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The transcription complex p52–ETS1 is essential for germinal center formation

Abstract

The NF-κB family comprises five transcription factors (RELA, RELB, C-REL, NF-κB1 (p50) and NF-κB2 (p52)) that form homo- or heterodimers among themselves to regulate gene expression by binding DNA. Here we show that p52 activates transcription without directly binding DNA but as a heterotetrameric complex with ETS1, a transcription factor outside the NF-κB family. By generating a knock-in mouse model (Nfkb2ki/ki) with three mutated residues on p52 required for its interaction with ETS1, but not RELB, we demonstrate that the p52–ETS1 complex regulates the expression of transcription factors OCT1 and OBF1, which are known to be critical for the germinal center program. Consequently, B cell-intrinsic expression of the p52–ETS1 complex was indispensable for splenic germinal center B cell formation and T cell-dependent antibody responses. Functionally, loss of p52–ETS1 interaction led to diminished antigen-specific IgE, thereby protecting mice from allergic responses. Collectively, our findings expand current knowledge of NF-κB signaling and may provide new therapeutic targets for the treatment of allergic diseases.

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Fig. 1: Generation of p52ki/ki mice with disruption of the p52–ETS1 interaction.
Fig. 2: p52–ETS1 interaction is necessary for splenic GC B cell responses to T cell-dependent immunization.
Fig. 3: B cell-intrinsic disruption of the p52–ETS1 complex impairs splenic GC responses.
Fig. 4: Disruption of the p52–ETS1 complex alters gene expression during the differentiation of B cells into GC B cells.
Fig. 5: p52–ETS1 is necessary for OCT1 and OBF1 expression in GC B cells.
Fig. 6: p52–ETS1 binding sites are present in the promoter regions of Pou2f1 and Pou2af1.
Fig. 7: p52–ETS1 is necessary for IgE-mediated allergic responses.

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Data availability

Raw and processed data files for bulk RNA-seq, ChIP–seq and scATAC–seq analyses have been deposited in the NCBI Gene Expression Omnibus under accession numbers GSE299466 (scATAC–seq), GSE300334 (ChIP–seq), GSE300335 (GC B cell RNA-seq) and GSE300336 (pre-GC B cells RNA-seq).

Code availability

The custom code used in analyzing the datasets is available via Zenodo at https://doi.org/10.5281/zenodo.15628175 (ref. 54) and https://doi.org/10.5281/zenodo.15680988 (ref. 55) for scATAC–seq and all other datasets, respectively.

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Acknowledgements

We thank all members of the laboratories of V.T. and K-.P.L. for useful discussion and advice. We thank the SIgN Flow Cytometry Core, in particular S. Mustafah and J. M. Ong, for cell sorting services. We are also grateful to G. Yeo (GIS, A*STAR) and Y. Tan (SIgN, A*STAR) for helpful discussions about scATAC–seq analyses and imaging, respectively. This work was supported by MOH-OFIRG21jun-0014, NRF-CRP26-2021-0001 and MOH-OFIRG24jan-0003 awarded to V.T. This work was also supported by SIgN Core Funds and HHP-IAF-PP:H22J1a0046 awarded to K.-P.L. D.M. and B.Z. are supported by an A*STAR Graduate Scholarship and National Science Scholarship from the Agency for Science Technology and Research Singapore, respectively. B.Z. is supported by the A*STAR Career Development Fund C210812013. G.G. and S.S. were supported by the National Institutes of Health (GM 085490). V.Y.-F.W. and W.P. were supported by the Science and Technology Development Fund, Macao S.A.R. (FDCT) (0089/2022/AFJ) and the Multi-Year Research Grant from University of Macau (MYRG2018-00093-FHS).

