EBNA2-EBF1 complexes promote MYC expression and metabolic processes driving S-phase progression of Epstein-Barr virus-infected B cells.

Epstein-Barr virus (EBV) is a human tumor virus which preferentially infects resting human B cells. Upon infection in vitro, EBV activates and immortalizes these cells. The viral latent protein EBV nuclear antigen 2 (EBNA2) is essential for B cell activation and immortalization; it targets and binds the cellular and ubiquitously expressed DNA-binding protein CBF1, thereby transactivating a plethora of viral and cellular genes. In addition, EBNA2 uses its N-terminal dimerization (END) domain to bind early B cell factor 1 (EBF1), a pioneer transcription factor specifying the B cell lineage. We found that EBNA2 exploits EBF1 to support key metabolic processes and to foster cell cycle progression of infected B cells in their first cell cycles upon activation. The α1-helix within the END domain was found to promote EBF1 binding. EBV mutants lacking the α1-helix in EBNA2 can infect and activate B cells efficiently, but activated cells fail to complete the early S phase of their initial cell cycle. Expression of MYC, target genes of MYC and E2F, as well as multiple metabolic processes linked to cell cycle progression are impaired in EBVΔα1-infected B cells. Our findings indicate that EBF1 controls B cell activation via EBNA2 and, thus, has a critical role in regulating the cell cycle of EBV-infected B cells. This is a function of EBF1 going beyond its well-known contribution to B cell lineage specification

PLK1-dependent phosphorylation restrains EBNA2 activity and lymphomagenesis in EBV-infected mice.

While Epstein-Barr virus (EBV) establishes a life-long latent infection in apparently healthy human immunocompetent hosts, immunodeficient individuals are at particular risk to develop lymphoproliferative B-cell malignancies caused by EBV. A key EBV protein is the transcription factor EBV nuclear antigen 2 (EBNA2), which initiates B-cell proliferation. Here, we combine biochemical, cellular, and in vivo experiments demonstrating that the mitotic polo-like kinase 1 (PLK1) binds to EBNA2, phosphorylates its transactivation domain, and thereby inhibits its biological activity. EBNA2 mutants that impair PLK1 binding or prevent EBNA2 phosphorylation are gain-of-function mutants. They exhibit enhanced transactivation capacities, accelerate the proliferation of infected B cells, and promote the development of monoclonal B-cell lymphomas in infected mice. Thus, PLK1 coordinates the activity of EBNA2 to attenuate the risk of tumor incidences in favor of the establishment of latency in the infected but healthy host

EBF1 binds to EBNA2 and promotes the assembly of EBNA2 chromatin complexes in B cells.

Epstein-Barr virus (EBV) infection converts resting human B cells into permanently proliferating lymphoblastoid cell lines (LCLs). The Epstein-Barr virus nuclear antigen 2 (EBNA2) plays a key role in this process. It preferentially binds to B cell enhancers and establishes a specific viral and cellular gene expression program in LCLs. The cellular DNA binding factor CBF1/CSL serves as a sequence specific chromatin anchor for EBNA2. The ubiquitous expression of this highly conserved protein raises the question whether additional cellular factors might determine EBNA2 chromatin binding selectively in B cells. Here we used CBF1 deficient B cells to identify cellular genes up or downregulated by EBNA2 as well as CBF1 independent EBNA2 chromatin binding sites. Apparently, CBF1 independent EBNA2 target genes and chromatin binding sites can be identified but are less frequent than CBF1 dependent EBNA2 functions. CBF1 independent EBNA2 binding sites are highly enriched for EBF1 binding motifs. We show that EBNA2 binds to EBF1 via its N-terminal domain. CBF1 proficient and deficient B cells require EBF1 to bind to CBF1 independent binding sites. Our results identify EBF1 as a co-factor of EBNA2 which conveys B cell specificity to EBNA2

Comparative transcript profiling of EBNA2 target gene expression in CBF1 proficient and deficient DG75 cells.

<p>DG75 cells expressing ER/EBNA2 were cultivated in estrogen supplemented medium for 24 h or were left untreated. Total cellular RNA was isolated and submitted to gene expression analysis using the Human Gene 2.0 ST array. All probe sets represent single transcripts (trxs). For each condition, 3 biological replicates were examined. Each vertical column represents the results obtained after hybridizing a single microarray. Horizontal rows represent data obtained for a particular probe set across all cell lines and conditions adjusted to a scale ranging from -2.0 to + 2.0. The relative high, medium and low expression values are represented by red, white and blue color, respectively. Vertical columns are ranked according to fold changes from highest induction levels on top to highest repression levels at the bottom. (A) Expression levels of 136 transcripts which change expression levels at least 4-fold (p ≤ 0.001) in response to EBNA2 in CBF1 proficient DG75 (DG75^ER/EBNA2 CBF1 wt) cells are displayed. The transcript cluster ID and the assigned genes/transcripts, including non-coding RNAs, are annotated. (B) 21 transcripts regulated at least 4-fold (p ≤ 0.001) in CBF1 deficient DG75 (DG75^ER/EBNA2 CBF1 ko). (C) Boxplots depicting the fold change distribution of EBNA2 induced and repressed transcripts for the subset of target genes changed at least 2-fold (p ≤ 0.05) in CBF1 wt and ko cells, respectively. EBNA2 induced (D) and repressed (E) transcripts are shown to illustrate the dynamic range of each system. Boxplot whiskers extend to 1.5x interquartile range. Dotted lines mark the 2-fold change chosen as cut-off. (F) Expression levels of EBNA2 (prior to and after estrogen treatment) and CBF1 proteins were monitored by Western blot analysis. Equal amounts of total protein lysates were applied and GAPDH served as an internal loading control. One representative experiment (n = 3) is shown.</p

