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Smc3 dosage regulates B cell transit through germinal centers and restricts their malignant transformation

Nature Immunology volume 22, pages 240–253 (2021)Cite this article

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Abstract

During the germinal center (GC) reaction, B cells undergo extensive redistribution of cohesin complex and three-dimensional reorganization of their genomes. Yet, the significance of cohesin and architectural programming in the humoral immune response is unknown. Herein we report that homozygous deletion of Smc3, encoding the cohesin ATPase subunit, abrogated GC formation, while, in marked contrast, Smc3 haploinsufficiency resulted in GC hyperplasia, skewing of GC polarity and impaired plasma cell (PC) differentiation. Genome-wide chromosomal conformation and transcriptional profiling revealed defects in GC B cell terminal differentiation programs controlled by the lymphoma epigenetic tumor suppressors Tet2 and Kmt2d and failure of Smc3-haploinsufficient GC B cells to switch from B cell- to PC-defining transcription factors. Smc3 haploinsufficiency preferentially impaired the connectivity of enhancer elements controlling various lymphoma tumor suppressor genes, and, accordingly, Smc3 haploinsufficiency accelerated lymphomagenesis in mice with constitutive Bcl6 expression. Collectively, our data indicate a dose-dependent function for cohesin in humoral immunity to facilitate the B cell to PC phenotypic switch while restricting malignant transformation.

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Fig. 1: Smc3 knockout abrogates GC formation, whereas Smc3 haploinsufficiency induces GC hyperplasia.
Fig. 2: Smc3 haploinsufficiency confers a proliferative advantage to GC B cells.
Fig. 3: GC hyperplasia induced by Smc3 haploinsufficiency is due to the expansion of centrocytes.
Fig. 4: Smc3 haploinsufficiency impairs PC differentiation in vivo.
Fig. 5: Smc3wt/– centrocytes fail to upregulate GC exit genes and transition toward the PC lineage.
Fig. 6: Smc3 haploinsufficiency disrupts intra-TAD interactions and GC exit gene looping.
Fig. 7: Smc3 dosage does not impair B cell differentiation and is only required for GC exit.
Fig. 8: Smc3 deficiency accelerates malignant transformation of GC B cells and is linked to inferior outcome in people with DLBCL.

Data availability

Datasets generated in this manuscript were deposited in the NCBI Gene Expression Omnibus under the accession number GSE143852. Source data are provided with this paper.

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Acknowledgements

We thank J. Yan and B. Ren (University of California, San Diego) for their help in setting up the in situ Hi-C protocol. Sequencing was performed in the Epigenomics Core and the Genomics Core at Weill Cornell Medicine. The authors thank J. McCormick and T. Baumgartner from the Flow Cytometry Core Facility at Weill Cornell Medicine and G. Nanjangud from the Molecular Genetics Core at Memorial Sloan Kettering Cancer Center for expert assistance with protocols. A.M.M. is supported by NCI/NIH R35 CA220499, NCI/NIH P01 CA229086-01A1 (together with A.T.), LLS-SCOR 7012-16, LLS-TRP 6572-19, the Samuel Waxman Cancer Research Foundation, the Follicular Lymphoma Consortium and the Chemotherapy Foundation. M.A.R. was a recipient of a postdoctoral fellowship grant from the Lymphoma Research Foundation and is funded by an NHLBI 5 T32 HL135465-3 training grant. O.E. is supported by NIH grants UL1TR002384 and R01 CA194547 and LLS-SCOR grants 180078-02 and 7021-20. R.L.L. was supported by NCI P30 CA008748, NCI R35 CA197594-01A1, NCI R01 CA216421 and NCI PS-OC U54 CA143869-05. A.D.V. is supported by NCI K08 CA215317, the William Raveis Charitable Fund Fellowship of the Damon Runyon Cancer Research Foundation (DRG 117-15) and an Evans MDS Young Investigator grant from the Edward P. Evans Foundation. C.E.M. thanks the Scientific Computing Unit, XSEDE Supercomputing Resources as well as the Starr Cancer Consortium (I7-A765, I9-A9-071 and I13-0052) and acknowledges funding from the WorldQuant Foundation, The Pershing Square Sohn Cancer Research Alliance, the NIH (grants R01 CA249054, R01 AI151059, P01 CA214274, R01 AI125416-03 and R21 AI129851-02) and Leukemia and Lymphoma Society grants LLS 9238-16 and LLS MCL-982. A.T. is funded by American Cancer Society RSG-15-189-01-RMC, a St. Baldrick’s Scholar Award and NCI/NIH Cancer Center Support Grant P30 CA016087.