Author information

Authors and Affiliations

Authors

Contributions

D.M. and B.Z. conceptualized the project, designed and performed all experiments, analyzed all data and wrote the paper unless otherwise stated. A.R., T.Y.S., J.Y., A.H.-H.W. and M.M.H.M. assisted with performing the experiments. T.S.V. performed PCAs. M.I. generated the p52ki/ki mouse model. D.H. and A.B. helped with confocal microscopy and image processing. W.P. and V.Y.-F.W. designed and performed BLI. K.F. performed all computational analyses unless otherwise stated. S.W.H. and S.H.F. helped design and perform scATAC–seq experiments. N.A., W.L.T. and M.C.L. analyzed the scATAC–seq data. S.S. and G.G. helped to design and optimize the ChIP–seq experiments. I.N.S. and J.W.C. performed ChIP–seq experiments on human cell lines. P.M. performed EMSAs. Y.F.P., P.J. and A.D.J. designed and optimized PLA assays. I.T. optimized the cell fractionation protocol. S.X. and Y.Z. helped with experimental design. V.T. and K.-P.L. obtained funding for this research and co-wrote the paper. All authors approved the final draft of the paper.

Corresponding authors

Correspondence to Kong-Peng Lam or Vinay Tergaonkar.

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The authors declare no competing interests.

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Nature Immunology thanks Lee-Ann Garrett-Sinha and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available. Primary Handling Editor: L. A. Dempsey, in collaboration with the Nature Immunology team.

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Extended data

Extended Data Fig. 1 Characterisation of p52-RMK > A mutant and its binding to known partners and DNA.

a-d, Biolayer interferometry (BLI) assays were performed to measure the binding affinities. Each experiment was performed in duplicate and one representative set of curves is shown. (a) RMK > A mutations of p52 does not affect p52-RELB heterodimer binding to DNA. Biotin-TEG-κB DNA immobilized on streptavidin biosensors was incubated with WT p521-398: RELB 1-400 (left) and mutant RMK > A p521-398: RELB 1-400 (right) in solution at 2-fold serial dilutions (from 50 nM to 3.13 nM). (b) RMK > A mutations does not affect p52 homodimer binding to DNA. Biotin-TEG-κB DNA immobilized on streptavidin biosensors was incubated with WT p521-398 homodimer (left) and mutant RMK > A p521-398 homodimer (right) in solution at 2-fold serial dilutions (from 50 nM to 3.13 nM) were tested for WT p521-398 and mutant RMK > A p521-398 homodimers. (c) BLI showed RMK > A mutations of p52 does not affect p52:BCL3 binding. His-tagged-BCL3 immobilized on Ni-NTA biosensors was incubated with p521–398 WT (left) and p521–398 RMK > A mutant (right) in solution at 2-fold serial dilutions (from 80 nM to 5 nM). (d) p52 WT and RMK > A mutant does not interact with p53. His-tagged-p53 immobilized on Ni-NTA biosensors was incubated with p52 WT and RMK > A mutant in solution at a high protein concentration of 180 nM.

Source data

Extended Data Fig. 2 Immune cell profiling in p52ki/ki mice.

