might relate to impaired proliferation, since proliferation is a prerequisite for CSR 42 (e.g. see WT in Fig. 3d-e), or a defect in the CSR machinery. We found that the proliferative response of Dot1L-KO B cells was strongly impaired upon CD40+IL-4 in-vitro stimulation, as revealed by tracing the dilution of a fluorescent label (Fig. 3d). The reduced CSR potential is most likely caused by the impaired proliferation as the frequency of switched cells among equally-proliferating populations was not different between KO and WT (Fig. 3e). Furthermore, RNA-Seq analysis of KO and WT B cells activated with LPS and IL-4 argued against a potential failure of CSR in Dot1L-KO B cells, since components of the CSR machinery were expressed in KO cells (Supplementary Table S1). Finally, in-vitro activation of naïve B cells with LPS and IL-4 led to a higher proportion of dead cells (Zombie NIR positive) in Dot1L-KO compared to WT. In addition, the viable (Zombie NIR negative) subset in activated KO B cells consistently showed higher levels of active caspase 3, a marker of apoptosis. These insights indicated that the viability of Dot1L-deficient B cells is severely compromised (Supplementary Fig. S3d-f). The virtual absence of GC B cells, the impaired proliferative response, and the increased cell death of Dot1L-deficient B cells implicated a severe defect of Mb1-Cre+/−;Dot1Lfl/fl mice in establishing effective humoral immunity.
Dot1L-deficient B cells fail to mount efficient immune responses in vivo and acquire plasma cell features in vitro
In unchallenged Dot1L-KO mice, serum IgM titers appeared normal but IgG1 titers were decreased, while IgG2b, IgG3, and IgA titers were not significantly decreased (Supplementary Fig. S4a-e). To determine the immune responsiveness of Dot1L-deficient B cells, Mb1-Cre+/−;Dot1Lfl/fl and Mb1-Cre+/−;Dot1Lwt/wt mice were challenged with an acute lymphocytic choriomeningitis virus (LCMV) infection. During the LCMV infection, Dot1L-deficient B cells failed to establish GC B cells and to generate plasma cells (Fig. 4a-b). In accordance with this, these mice also failed to mount normal IgM serum titers against LCMV (Fig. 4c). The failure to establish GCs in response to LCMV is also in line with the very low LCMV-specific IgG serum titers (Fig. 4c). The inability of Mb1-Cre+/−;Dot1Lfl/fl mice to mount efficient antibody responses to T-cell dependent antigen was confirmed using 4-hydroxy-3-nitrophenylacetyl conjugated to chicken gamma globulin (NP-CGG) in alum as immunogen (Fig. 4d). Together, these data suggest that DOT1L is essential for establishing a normal humoral immune response. Upon in-vitro activation of naïve Dot1L-KO B cells with LPS and IL-4, a significantly increased frequency of cells expressing the plasma-cell marker CD138 43, 44 was observed (Supplementary Fig. S4f). This observation was supported by the increased proportion of cells expressing the pan-plasma cell transcription factor BLIMP1 45 (Supplementary Fig. S4g) in Dot1L-KO versus WT. However, these cells failed to downregulate B220 (Supplementary Fig. S4h). Downregulation of B220 is considered as a hallmark of post-mitotic plasma cells 46. In addition, in-vitro activated Dot1L-KO B cells failed to differentiate into CD19-high activated B cell blasts or CD19-negative plasma cells, but were stuck at a transitional state, expressing CD19 at intermediate levels (Supplementary Fig. S4i). Together, these phenotypes upon in-vitro activation suggest that in the absence of DOT1L-mediated H3K79 methylation, naïve B cells skip the GC stage and prematurely start to gain some plasma cell features but do not accomplish complete differentiation program.
