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PI3Kγ in B cells promotes antibody responses and generation of antibody-secreting cells

Nature Immunology (2024)Cite this article

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Abstract

The differentiation of naive and memory B cells into antibody-secreting cells (ASCs) is a key feature of adaptive immunity. The requirement for phosphoinositide 3-kinase-delta (PI3Kδ) to support B cell biology has been investigated intensively; however, specific functions of the related phosphoinositide 3-kinase-gamma (PI3Kγ) complex in B lineage cells have not. In the present study, we report that PI3Kγ promotes robust antibody responses induced by T cell-dependent antigens. The inborn error of immunity caused by human deficiency in PI3Kγ results in broad humoral defects, prompting our investigation of roles for this kinase in antibody responses. Using mouse immunization models, we found that PI3Kγ functions cell intrinsically within activated B cells in a kinase activity-dependent manner to transduce signals required for the transcriptional program supporting differentiation of ASCs. Furthermore, ASC fate choice coincides with upregulation of PIK3CG expression and is impaired in the context of PI3Kγ disruption in naive B cells on in vitro CD40-/cytokine-driven activation, in memory B cells on toll-like receptor activation, or in human tonsillar organoids. Taken together, our study uncovers a fundamental role for PI3Kγ in supporting humoral immunity by integrating signals instructing commitment to the ASC fate.

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Fig. 1: PI3Kγ is required for T cell-dependent antibody responses.
Fig. 2: PI3Kγ is dispensable for Ig class switching and somatic mutation frequency but required for GC B cells to adopt ASC gene signatures.
Fig. 3: Loss of B cell-intrinsic PI3Kγ is sufficient to impair specific IgG responses with no effect on overall IgA production.
Fig. 4: PI3Kγ functions in activated GC B cells to promote generation of ASCs.
Fig. 5: Human B cells require PI3Kγ for PIP3-dependent primary and secondary ASC formation via IRF4 induction.

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Data availability

Bulk RNA-seq and scRNA-seq and BCR-seq data are available via the Gene Expression Omnibus (GEO) and were analyzed using mm10 reference genome. The bulk and scRNA-seq data used in the present study are available through the GEO database under accession nos. GSE269303 and GSE269300, respectively. Source data are provided with this paper.

Code availability

Customized scripts in R v.4.3.1 for scBCR analysis were deposited under bitbucket.org/kleinstein/projects (Lanahan2023 folder).

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Acknowledgements

We thank the patients and their families for participation in research and all clinical care staff for their contributions. We thank L. Wirth for technical assistance, J.-M. Carpier for critical feedback and training, E. Fagerberg and J. Attanasio for contributions to RNA-seq experimental design and A. Rice for his contributions. We acknowledge D. Kitamura, Tokyo University of Science, Organization for Research Advancement, Research Institute for Biomedical Sciences for the 40LB feeder cell line used in Extended Data Fig. 3. C.L.L. received funding for this work from the Colton Center for Autoimmunity at Yale, NIH/NIAID (grant no. R21AI144315) and Yale University. M.P.W. was funded by the Swiss National Science Foundation (SNF; grant no. 310030_189065). N.R. is funded by the NIH, NIAID (grant no. AI146026 to N.R.), the Chan Zuckerberg Initiative Pediatric Human Cell Atlas and the Jeffrey Modell Foundation. BioRender.com was used for schematics in Extended Data Fig. 2h and Extended Data Fig. 6.

Author information

Authors and Affiliations

  1. Department of Immunobiology, Yale University School of Medicine, New Haven, CT, USA

    Stephen M. Lanahan, Lucas Yang, Kate M. Jones, Zhihong Qi, Anjali Ramaswamy, Anis Barmada, Dinesh Babu Uthaya Kumar, Lan Xu, Peiying Shan, Steven H. Kleinstein & Carrie L. Lucas