Author information

Authors and Affiliations

  1. Division of Hematology and Medical Oncology, Department of Medicine, Weill Cornell Medicine, New York, NY, USA

    Martín A. Rivas, Christopher R. Chin, Matt F. Challman, Daleum Kim, Matt R. Teater, Dylan R. McNally, Ashley S. Doane, Wendy Béguelin, María Teresa Calvo Fernández, Hao Shen, Xiang Wang & Ari M. Melnick

  2. Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA

    Cem Meydan, Christopher R. Chin, Olivier Elemento & Christopher E. Mason

  3. The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Al-Saud Institute for Computational Biomedicine, Weill Cornell Medicine, New York, NY, USA

    Cem Meydan, Christopher R. Chin, Olivier Elemento & Christopher E. Mason

  4. Caryl and Israel Englander Institute for Precision Medicine, Weill Cornell Medicine, New York, NY, USA

    Bhavneet Bhinder, Dylan R. McNally, Ashley S. Doane & Olivier Elemento

  5. Department of Pathology, New York University School of Medicine, New York, NY, USA

    Andreas Kloetgen & Aristotelis Tsirigos

  6. Human Oncology & Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA

    Aaron D. Viny & Ross L. Levine

  7. Leukemia Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA

    Aaron D. Viny & Ross L. Levine

  8. Center for Epigenetics Research, Memorial Sloan Kettering Cancer Center, New York, NY, USA

    Ross L. Levine

  9. Division of Biostatistics and Epidemiology, Department of Population Health Sciences, Weill Cornell Medicine, New York, NY, USA

    Zhengming Chen

  10. Institute for Computational Medicine, New York University School of Medicine, New York, NY, USA

    Aristotelis Tsirigos

  11. Applied Bioinformatics Laboratories, New York University School of Medicine, New York, NY, USA

    Aristotelis Tsirigos

  12. The WorldQuant Initiative for Quantitative Prediction, Weill Cornell Medicine, New York, NY, USA

    Christopher E. Mason

  13. The Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA

    Christopher E. Mason

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  1. Martín A. Rivas
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Contributions

M.A.R. conceptualized, designed and performed most experiments, with the help of M.F.C. and D.K., and analyzed and interpreted data, drafted the manuscript and supervised the study. C.M. analyzed and interpreted RNA-seq, Hi-C and Mint-ChIP data, and C.R.C. analyzed single-cell RNA-seq data with the help of M.R.T., X.W., A.K., B.B. and A.S.D. A.D.V. and R.L.L. provided the Smc3 animal model and contributed to the interpretation of results. D.R.M. has helped with the execution of experiments and analysis of data. W.B., M.T.C.F. and H.S. provided technical expertise and helped with the interpretation of results. Z.C. analyzed the clinical data. A.T., O.E. and C.E.M. provided expertise and resources for data analysis. A.M.M. participated in the study conceptualization, interpretation of data, drafting of the manuscript, acquisition of funds and supervision of the project. All authors have read and approved the submitted version.

Corresponding author

Correspondence to Ari M. Melnick.

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Competing interests

A.M.M. receives research funding from Janssen Pharmaceuticals, Sanofi and Daiichi Sankyo, has consulted for Epizyme and Constellation and is on the scientific advisory board of KDAC pharmaceuticals. R.L.L. is on the supervisory board of Qiagen and was on the scientific advisory board of Loxo, Imago, Mana, Auron, C4 Therapeutics and Isoplexis, which include equity interest. R.L.L. receives research support from and consulted for Celgene and Roche and consults for Incyte, Lilly, Janssen, Astellas, Morphosys and Novartis. R.L.L. receives research support from Prelude and has received honoraria from AstraZeneca, Roche, Lilly and Amgen for invited lectures and from Gilead for grant reviews. O.E. is supported by Janssen and Eli Lilly research grants. O.E. is a scientific advisor and equity holder in Freenome, Owkin, Volastra Therapeutics and One Three Biotech. C.E.M. is a cofounder and board member for Biotia and Onegevity Health as well as an advisor or compensated speaker for Abbvie, Acuamark Diagnostics, ArcBio, Bio-Rad, DNA Genotek, Genialis, Genpro, Karius, Illumina, New England BioLabs, Qiagen, Whole Biome and Zymo Research. C.M. is a consultant and analyst for Onegevity Health. M.A.R., C.R.C., M.F.C., D.K., B.B., A.K., A.D.V., M.R.T., D.R.M., A.S.D., X.W., W.B., M.T.C.F., H.S., Z.C. and A.T. have no relevant competing interests to declare.