DOT1L supports a pro-proliferative, MYC-high GC stage and prohibits premature differentiation towards plasma cells in vitro
To unravel the underlying molecular mechanisms that prohibit Dot1L-KO GC B cell differentiation and stimulate partial differentiation towards plasma cells we performed RNA-Seq analyses of in vitro activated (LPS and IL-4) B cells under Dot1L-proficient and -deficient conditions. Among the differentially-expressed genes, the genes encoding the pro-GC transcription factor BACH2 and the pro-proliferative transcription factor MYC25, 47, 48 were H3K79me2 methylated in WT cells and transcriptionally downregulated in activated DOT1L-deficient B cells (Supplementary Fig. S5a-d). In agreement with this, Prdm1, repressed by BACH2 (and H3K79me2-methylated and expressed in activated B cells) and encoding the pan-plasma cell transcription factor BLIMP145, 49, was found upregulated (Fig. 5b and Supplementary. Figs. S5c-d). These transcriptional changes are in line with the observed absence of GC B cells and increased formation of cells with plasma cell features in KO cells. In addition, analysis of a published plasma-cell gene signature 34, revealed that the transcriptome of activated Dot1L-deficient B cells was indeed strongly enriched for plasma-cell associated transcripts (Fig. 5c). Simultaneously, MYC-target gene transcripts were strongly reduced (Fig. 5d). Together, these observations indicate that DOT1L-mediated H3K79 methylation licenses a transient entrance into a pro-proliferative, MYC-high GC stage and is required to prevent premature differentiation of activated B cells towards non-proliferative terminally differentiated plasma cells. Transcriptomic data from ex-vivo isolated naïve Dot1L-deficient B cells also revealed enrichment of some plasma-cell associated genes, suggesting that antigen-inexperienced B cells are already prematurely differentiated in the absence of DOT1L (Supplementary Fig. S5e). However, upon activation, expression of Irf4, a factor essential for plasma cell differentiation50, was not differential between WT and KO. This dichotomy, amongst other factors, likely contributes to the failure to adopt an identity of terminally differentiated plasma cells (Supplementary Fig. S5f). Together, our results indicate that DOT1L modulates the expression of several key transcriptional regulators essential in controlling stepwise B cell differentiation.
DOT1L-mediated H3K79 methylation is associated with gene activity in B cells
To link the phenotypes of loss of DOT1L to its role as an epigenetic regulator in B cells, we generated genome-wide maps of DOT1L-mediated H3K79me2 in naïve and activated WT B cells by ChIP-Seq. We analyzed the H3K79me2 mark because it is known to mark the region downstream of the transcriptional start site of transcribed genes and positively correlate with gene activity9, 10, 51, 52. While H3K79me1 shows the same trends, it has a broader distribution, and H3K79me3 is detectable only at limited levels9, 19, 52. Here we analyzed how the gene-expression changes in Dot1L-KO versus WT B cells related to genes being marked by H3K79me2 in WT cells.
Both in naïve and activated B cells more than 83 percent of the differentially expressed genes was found upregulated in the absence of DOT1L; only a small subset was downregulated (Fig. 5a and Supplementary Fig. S5g). The upregulation was biased towards more lowly expressed genes. The observed upregulation of genes in Dot1L-KO B cells was unexpected given the fact that H3K79me2 generally correlates with transcriptional activity9, 11, 17, 51, 53, 54, 55, 56. However, repressive functions of DOT1L have been proposed as well57, 58, 59, 60. Comparing H3K79me2 ChIP values in WT cells with the gene expression changes caused by loss of DOT1L revealed that the genes upregulated in Dot1L-KO B cells were mostly hypomethylated in WT cells, indicating that they are likely indirectly affected by the loss of DOT1L (Fig. 6a and 6b). In contrast, genes downregulated in Dot1L-KO B cells were generally highly expressed and H3K79 methylated in WT B cells, indicating that this gene set harbors the genes directly dependent on DOT1L. These findings show that DOT1L-mediated H3K79me2 is a mark of many active genes in B cells, but suggest that only a small fraction of these genes requires H3K79me2 for maintenance of gene expression, since only a subset of the active genes was downregulated in Dot1L KO.