(a) Mendelian genotypes from p52+/ki crosses. b-e, Immunoprecipitation assays using mice spleen. Lanes 1–2: Input. Lanes 3–4: IP fractions. Lanes 5–6: IgG control. (b) Anti-p52 IP. p52 and RELB on one blot. ETS1 and GAPDH on another blot using same samples. (c) Data from (Fig. 1g), with additional ETS2 detection on a separate blot using same samples. b-c, Representative data from 3 biological replicates. (d) Anti-ETS1 IP. ETS1 and HSP90 on one blot. RUNX1, p50 and GAPDH on another blot using same samples. (e) B cell lysates, anti-ETS1 IP. ETS1, p65 and GAPDH on one blot. p100/ p52 and PAX5 on separate blots using same samples. d-e, Data in (d) and (e) are representative of 2 and 3 biological replicates respectively. (f) Transcription of Cd79α and Tcrβ in spleen, n = 12 per group. Pooled data from 3 independent experiments, n = 4 mice per group. g-i, Nuclear and cytoplasmic ETS1 expression in splenic B cells. (g) Data are representative of 4 biological replicates. Densitometry ratio of (h) ETS1/GAPDH and (i) ETS1/LAMIN B, n = 4 per group. Pooled data from 4 biological replicates. j-r, Summary bar graphs. (j-k) Lineage negative (Lin-), c-Kit positive, Sca-1 positive, lineage negative (KSL) and c-Kit positive, lineage negative (KL) cells. (l-m) Granulocyte macrophage progenitor (GMP), common myeloid progenitor (CMP), megakaryocyte erythroid progenitor (MEP). (n-o) Short-term hematopoietic stem cells (ST-HSC), long-term hematopoietic stem cells (LT-HSC) and multipotent progenitor (MPP). j-o, Bone marrow cells, n = 4 per group. Pooled data from 2 independent experiments, n = 2 per group. (p) Splenic B and T cells, n = 10 per group. Pooled data from 2 independent experiments, n = 2-8 per group. (q) B cell precursors in bone marrow, n = 8 per group. Data are representative of 2 independent experiments. (r) Thymic CD4+, CD8+, CD4CD8, CD4+CD8+, CD44+, CD25+, CD44CD25 and CD44+CD25+cells, n = 6 per group. Data are pooled from 3 independent experiments, n = 2 per group. f,j-r, Data are presented as mean ± sd, each data point representing one mouse. All mice used were 8-12 weeks old, mixed gender. Statistical analyses were performed using two-tailed Mann-Whitney U tests in (f),ns=not significant and ordinary one-way ANOVA in (j-r).

Source data

Extended Data Fig. 3 Loss of p52-ETS1 interaction affects inguinal lymph nodes GC B cells and splenic TFH cell formation but not chronic GCs.

(a) Representative flow cytometry plots and summary bar graphs of frequencies of (b) follicular B cells (CD23+CD21+ CD19+) and (c) marginal zone B cells (CD23 CD21+CD19+) in p52+/+ (Ctrl) and p52ki/ki mice at steady state, n = 10 per group. Pooled data from 3 independent experiments with at least n = 3 mice per group. Summary bar graphs of (d) frequencies and (e) numbers of GC B cell (CD19+ IgD Fas+ GL7+) assessed by flow cytometry 5 days post intraperitoneal immunization of Ctrl and p52ki/ki mice with NP-OVA and alum, n = 11 per group. Pooled data from 3 independent experiments with at least n = 3 mice per group. f-i, Characterization of chronic GCs in mesenteric lymph nodes (MLN) and Peyer’s patches (PP) of naive Ctrl and p52ki/ki mice by flow cytometry. Summary bar graphs of (f,h) GC B cell frequencies and (g, i) numbers in the MLN and PP respectively. Pooled data from 3 independent experiments with at least n = 3 mice per group. j-k, Ctrl and p52ki/ki mice were immunized subcutaneously with NP-OVA+alum and GCs in inguinal lymph node (ILN) and examined on day 9 by flow cytometry. Summary bar graphs of GC B cell frequencies (j) and numbers (k) in ILN from Ctrl (n = 10) and p52ki/ki (n = 9) mice. Pooled data from 3 independent experiments with minimally n = 3 mice per group. (l) Representative flow cytometry plots of (m) frequencies of splenic TFH cells (CXCR5+PD-1+) 9 days post intraperitoneal immunization of Ctrl (n = 11) and p52ki/ki (n = 10) mice with NP-OVA and alum. Pooled data from 3 independent experiments with minimally n = 3 mice per group. b-k,m, Data are presented as mean ± sd and analysed by two-tailed Mann-Whitney U-tests. Mice were sex matched per experiment. Both male and female mice used in these experiments were 8-12 weeks old.