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Extended data

Extended Data Fig. 1 Smc3 knockout abrogates GC formation whereas Smc3 haploinsufficiency induces GC Hyperplasia.

a, Box plots showing transcripts per million (TPM) of cohesin core subunits (Smc3, Smc1a, Stag1, Stag2 and Rad21) and regulator proteins (Nipbl, Wapl, Pds5a, Pds5b) in mouse and human (b). NB: naive B cells, CB: centroblasts, CC: centrocytes, PC: splenic plasma cells, TPC: tonsillar plasma cells, BMPC: bone marrow plasma cells. c, Scheme depicting Smc3 conditional knockout model breeding strategy and d, genotyping strategy. e, Gating strategy used for flow cytometric analysis of GC B cells. f, Genotyping of sorted GC B cells. Representative gel of one experiment out of four performed. g, Representative flow cytometry plots showing total B cells (B220+ cells) and follicular B cells (B220+CD23hiCD21lo cells) and marginal zone B cell populations (B220+CD23loCD21hi cells) and quantitative data for one representative experiment out of 4 performed in Smc3wt/wt (n=6), Smc3wt/– (n=4) and Smc3–/– (n=3) as shown (right). One-way ANoVA followed by Tukey test for multiple comparisons was used. h, i, Quantification of GC B cells, defined as B220+Fas+CD38–, 4 days (h, p=0.002) or 15 days (I, p=0.0434) after SRBC immunization. Two-tail unpaired t-test was used. j, RT-qPCR comparing Smc3 mRNA expression in GC B cells (centroblasts, CB and centrocytes, CC), plasmablasts (PB) and plasma cells (PC) in Cγ1wt/cre;Smc3wt/wt and Cγ1wt/cre;Smc3wt/– mice as indicated. Two-tail unpaired t-test was used. CB, p=0.0039, CC: p=0.0005, PB: p=0.0041 and PC: p=0.0271. k, Capillary immunoblot analyses comparing Smc3, Smc1a, Rad21 and Sag2 protein levels in centroblasts (CB), centrocytes (CC) and naïve B cells (NBC) from Cγ1wt/cre;Smc3wt/wt (n=3) and Cγ1wt/cre;Smc3wt/– (n=3) mice as indicated. Representative gel our of two experiments performed. Right panels show quantifications of the cohesin complex subunits using β-actin protein as loading control. Two-way ANoVA was used. **p<0.01. In (a) and (b) box plots show the median as center, first and third quartiles as the box hinges, and whiskers extend to the smallest and largest value no further than the 1.5 × interquartile range (IQR) away from the hinges. In (g) (h), (i), (j) and (k) data are presented as mean +/- SD.

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Extended Data Fig. 2 Smc3 haploinsufficiency confers proliferative advantage to GC B cells without chromosomal instability.

a, Cγ1wt/cre;Smc3wt/wt (n=5) and Cγ1wt/cre;Smc3wt/– (n=5) were immunized with SRBCs to induce GC formation. One hour prior to euthanasia, mice were injected with 50 mg/kg i.v. 5-ethynyl-2’-deoxyuridine (EdU). b, GC organoids were performed with splenocytes from Cγ1wt/cre;Smc3wt/wt and Cγ1wt/cre;Smc3wt/– mice. c, On day 0 and day 4 after organoid plating, the presence of B cells and GC-like cells (B220+Fas+GL7+) was determined by flow cytometry. d, Gating strategy followed to detect apoptotic active Caspase-3+ GC B cells.

Extended Data Fig. 3 GC hyperplasia induced by Smc3 haploinsufficiency is due to expansion of centrocytes.