DOT1L supports repression of PRC2 target genes
The large number of genes found upregulated in Dot1L-KO B cells indicated that DOT1L positively regulates the expression of a transcriptional repressor whose target genes are derepressed in absence of DOT1L. To identify such candidate repressors, we investigated the relatively small fraction of genes downregulated in naïve and activated Dot1L-KO B cells. Unbiased identification of upstream transcriptional regulators by Ingenuity Pathway analyses (IPA) pointed towards potential regulators that were differentially upregulated in WT B cells (Tables 1 and 2). To further narrow down the list, we filtered for genes that are (i) H3K79-dimethylated by DOT1L, (ii) encode transcriptional repressors, and (iii) play a role in B cell differentiation/proliferation and GC formation. This led to the identification of the histone H3K27 methyltransferase EZH2 as a candidate factor (Table 1 and 2). We verified that Ezh2 expression was reduced in Dot1L-KO B cells (Fig. 6c) and that the gene is H3K79-dimethylated in WT cells (Fig. 6d), indicating that the expression of Ezh2 is directly promoted by DOT1L activity (Fig. 6c and 6d). Further supporting this notion, the expression of Ezh2 and Dot1L was found co-regulated in B cell subsets (Fig. 6e).
We next investigated the physiological relevance of the connection between DOT1L and EZH2. First, Ezh2-KO and Dot1L-KO B cells have overlapping phenotypes31, 61, 62, 63, 64, 85. Second, we took advantage of publicly available RNA-Seq data62 from Ezh2-KO plasma cells to identify genes that require EZH2 for their repression (Supplementary Fig. S6a). Using this as a signature of EZH2-dependent genes, we found that many of the genes de-repressed in Ezh2-KO cells were also found de-repressed in activated Dot1L-KO B cells (Supplementary Fig. S6b). Many of these genes were found de-repressed also in naïve Dot1L-KO B cells (Supplementary Fig. S6b). As an independent validation, we evaluated the expression of a known PRC2-target gene Cdkn1a (p21)63, 65, 66, and found that it was upregulated in activated Dot1L-KO B cells (Fig. 6c). Third, we analyzed the level of H3K27me3 and H3K79me2 in the set of genes that was de-repressed in Dot1L KO using our H3K79me2 ChIP-Seq data and publicly available H3K27me3 ChIP-Seq data from naïve B cells67. The analysis revealed that this gene set was enriched for H3K27me3 in WT cells compared to expression-matched non-differentially expressed genes (Fig. 6f). Together, these findings suggest that in B cells, DOT1L supports the repression of PRC2 target genes, thus uncovering a previously unknown connection between two conserved histone methyltransferases associated with activation and repression, respectively. Together, our findings place H3K79 methylation by DOT1L at the heart of maintaining epigenetic identity of B cells, by orchestrating the activity of central transcriptional and epigenetic regulators such as BACH2, MYC, EZH2, and their target genes.
DISCUSSION
Given the critical contribution of B cells to the immune system, it is important to understand the molecular mechanisms underlying the epigenetic programming during their differentiation. Taking advantage of a B-cell specific murine knock-out model, we observed that the H3K79 methyltransferase DOT1L has a central role in B cell physiology. Among mature B cells, GC B cells express the highest levels of Dot1L and they were strongly reduced in Dot1L-KO mice. Indeed, GC B cell differentiation was found to be critically dependent on DOT1L. Upon in vitro activation, Dot1L-KO B cells failed to proliferate and after an in vivo immune challenge these cells failed to differentiate into GC B cells, and establish an effective immune response. In addition, we observed accelerated partial plasma cell differentiation in Dot1L-KO B cells in vitro. RNA-Seq data generated from naïve and in-vitro activated Dot1L-KO and WT B cells demonstrated a strong enrichment of genes associated with plasma cell differentiation among the genes up-regulated in Dot1L KO. However, in-vitro activated B cells failed to downregulate B220, indicating an incomplete differentiation of Dot1L-KO plasma cells46, which is in agreement with the failure to upregulate Irf4, a factor essential for plasma cell differentiation50. Our results also revealed that DOT1L supports MYC activity, which B cells depend on to differentiate effectively into pro-proliferative GC B cells25. Recent studies have shown that inhibition of DOT1L also leads to reduced Myc expression in multiple myeloma68 and in MYC-driven B cell lymphoma69, indicating that the connection between DOT1L and MYC has broad implications in B cell physiology. Furthermore, in neuroblastoma H3K79me2 methylation has been shown to be a strict prerequisite for MYC-induced transcriptional activation, indicating a mutual interaction between DOT1L and MYC70. Interestingly, this novel interaction has also been reported recently in colorectal cancer71. In addition to the crucial role in GC formation we also identify DOT1L as a critical factor in maintaining MZ B cells. Further exploring the strong reduction of MZ B cells upon loss of Dot1L should provide additional insights regarding the contribution of DOT1L in orchestrating normal B cell physiology.