Source data

Extended Data Fig. 4 B cell-intrinsic disruption of p52-ETS1 interaction does not affect TFH differentiation.

a-b, Mixed bone marrow chimeric mice were made using irradiated C57BL/6 wildtype (CD45.1) recipient mice reconstituted with bone marrow cells from muMT (CD45.2) and wildtype (CD45.1.2) or p52ki/ki (CD45.1.2) mice in a 1:1 ratio, set up to study B cell-intrinsic role of p52:ETS1 interaction. Representative flow cytometry plots of (a) CD19+ cells and (b) CD19 cells in peripheral blood of 8 weeks post bone marrow transfer in recipient Ctrl and B-p52ki/ki mice. Representative data of 3 independent experiments, minimum n = 4 mice per group. c-f, Ctrl and B-p52ki/ki were immunized with NP-OVA and alum intraperitoneally before T follicular helper (TFH) cells frequencies and functionality were assessed by flow cytometry on day 9. (c) Representative flow cytometry plots and summary bar graphs of (d) frequencies of TFH cells (CXCR5+PD-1+), n = 13 mice per group. Pooled data from 3 independent experiments with at least n = 4 mice per group. Summary bar graphs of mean fluorescence intensity (MFI) of ICOS (e) or BCL6 (f) in splenic TFH cells from Ctrl (n = 5) and B-p52ki/ki (n = 4) mice. Representative data from 3 independent experiments with at least n = 4 mice per group. d-f, Data are presented as mean ± sd with each data point representing biological sample from an individual mouse. Statistical analyses were performed using two-tailed Mann-Whitney U-tests in (d-f). All mice used in these experiments were 8 weeks old males at the point of bone marrow reconstitution and 16-18 weeks old at the beginning of each experiment.

Source data

Extended Data Fig. 5 p52-ETS1 interaction regulates gene expression in GC and pre-GC B cells.

(a) Representative gating strategy showing the identification and sorting of various B cell populations for RNA-seq: naïve B cells (CD19+ IgD+), GC B cells (CD19+ IgDGL7+FAS+) and activated non-GC B cells (CD19+ IgDGL7FAS). b-e, RNA-seq analyses of splenic B cell populations (naïve, activated non-GC and GC B cells) sorted from control (Ctrl) and p52ki/ki mice 9 days post NP-OVA and alum immunization. (b) Heatmap of DEGs for different B cell populations from mice. 1, 2 and 3 refer to an individual mouse. Z-scores of log2 (CPM + 1) of gene expression are calculated and plotted as heatmap. (c) Gene sets enriched for DEGs between p52ki/ki and Ctrl GC B cells analyzed by Enrichr using gene signatures from MSigDB Hallmark (adjusted p-value < 0.05). Top 5 enrichments are shown based on p-value ranking. Enrichment of genes upregulated by (d) BCR and (e) CD40, highly expressed in p52ki/ki GC B cells compared to Ctrl GC B cells analyzed by GSEA. NES, normalized enrichment score. f-l, RNA-seq analyses of splenic pre- GC B cells sorted from of Ctrl and p52ki/ki mice 9 days post NP-OVA and alum immunization (f) Representative gating strategy showing the identification and sorting of live pre-GC B cells (CD19+ IgDGL7+CD38+) for RNA-seq. (g) Volcano plot of DEGs (2-fold; p < 0.05) between Ctrl and p52ki/ki pre-GC B cells. (h) Heatmap of DEGs in pre-GC B cells from mice. 1, 2, 3, 4 and 5 refer to an individual mouse. Z-scores of log2 (CPM + 1) of gene expression are calculated and plotted as heatmap. Normalized gene expression of (i) Aicda, (j) Mki67, (k) Pou2f1and (l) Prdm1 presented as log2 count per million (CPM) based on RNA-seq in (g) of Ctrl and p52ki/ki pre-GC B cells. Box plots show median (center line), interquartile range (box: 25th to 75th percentile), and whiskers extending to data points within 1.5× the IQR. Points beyond are shown as outliers. g,i-l, Data from n = 4 Ctrl mice and n = 5 p52ki/ki mice. Statistical analyses were performed using empirical Bayes moderated t-test. Mice were sex matched per experiment using both 8-12 weeks old male and female mice.