(a) Mice were immunized with sheep red blood cells (SRBCs) to induce GC formation and euthanized 8 days after. (b) Gating strategy followed to identify DZ (B220+Fas+CD38–CXCR4+CD86–) and LZ (B220+Fas+CD38–CXCR4–CD86+) GC B cells. (c) Quantification of absolute numbers of DZ centroblasts (Cγ1wt/cre;Smc3wt/wt (n=7) and Cγ1wt/cre;Smc3wt/– (n=6) mice) or LZ centrocytes (Cγ1wt/cre;Smc3wt/wt (n=6) and Cγ1wt/cre;Smc3wt/– (n=6) mice). (d) Cγ1wt/cre;Smc3fl/fl were crossed to Rosa26YFP/YFP to produce mice that express the yellow fluorescent protein when expressing the cre recombinase. (e) Gating strategy used in Cγ1wt/cre;Rosa26YFP;Smc3wt/– and Cγ1wt/cre;Rosa26YFP;Smc3wt/wt mice to identify YFP+ GC B cells. (f) Plot showing YFP+ GC B cells in the reporter Cγ1wt/cre;Rosa26YFP;Smc3wt/– (n=4) and Cγ1wt/cre;Rosa26YFP;Smc3wt/wt (n=9) mice. In (c) and (f) data are presented as mean +/- SD.

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Extended Data Fig. 4 Smc3 haploinsufficient mice have impaired terminal differentiation.

a, Mice were immunized on day 0 with 100 μg NP-KLH:Alum 1:1 i.p., and received a boost on day 21 of 100 μg NP-CGG: Alum 1:1 i.p. Mice were bleed on days 0, 14, 26, 35 and 70, at which time were euthanized. b, Representative flow cytometry gating strategy followed to determine the presence of bone marrow plasma cells (BMPC, CD138+B220– cells) and long-lived BMPCs (NPcyt+IgG1cyt+CD138+B220– cells). c, Representative flow cytometry gating strategy followed to determine the percentage of IgM- and IgG1-expressing GC B cells. d, Frequency of IgG1+, IgM+, or IgG1+/IgM+ GC B cells in 4, 8 or 15 day SRBC immunized Cγ1wt/cre;Smc3wt/wt (n=5) or Cγ1wt/cre; Smc3wt/– (n=5) mice. Two tail unpaired t-test. All differences are statistically non-significant. e, Splenocytes from Cγ1wt/cre;Rosa26YFP;Smc3wt/wt (n=5) and Cγ1wt/cre;Rosa26YFP;Smc3wt/– (n=5) mice were cultured in the presence of IL-4, LPS and anti-CD40 antibody and PB/PC followed by flow cytometry and f, levels of active Cspase-3 were detected by flow cytometry using the presented gating strategy. g, Active Caspase-3 levels in B cells, PBs and PCs from ex vivo cultures. h-i, 8, 15 and 25-day immunized mice were sacrificed and splenocytes stained for GC markers. Nuclear staining of Irf4 was done afterwards. (h) Representative flow cytometry plots of IRF4+ GC B cells and (i) plots depicting the percentage of IRF4+ GC B cells in Cγ1wt/cre;Smc3wt/wt (n=5) and Cγ1wt/cre;Smc3wt/– (n=5) mice (at every time point). j, At each time point, mice were injected with 50 μg/kg EdU i.p. and sacrificed one hour later. Quantification of IRF4+ GC B cells in S-phase in the spleens of SRBC immunized mice for the indicated times in Cγ1wt/cre;Smc3wt/wt (n=5) and Cγ1wt/cre;Smc3wt/– (n=5) mice at every time point. **p<0.01, ***p<0.001 and ****p<0.0001. In (d), (i) and (j) data are presented as mean +/- SD. (i) and (j) two-way ANoVA and Sidak multi-comparison test was used.

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Extended Data Fig. 5 Smc3wt/– centrocytes fail to upregulate GC exit genes and transition towards the plasma cell lineage.

a, Gene set enrichment analysis (GSEA) plots for TET2_KO and shKMT2D_DOWN. b, Sorting strategy used for single cell RNA-seq by BDRhapsody.