In addition to supporting MYC and BACH2 activity, our findings also suggest that DOT1L supports the repression of target genes of PRC2. The observation that Ezh2 is normally H3K79-dimethylated and downregulated in Dot1L-KO B cells, and that Dot1L and Ezh2 are co-regulated in B cells indicates that DOT1L promotes repression of PRC2 targets by maintaining expression of Ezh2. A direct stimulatory effect of H3K79me on H3K27me3 synthesis is not likely to be involved since the modifications occur in distinct locations in the genome and are associated with opposite transcriptional states. Finally, besides MYC and PRC2, additional factors controlled by DOT1L may impact differentiation of B cells. For example, it will be interesting to determine the role of other candidate transcriptional regulators regulated by DOT1L (Tables 1-2). The number of transcriptional regulators involved in B cell development affected by DOT1L ablation implies the existence of a complex regulatory network that warrants further investigations to untangle.
Understanding the critical role of DOT1L in normal B cell differentiation is also relevant for disease. Considering the requirement for DOT1L in supporting humoral immune responses that we show here, targeting DOT1L may offer an opportunity for immune suppression. Given the strong dependency of GC B cells on DOT1L and the role of DOT1L in controlling the activity of EZH2 together with the oncogenic factor MYC, DOT1L inhibition may also offer a novel therapeutic angle in the treatment of diffuse large B cell lymphoma of the GCB type. In summary, in B cells, DOT1L has a central role in guiding dynamic epigenetic states controlling differentiation and ensuring functional immune responses, with a potential for clinical utility.
Methods
Mice
Mb1-Cre+/−;Dot1Lfl/fl mice were derived by crossing the Dot1Ltm1a(KOMP)Wtsi line - generated by the Wellcome Trust Sanger Institute (WTSI) and obtained from the KOMP Repository (www.komp.org) - with the MB1-Cre strain kindly provided by M. Reth72. Mice from this newly created Mb1-Cre+/−;Dot1L strain were maintained under specific pathogen free (SPF) conditions at the animal laboratory facility of the Netherlands Cancer Institute (NKI; Amsterdam, Netherlands). Mice used for experiments were between 6-8 weeks old and of both genders. All experiments were approved by the Animal Ethics Committee of the NKI and performed in accordance with the Dutch Experiments on Animals Act and the Council of Europe.
Genotyping PCR
Mice were genotyped for Dot1L using the forward primer (Dot1L: FWD, GCAAGCCTACAGCCTTCATC) and reverse primer 1 (Dot1L:REV1, CACCGGATAGTCTCAATAATCTCA) to identify WT allele; Dot1Lwt (642 Bps) while the floxed allele; Dot1Lfl (1017 Bps) was identified by using Dot1L: FWD and reverse primer 2 (Dot1L:REV2, GAACCACAGGATGCTTCAG). WT allele (418 Bps) for Mb1 was detected by using forward primer (Mb1-FWD1: CTGCGGGTAGAAGGGGGTC) and reverse primer (Mb1-REV1: CCTTGCGAGGTCAGGGAGCC) while Cre (219 Bps) was detected by using forward primer (Mb1-FWD2: GTGCAAGCTGAACAACAGGA) and reverse primer (Mb1-REV2: AAGGAGAATGTGGATGCTGG).