EBNA2 can access more than 15% of its chromatin binding sites in CBF1 deficient DG75 B cells.

<p>(A) Intersection of EBNA2 binding sites identified in CBF1 proficient or deficient cells 24 h post doxycycline induction. 1,546 peaks that were identified in CBF1 proficient but not in CBF1 deficient cells were defined as "CBF1 dependent" EBNA2 peaks. 243 EBNA2 peaks identified in CBF1 deficient and proficient DG75 cells were defined as "CBF1 independent". (B-E) Comparison of EBNA2 ChIP-seq signal distributions at CBF1 independent or dependent peaks. (B) Anchor and (C) scatter plots (mean + 95% CI) depicting ChIP-seq signal distributions at EBNA2 peak subsets. Regions flanking the peak center for 2 kb in each direction were analyzed (Data underlying panel B). Absolute means and SEMs are indicated below. (D) Anchor and (E) scatter plots (mean + 95% CI) as shown in B and C but depicting EBNA2 ChIP-seq signal intensities for the two different subsets of EBNA2 peaks as defined in A. Statistical significance for differences of all means were assessed applying unpaired two-tailed t-test for log values with Welch’s correction (**** p < 0.0001); absolute means and SEMs are indicated below. (F) List of EBNA2 mean ChIP-seq signal intensities at CBF1 independent and dependent peaks.</p

EBNA2 requires EBF1 to bind to its CBF1 independent binding sites.

<p>DG75^doxHA-E2 CBF1 wt or CBF1 ko B cells were transfected with a mixture of scrambled non-targeting siRNAs (siCNTRL) or EBF1 specific siRNAs (siEBF1). 8 h post transfection, EBNA2 transcription was induced. 24 h post transfection, cells were harvested and analyzed by immunoblots (<a href="http://www.plospathogens.org/article/info:doi/10.1371/journal.ppat.1006664#ppat.1006664.s009" target="_blank">S9 Fig</a>) and ChIP-qPCR. In the upper panel, EBNA2 (E2) binding signal and peak tracks as obtained in DG75^doxHA-E2 (DG75) as well as EBNA2, CBF1 and EBF1 peak tracks in LCLs are shown for three (A) CBF1 independent or (B) CBF1 dependent EBNA2 binding sites. ChIP-qPCR results for EBF (middle panel) and EBNA2 (lower panel) binding to chromatin before and after EBF1 knock down are shown. Data are mean values, whiskers display standard deviations, p-values, based on a two tailed, paired t-test, are indicated.</p

Gene ontology enrichment analysis for CBF1 independent EBNA2 repressed target genes.

<p>Gene ontology enrichment analysis for CBF1 independent EBNA2 repressed target genes.</p

CBF1 independent and dependent EBNA2 binding sites are significantly enriched for activated chromatin marks in DG75 cells prior to EBNA2 binding.

<p>Based on published data sets on histone modification in DG75, the two EBNA2 peak subsets (CBF1 independent dark blue; CBF1 dependent light blue) were separately analyzed for histone activation marks typically found at enhancer regions. These data were compared to signal intensities of all peaks for the respective chromatin modification (red). (A) Anchor plots depict H3K4me1, H3K4me3, and H3K27ac at the respective peak centers and 20 kb flanking regions. (B) Data underlying panel (A) were used to generate boxplots showing the signal distributions encompassing the entire 40 kb genomic region. The significance of differences of means was assessed by unpaired two-tailed t-tests with Welch’s correction (**** p < 0.0001, *** p < 0.001). The differences of means for CBF1 independent compared to CBF1 dependent EBNA2 peaks for H3K4me1 (-0.3004 ± 0.7957; p = 0.706), H3K4me3 (0.4323 ± 1.411; p = 0.7595), and H3K27ac (-0.5184 ± 0.3501: p = 0.1396) were not statistically significant. Box plot whiskers extend to 1.5x interquartile range. (C) Table summarizing means and SEMs of histone modifications analyzed in (A) and (B).</p