Extended Data Fig. 6 Smc3 haploinsufficiency disrupts intra-TAD interactions and GC exit gene looping.

a, Genome wide chromosomal interactivity was mapped by in situ Hi-C in Cγ1wt/cre;Smc3wt/wt (n=2) or Cγ1wt/cre;Smc3wt/– (n=2) centrocytes (B220+Fas+CD38–CXCR4–CD86+) from 8 day SRBC immunized mice. b, Cartoon depicting the definition of intra- and inter-TAD connectivity. c, Log2 fold change of inter- and intra-TAD interactions in Smc3 haploinsufficient versus wild-type centrocytes. p-value expresses significant difference between inter- and intra-TAD interactions. Wilcoxon rank-sum test was used, p<2.2×10–16. d, TAD boundary strength for Smc3 haploinsufficient centrocytes versus wild-type centrocytes by Hi-C. Wilcoxon rank-sum test was used, p<2.2×10–16. e, z-score of promoter short-range interactivity change plotted for genes which are downregulated, non-changing or upregulated in centrocyte RNA-seq of Smc3 haploinsufficient cells versus control. Wilcoxon rank-sum test was used, Down vs NS p<1.6×10–7, NS vs Up p=0.055 and Down vs Up p=0.00024. f, Gene set enrichment of compartment changes in Smc3 haploinsufficient vs wild-type centrocytes. Compartment C-scores are calculated in 100 kb intervals and annotated to genes based on the location of their TSS within these bins. Genes are ranked by Δ c-score and analyzed by GSEA. g, Gene set enrichment of enhancer-promoter interactivity changes in Smc3 haploinsufficient vs wild-type centrocytes. Enhancers are annotated to the nearest TSS (as explained in Methods), normalized contacts between a gene and all its enhancers are summed to get an aggregate promoter-enhancer looping score. Genes are ranked by Δ promoter-enhancer score between Smc3 haploinsufficient and wild-type mice and analyzed by GSEA. In (c) and (e) box plots show the median as center, first and third quartiles as the box hinges, and whiskers extend to the smallest and largest value no further than the 1.5 × interquartile range (IQR) away from the hinges.

Extended Data Fig. 7 Smc3 dosage does not impair B cell differentiation and is only required for GC exit.

a, Scheme depicting Smc3 conditional knockout model breeding strategy. b, Early B cell differentiation stages and markers used for identification. c, Representative flow cytometry plots of splenic CD3+ T cells, B220+ B cells and naïve B cells in CD19wt/cre;Smc3wt/wt (n=4), C19wt/cre;Smc3wt/– (n=7) and C19wt/cre;Smc3–/– (n=4) and d, quantification of ratio between splenic B220+/CD3+ cells in Cd19wt/cre;Smc3wt/wt (n=4), Cd19wt/cre;Smc3wt/– (n=7) and Cd19wt/cre;Smc3–/– (n=4) (****p<0.0001) or e, naïve B cells in Cd19wt/cre;Smc3wt/wt (n=5) and Cd19wt/cre;Smc3wt/– (n=9). f, Quantification of the percentage of bone marrow pre-BI cells, immature B cells, and splenic follicular B cells in Cd19wt/cre;Smc3wt/wt (n=4) and Cd19wt/cre;Smc3wt/– (n=5). NS: non-significant differences. In (d), (e), and (f) data are presented as mean +/- SD. In (d) and (e) one-way ANoVA and Tukey multi-comparison test was used, and two-way unpaired t-test in (f).

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Extended Data Fig. 8 Haploinsufficiency of Smc3 cooperates with Bcl6 to induce lymphoma.

a, Bone marrow transplantation experimental design. Bone marrow cells were isolated from Cγ1wt/cre;Smc3wt/wt, Cγ1wt/cre;Smc3wt/–, IμBcl6;Cγ1wt/cre;Smc3wt/w and IμBcl6;Cγ1wt/cre;Smc3wt/– CD45.2 donors, and transplanted through tail vein injection into lethally irradiated CD45.1 mice. After engraftment, mice were immunized with SRBCs every 3 weeks for the duration of the experiment. Mice were euthanized when presented with signs of disease. b, Representative flow cytometry plots performed 300 days after engraftment showing that all B220+ are CD45.2+ and CD45.1–, demonstrating that all B cells in these mice come from the donor and not from the recipient. c, Representative allele occurrence was showed by performing PCR in DNA from tumors from IμBcl6;Cγ1wt/cre;Smc3wt/w and IμBcl6;Cγ1wt/cre;Smc3wt/– mice. One representative gel is shown out of 2 experiments performed.

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Rivas, M.A., Meydan, C., Chin, C.R. et al. Smc3 dosage regulates B cell transit through germinal centers and restricts their malignant transformation. Nat Immunol 22, 240–253 (2021). https://doi.org/10.1038/s41590-020-00827-8

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