Flow cytometry
Single cell suspensions were made from bone marrow, spleen and Peyer’s patches. Bone marrow, spleen and blood samples were subjected to erythrocyte lysis. Distinct cellular populations were identified using combination of fluor-conjugated antibodies against surface markers (Table 3). Cells were stained with fluorescently labeled antibodies (Table 4). For intracellular staining cells were fixed and permeabilized using the Transcription Factor Buffer kit (Becton Dickinson, BD). Antibodies for intracellular staining were diluted in Perm/Wash buffer except for cleaved caspase-3. For H3K79me2 staining, cells were first stained with surface markers and fixed and permeabilized as described before. After fixation and permeabilization cells were washed with Perm/Wash containing 0.25% SDS. H3K79me2 specific antibody (Millipore) was diluted 1:200 into Perm/Wash + 0.25% SDS and cells were incubated for 30 min. Cells were washed with Perm/Wash and incubated with the secondary antibodies Donkey anti-Rabbit AF555 (Thermo Scientific) or Goat-anti-Rabbit AF488 (Invitrogen) 1:1000 in Perm/Wash. For cleaved caspase-3 staining the cells were first stained with surface markers and then fixed with 4% formaldehyde for 15 minutes at room temperature. After washing with 0.25% tween buffer the cells were permeabilized with 0.25% tween buffer for 15 minutes at room temperature. Following permeabilization the cells were stained with cleaved caspase-3 antibody as 1:50 diluted in 0.25% tween buffer for 45 minutes at room temperature under dark condition. Flow cytometry was performed using the LSR Fortessa (BD Biosciences) and data were analyzed with FlowJo software (Tree Star Inc.). Histograms were smoothed.
Immunization
Adult mice were inoculated intravenously with sub-lethal dose 2×105 PFU (Plaque forming units) of lymphocytic choriomeningitis virus strain Armstrong. Serum was collected prior to immunization and 14 days post immune challenge. For NP-CGG immunization mice were injected intraperitoneally with 100 μg of alumprecipitated NP-CGG [(4-hydroxy-3-nitrophenyl) acetyl coupled to chicken γ–globulin, BIOSEARCH™ TECHNOLOGIES] in a 200 μl of NP-CGG alum solution. To determine the serum titers of NP-specific IgM and IgG1, mice were bled from the tail vein on day 0,7,14,21,28, and 35.
Class switch recombination and Proliferation
Single cells suspensions were prepared from the spleen of 6-8-week-old mice. Following erythrocyte lysis, naïve splenic B cells were enriched by the depletion of CD43 expressing cell using biotinylated anti-CD43 antibody (Clone S7, BD Biosciences), BD IMag Streptavidin Particles Plus and the IMag® system (BD Biosciences), as described by the manufacturer. To measure their proliferative capacity, naïve B cells were labeled for 10 min at 37°C with 5 μM Cell Trace Violet (CTV, Life Technologies, Invitrogen™) in IMDM medium containing 2% FCS,100 mM pen/strep and 100 mM β-mercaptoethanol. After washing, cells were cultured in complete IMDM medium (IMDM supplemented with 8% FCS, 100 mM pen/strep and 100 mM β-mercaptoethanol) at a density of 105 cells/well in 24 well plates. CSR to IgG3 and IgG1 was induced in T cell independent manner by exposure to 5 μg/ml of Lipopolysaccharide (Escherichia Coli LPS, 055:B5, Sigma) or LPS+rIL-4. rIL4 was used at a concentration of 10 ng/ml. Cells were exposed to anti-CD40 (1ug/ml, BD Clone HM40-3) and rIL-4 (10 ng/ml) to induce IgG1 switching in a T cell dependent manner. Four days later, the cells were harvested and stained with CD19, IgM, and IgG3 (LPS cultures) or IgG1 (LPS/rIL4 cultures or anti-CD40/rIL-4) to determine CSR frequency along with CTV dilution as an indicator of cell multiplication.