  2. Division of Immunology and Allergy, Children’s Hospital of Philadelphia, Philadelphia, PA, USA

    Emylette Cruz Cabrera & Neil Romberg

  3. Immunology Graduate Group, Perelman School of Medicine, Philadelphia, PA, USA

    Lauren Y. Cominsky

  4. Department of Pathology, Yale University School of Medicine, New Haven, CT, USA

    Gisela Gabernet & Steven H. Kleinstein

  5. Department of Biomedicine, University of Basel, Basel, Switzerland

    Matthias P. Wymann

  6. Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA

    Steven H. Kleinstein

  7. Primary Immunodeficiency Clinic, Laboratory of Clinical Immunology and Microbiology, NIAID, NIH, Bethesda, MD, USA

    V. Koneti Rao

  8. Division of Allergy and Immunology, Department of Pediatrics, Nationwide Children’s Hospital, Columbus, OH, USA

    Peter Mustillo

  9. Department of Pediatrics, Perelman School of Medicine, Philadelphia, PA, USA

    Neil Romberg

  10. Department of Pathology and Laboratory Medicine, Nationwide Children’s Hospital, Columbus, OH, USA

    Roshini S. Abraham

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Contributions

S.M.L. was involved in idea generation, performed experiments, analyzed data and wrote the manuscript. L.Y. and K.M.J. performed experiments, analyzed data and wrote methods for their work. Z.Q., D.B.U.K., L.X. and P.S. conducted experiments and analyses. E.C.C., L.Y.C. and N.R. conducted and analyzed the tonsillar organoid experiments. A.R., A.B., G.G. and S.H.K. performed analysis of single-cell transcriptome and BCR-seq. K.R., P.M. and R.A. provided patient care and analyses relating to patient A.1’s samples. M.P.W. provided KO and floxed mice and input. C.L.L. supervised overall research and data analysis, was involved in idea generation and wrote and edited the manuscript. All authors discussed and reviewed the manuscript.

Corresponding author

Correspondence to Carrie L. Lucas.

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Competing interests

C.L.L. reports an advisory/consulting role for Pharming Healthcare Inc. and unrelated funding support from Ono Pharma. S.H.K. receives consulting fees from Peraton. R.S.A. discloses support from ClinGen, Journal of Immunology and Clinical Laboratory Standards Institute. The remaining authors declare no competing interests.

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Nature Immunology thanks Sidonia Fagarasan and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. L. A. Dempsey was the primary editor on this article and managed its editorial process and peer review in collaboration with the rest of the editorial team.

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Extended data

Extended Data Fig. 1 PI3Kγ is required for T-dependent antibody responses.

(a-b) Serum IgM (a) and IgA (b) levels in Patient A.1. (c-e) Mice were immunized (as in Fig. 1b, c) and antigen-specific IgM (day 5) (c), primary (non-boosted) IgG1 (day 12) (d), or IgG2c (e) was measured via high conjugation ratio NP-BSA ELISA. (f) Mice were immunized (as in Fig. 1d, e) and IgG2b was measured via NP-BSA ELISA. Data are from 2-3 independent experiments and are presented as box-and-whisker plots showing median, min, and max. Data points represent different biological samples. Statistical analysis was performed using non-parametric two-tailed unpaired T-tests. (c) n = 12 for control, n = 12 for KO. (d) n = 15 for control, n = 14 for KO. (e) n = 12 for control, n = 11 for KO. (f) n = 5 for control, n = 6 for KO.

Source data

Extended Data Fig. 2 PI3Kγ is required for GC B cells to adopt ASC gene signatures.

(a) Stacked bar plots showing proportions of cell subsets within Naïve or GC B cells used for CSR/SHM analysis. (b) Percentage of high-affinity W38L mutations from the total number of sequences with IGHV1-72 gene and lambda light chains. Statistical analysis was Wilcoxon Rank Sum (c-d) Quantification of marginal zone B cells (c) and follicular B cells (d) from the spleens of indicated mice assessed by flow cytometry. Data are representative of 2 independent experiments (n = 5 for each condition). (e) Volcano plot showing gene expression from RNA sequencing in sorted naïve B cells (IgD+ B220+) from WT versus PI3Kγ KO mice 28 days after SRBC i.p. immunization. Data are from one experiment. (f) Volcano plot of differentially expressed genes from bulk RNA sequencing of sorted GC B cells at day 28 post immunization, as described for Fig. 2e. (g) Expression of ‘Activated B cell’ UPR program genes in sorted splenic GC B cells from Pik3cg heterozygous or KO mice 28 days after SRBC immunization. Transcriptional program is defined by Gaudette, et. al 2020. Data are from one experiment (n = 3 for het, n = 4 for KO). (h) Diagram of germinal center B cells that are beginning to adopt expression of antibody secreting cell surface markers (CD138). Diagram was created with BioRender.com. (c-d) Each dot represents different biological samples and data are presented as box-and-whisker plots showing median, min, and max. Statistical analysis was performed using non-parametric two-tailed unpaired T-tests.

Source data

Extended Data Fig. 3 B cells lacking PI3Kγ activate normally and are capable of forming germinal centers and normal IgA responses.