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Extended Data Fig. 6 p52-ETS1 affects chromatin accessibility based on scATAC-seq in B cells.

a-c, Splenic B cell subsets were sorted from Ctrl and p52ki/ki mice 9 days post NP-OVA and alum immunization for scATAC-seq. (a) Summary bar graphs of cell numbers for each B cell cluster identified from scATAC-seq from control and p52ki/ki mice on day 9 post NP-OVA and alum immunization (Fig. 4k). (b)Weighted kernel density plot presenting gene activity levels of Ighm and Ighd naïve B cells. (c) Top panel: Coverage plot illustrating normalized scATAC-seq sequencing tracks for Prdm1 gene across all clusters identified in (a). Bottom panel: Combined coverage plot across all clusters for the region in red box presented in upper panel. Two-tailed wilcoxon rank-sum statistical test with adjustment for multiple comparisons correction was used to analyze data, adjusted p ≤ 0.05. d-f, Ctrl and p52ki/ki were immunized with NP-OVA and alum intraperitoneally before expression of markers of proliferation and apoptosis on GC B cells (CD19+ IgD Fas+ GL7+) were assessed by flow cytometry on day 9. (d) Summary bar graph of frequencies of Ki-67+ cells within splenic GC B cell population. (e) Representative flow cytometry plots and summary bar graphs of (f) frequencies of active caspase 3+ (aCasp3) cells within splenic GC B cell population from Ctrl (n = 9) and p52ki/ki (n = 10) mice. Pooled data from 3 independent experiments, minimum n = 3 mice per group. d,f, Data are presented as mean ± sd with each data point representing biological sample from an individual mouse. Statistical analyses were performed using two-tailed Mann-Whitney U-tests in (d, f). Mice were sex matched per experiment. Both male and female mice used in these experiments were 8-12 weeks old.

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Extended Data Fig. 7 Potential ETS1 binding sites on promoters of OCT1 and OBF1.

JASPAR prediction based on 1000 nucleotides upstream of the transcription start site identified (a) 5 potential binding sites for ETS1 at the mouse Pou2f1 gene promoter and (b) 4 potential binding sites for ETS1 at the mouse Pou2af1 gene promoter. ChIP-seq tracks of p52 in L1236 B cells and ETS1 and RELB in GM12828 B cells at the human (c) POU2AF1 and (d) POU2F1 gene promoters. c-d, Data retrieved from Cistrome database. (e) JASPAR prediction based on 1000 nucleotides upstream of the transcription start site identified top 5 potential binding sites for ETS1 at the human POU2AF1 gene promoter.

Extended Data Fig. 8 Electrophoretic mobility shift assay reveals cooperative binding of p52-ETS1 on human POU2AF1 promoter sequence.

(a)Murine Pou2af1 promoter sequence. The highlighted ~330 bp region denotes the promoter segment containing two ETS1 binding sites (marked in red). (b) Human POU2AF1 promoter sequence used for the EMSA assay. The highlighted ~330 bp region denotes the promoter segment containing two ETS1 binding sites (marked in red). (c) Sequence alignment analysis showing the ETS1 binding sites (site 1 in purple and site 2 in blue) in the Pou2af1 promoter sequence to be conserved among human and mice. (d) Recombinant p52 and ETS1 proteins (500 ng) were analysed for cooperative binding on the POU2AF1 promoter DNA-labelled probes (Cy5 labeled) with EMSA. Data are representative of two independent experiments. Lane 1: Free POU2AF1 promoter DNA-Cy5 labelled probe, Lane 2: Binding of ETS1 alone with the labelled probe, Lane 3: Binding of p52 alone with the labelled probe, Lane 4: Cooperative binding of p52 and ETS1 proteins with the labelled probe (marked by the top arrow), Lane 5: Cooperative binding of p52RMK>A mutant and ETS1 proteins with the labelled probe.

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Supplementary Methods for additional protocols and Supplementary Tables 1 and 2 for primers and antibodies, respectively.

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Morgan, D., Zhang, B., Fidan, K. et al. The transcription complex p52–ETS1 is essential for germinal center formation. Nat Immunol 26, 1553–1566 (2025). https://doi.org/10.1038/s41590-025-02236-1

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