ELISA
LCMV-specific serum IgM and IgG levels were measured by ELISA. In short, Nunc-Immuno Maxisorp plates (Fisher Scientific) were coated overnight at 4°C with virus in bicarbonate buffer. Plates were subsequently incubated for 1h with blocking buffer (PBS/5% milk powder (Fluka Biochemika)). Sera from mice were diluted in PBS/1% milk powder and incubated for 1h at 37°C. Next, HRP-conjugated IgG and IgM antibodies (Southern Biotech) were diluted 1:4000 in PBS/1% milk powder and incubated 1h at 37°C. Plates were developed with TMB substrate (Sigma Aldrich), and the color reaction was stopped by the addition of 1 M H2SO4. Optical density was read at 450 nm (OD450) using a Microplate reader (Model 680, Bio-Rad). To quantify NP-specific serum antibodies, plates were coated with 2 μg/ml NP30-BSA. Serum was added at a starting dilution of 1:100 followed by 3-fold serial dilutions and incubated at room temperature for 2 hours. Bound serum antibodies were detected with polyclonal biotinylated goat anti-mouse IgM or anti-IgG1 (Southern Biotech), streptavidin-alkaline phosphatase conjugate (Roche) and chromogenic substrate 4-nitrophenyl phosphate (Sigma). Purified monoclonal antibodies (B1-8μ and 18-1-16y1) were used as standards for quantification.
Lectin histochemistry
Lymphoid tissues such as spleens and lymph nodes were fixed in EAF (ethanol, acetic acid, formaldehyde, saline) for 24 hours and subsequently embedded in paraffin. 4 um-thick sections were stained with the lectin Peanut Agglutinin (PNA, Vector Laboratories) at 1:1500 dilution to reveal germinal centers. The sections were counterstained with hematoxyline.
Sorting and in vitro activation for RNA and ChIP-Seq
For RNA sequencing, cells were first depleted for CD43+ cells and either subjected to MACS sorting for CD19+ cells as naïve B cells or activated for two days with LPS and IL-4. Following activation, the cells were enriched for CD19+ by MACS according to the manufacturer instructions. For ChIP-Seq, CD43-cells were either FACS sorted for CD19+ as naïve B cell pool or activated for three days with LPS and IL-4 and subjected to FACS sorting for CD19+ expression.
RNA-Seq sample preparation
MACS sorted CD19+ cells were resuspended in Trizol (Ambion Life Technologies) and total RNA was extracted according to the manufacturer’s protocol. Quality and quantity of the total RNA was assessed by the 2100 Bioanalyzer using a Nano chip (Agilent). Only RNA samples having an RNA Integrity Number (RIN) > 8 were subjected to library generation.
RNA-Seq library preparation
Strand-specific cDNA libraries were generated using the TruSeq Stranded mRNA sample preparation kit (Illumina) according to the manufacturer’s protocol. The libraries were analyzed for size and quantity of cDNAs on a 2100 Bioanalyzer using a DNA 7500 chip (Agilent), diluted and pooled in multiplex sequencing pools. The libraries were sequenced as 65 base single reads on a HiSeq2500 (Illumina).