(a) Littermate control or conditional Pik3cg KO mice were immunized and boosted with NP-OVA precipitated in alum. Antigen-specific IgG2c (day 28) was measured via NP-BSA ELISA, and arbitrary units were defined using pooled immunized sera as a standard. (b) Immunofluorescence imaging of spleens from indicated mice 28 days after SRBC immunization. Data are representative of two independent repeats (n = 6 for each genotype). (c-h) Murine naïve B cells were stimulated using TI stimulation with TLR agonists (CpG or LPS) or TD stimulation with anti-CD40, anti-IgM F(ab’)2 and assessed for proliferation using cell trace violet (gating on live cells after 4 days) and activation by staining for CD69 or CD86 (gating on live cells after 2 days). Data (n = 3 for each condition) are representative of two independent experiments. (i-n) Quantification of B cell subsets from Peyer’s patches of mice assessed by flow cytometry. Data are representative of three independent experiments (n = 13 for control and 14 for KO). (o) Quantification of fecal IgA in control versus B cell-specific PI3Kγ KO mice (n = 6 per group). (p) Quantification of surface IgG-expressing memory and GC B cells, normalized to control animals, in control versus B cell-specific PI3Kγ KO mice (n = 3 for control and 5 for KO). (q-r) In-vitro generation of GC B cells using 40LB feeder cells, as in Nojima et al. 2011. Data are from two independent experiments (n = 5 for each condition). Data are presented as a bar graph (median ± SD) or box-and-whisker plots showing median, min, and max. Each dot represents different biological samples and statistical analysis was performed using non-parametric two-tailed unpaired T-tests, except for panels q-r which uses non-parametric paired T-test.

Source data

Extended Data Fig. 4 Functional PI3Kγ is required for optimal ASC differentiation in vitro and in vivo despite being dispensable for innate-like B cell IgM responses.

(a) Expression of PI3K genes in human/mouse immune cells derived from Immgen3. (b) Expression of Pik3cg in mouse B cells comparing splenic follicular and germinal center B cells to innate-like marginal zone and B1a B cells. (c-d) Mice were immunized i.p. with TI antigens and serum was taken on day 5 to measure antigen-specific IgM via ELISA. (e-f) Antigen-specific ASCs were measured from splenocytes via ELISPOT in WT mice treated as described for Fig. 4e, f. (g-h) Assessment of in-vitro differentiation of naïve mouse B cells into ASCs (anti-CD40, IL-4, IL-5 gating on CD138+ after 4 days) in utilizing B cells from Blimp1-YFP mice treated in vitro with DMSO vehicle or the PI3Kγ inhibitor IPI-549. Data are from 2-4 independent experiments. Data presented as box-and-whisker plots show median, min, and max. (c) n = 11 for controls, n = 12 for KOs. (d) n = 12 for both groups. (e) n = 15 for both groups. (f) n = 13 for both. (g-h) n = 6 for each group. Each dot represents different biological samples and statistical analysis was performed using non-parametric two-tailed unpaired T-tests, with the exception of panel H which used non-parametric paired T-test.

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Extended Data Fig. 5 PI3Kγ is required for robust human ASC differentiation.

(a-h) Cells from human tonsillar organoid model were assessed via flow cytometry (n = 5). Graphs depict percentage of each subset or percentage of live cells in each subset. (i) Assessment of in-vitro differentiation of primary healthy human peripheral blood pan-B cells into IRF4+ cells with 100 nM dose of PI3Kγi IPI-549 versus DMSO (shown as a proportion) after 5 days in the presence of DMSO control or PI3Kα activator (UCL-TRO-1938). (j-k) Overnight IPI-549 treatment of isolated primary human CD138+ ASCs from peripheral blood. ELISPOTs and quantification are from 2 independent experiments (n = 6). Each dot represents different biological samples and data are presented as mean ± SD. Statistical analysis was performed using non-parametric two-tailed unpaired T-tests and paired T-test for (i).

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Extended Data Fig. 6 Model summarizing the function of PI3Kγ in antibody responses.

B cell-intrinsic PI3Kγ supports the transition to the ASC transcriptional program and ASC differentiation in activated B cells. Diagram was created with BioRender.com.

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Patient A.1 antibody titers elicited by indicated vaccines.

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Lanahan, S.M., Yang, L., Jones, K.M. et al. PI3Kγ in B cells promotes antibody responses and generation of antibody-secreting cells. Nat Immunol (2024). https://doi.org/10.1038/s41590-024-01890-1

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