RNA-Seq preprocessing
Strand-specific RNA reads (11-33 million reads per sample), 65 bp single-end, were aligned against the mouse reference genome (Ensembl build 38) using Tophat (version 2.1, bowtie version 1.1). Tophat was supplied with a Gene Transfer File (GTF, Ensembl version 77) and was supplied with the following parameters: ‘--prefilter-multihits -no-coverage-search -bowtie1 -library-type fr-firststrand’. In order to count the number of reads per gene, a custom script which is based on the same ideas as HTSeq-count has been used. A list of the total number of uniquely mapped reads for each gene that is present in the provided Gene Transfer Format (GTF) file was generated. Genes that have no expression across all samples within the dataset were removed. Analysis was restricted to genes that have least 2 counts per million (CPM) value in all samples in specific contrasts, to exclude very low abundance genes. Differential expression analysis was performed in R language (version 3.5.1) on only relevant samples using edgeR package and default arguments with the design set to either Dot1LKO status, Ezh2KO status or cell type. Genes were considered to be differentially expressed when the False discovery rate (FDR) was below 0.05 after the Benjamini-Hochberg multiple testing correction. Sets of differentially expressed genes in indicated conditions were called ‘gene signatures. MA plots were generated after differential expression analysis carried by edgeR package73, 74. Read counts were corrected for gene length based on the longest transcript of the gene followed by normalization for the library size and shown as transcript per million (TPM). Counts are shown as counts per million after trimmed mean of M-values (TMM) normalization using the edgeR R package. For analyses where we performed expression matching, we chose genes with an absolute log2 fold changes less than 0.1 and false discovery rate corrected p-values above 0.05 that were closest in mean expression to each of the genes being matched without replacement. The RNA-Seq datasets reported in this article have been deposited at the National Center for Biotechnology Information under the accession number GSE138909.
Ingenuity pathway analysis (IPA)
Lists of differentially expressed genes (FDR < 0.05) between WT and KO B cells both from naïve and activated conditions were submitted to IPA using default settings to identify potential upstream regulators.
Gene set enrichment analysis (GSEA)
GSEA was carried out after differential expression analysis. Gene set enrichment was shown as barcode plot where the genes were ranked according to the log2 fold change between the compared conditions. Statistical significance for the enrichment of gene set was determined by Fast approximation to mroast (FRY) gene set test 75 from limma package and two-sided directional p value less than 0.05 was considered significant.
Functional enrichment analysis
Functional enrichment analysis was carried by ‘g:GOST’ tool with default arguments from ‘g:Profiler2’ package and performed in R language (version 3.5.1).
ChIP-Seq sample preparation
Sorted cells were centrifuged at 500 rcf. The pellet was resuspended in IMDM containing 2% FCS and formaldehyde (Sigma) was added to a final concentration of 1%. After 10 min incubation at RT glycine (final concentration 125 mM) was added and incubated for 5 min. Cells were washed twice with ice-cold PBS containing Complete, EDTA free, protein inhibitor cocktail (PIC) (Roche). Cross-linked cell pellets were stored at −80°C. Pellets were resuspended in cold Nuclei lysis buffer (50mM Tris-HCl pH 8.0, 10mM EDTA pH8.0, 1%SDS) + PIC and incubated for at least 10 min. Cells were sonicated with PICO to an average length of 200-500bp using 30 s on/ 30 s off for 3 min. After centrifugation at high speed debris was removed and 9x volume of ChIP dilution buffer (50mM Tris-HCl pH8, 0.167M NaCl, 1.1% Triton X-100, 0.11% sodium deoxycholate) + PIC and 5x volume of RIPA-150 (50mM Tris-HCl pH8, 0.15M NaCl, 1 mM EDTA pH8, 0.1% SDS, 1% Triton X-100, 0.1% sodium deoxycholate) + PIC was added. Shearing efficiency was confirmed by reverse crosslinking the chromatin and checking the size on agarose gel. Chromatin was pre-cleared by adding ProteinG Dynabeads (Life Technologies) and rotation for 1 hour at 4°C. After the beads were removed 2μl H3K79me1, 2 μl H3K79me2 (NL59, Merck Millipore) and 1 μl H3K4me3 (ab8580, Abcam) were added and incubated overnight at 4°C. ProteinG Dynabeads were added to the IP and incubated for 3 hours at 4°C. Beads with bound immune complexes were subsequently washed with RIPA-150, 2 times RIPA-500 (50mM Tris-HCl pH8, 0.5M NaCl, 1mM EDTA pH8, 0.1% SDS, 1% Triton X-100, 0.1% sodium deoxycholate), 2 times RIPA-LiCl (50mM Tris-HCl pH8, 1mM EDTA pH8, 1% Nonidet P-40, 0.7% sodium deoxycholate, 0.5M LiCl2) and TE. Beads were resuspended in 150 μl Direct elution buffer (10mM Tris-HCl pH8, 0.3M NaCl, 5mM EDTA pH8, 0.5%SDS) and incubated overnight at 65°C and input samples were included. Supernatant was transferred to a new tube and 1 μl RNase A (Sigma) and 3 μl ProtK (Sigma) were added per sample and incubated at 55°C for 1 hour. DNA was purified using Qiagen purification columns.
ChIP-Seq Library preparation
Library preparation was done using KAPA LTP Library preparation kit using the manufacturer’s protocol with slight modifications. Briefly, after end-repair and A-tailing adaptor were ligated followed by Solid Phase Reversible Immobilization (SPRI) clean-up. Libraries were amplified by PCR and fragments between 250-450 bp were selected using AMPure XP beads (Beckman Coulter). The libraries were analyzed for size and quantity of DNAs on a 2100 Bioanalyzer using a High Sensitivity DNA kit (Agilent), diluted and pooled in multiplex sequencing pools. The libraries were sequenced as 65 base single reads on a HiSeq2500 (Illumina).
ChIP-Seq preprocessing
ChIP-Seq samples were mapped to mm10 (Ensembl GRCm38) using BWA-MEM with the option ‘-M’. Duplicate reads were removed using MarkDuplicates from the Picard toolset with ‘VALIDATION_STRINGENCY=LENIENT’ and ‘REMOVE_DUPLICATES=true’ as arguments. Bigwig tracks were generated from these bam files by using bamCoverage from deepTools using the following arguments: ‘-of bigwig -binsize 25 -normalizeUsing RPGC - ignoreForNormalization chrM -effectiveGenomeSize 2652783500’. Bigwig files were loaded into R using the ‘import.bw()’ function from the rtracklayer R package for visualization of heatmaps and genomic tracks. TSSs for heatmaps were taken from Ensembl GRCm38.77 gene models by taking the first base pair of the 5’ UTR of transcripts. When such annotation was missing, the most 5’ position of the first exon was taken. The ChIP-Seq datasets reported in this article have been deposited at the National Center for Biotechnology Information under the accession number GSE138906.
Statistics
Statistical analyses were performed using Prism 7 (GraphPad). Data are presented as mean ±SD except for Fig. 4D where it is presented as mean± SEM. The unpaired Student’s t-test with two-tailed distributions was used to calculate the p-value. A p-value < 0.05 was considered statistically significant.
Funding
This work would not have been possible without the generous support kindly provided by the Netherlands Organization for Scientific Research (NWO-VICI-016.130.627 to FvL; ZonMW Top 91213018 to HJ; ZonMW Top91218022 to FvL and HJ) and the Dutch Cancer Society (NKI 2014-7232 to FvL and HJ). The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Author contributions
Conception and design, M.A.A, M.F.A., E.M.K-M., F.v.L., and H.J.
Acquisition of data, M.A.A., M.F.A., E.M.K-M., M.C., I.N.P., T.v.W., J-Y.S., and F.I.M.
Analysis and interpretation of data, M.A.A, M.F.A., E.M.K-M., R.A., E.d.W., K.R., F.v.L., and H.J.
Bioinformatics Analysis, M.A.A, T. v.d. B., M.F.A, E.d.W., and I.d.R.
Writing of the manuscript, M.A.A., M.F.A., E.M.K-M., F.v.L. and H.J.
Acknowledgements
We like to thank the core facilities of the NKI-AVL for their superb biotechnical and molecular help. We highly appreciate the support from Michael Reth in providing his Mb1-Cre mouse model system.
Footnotes
Lead Contact: Heinz Jacobs
Fixed text issues, added additional analyses and experiments.