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Lymphocyte-derived cholinergic circuits modulate germinal center output and B cell activation

Nature Immunology (2026)Cite this article

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Abstract

Germinal centers (GCs) are specialized lymphoid structures in which activated B cells undergo clonal selection and B cell receptor (BCR) somatic hypermutation to generate high-affinity antibodies. Previous work has shown that T cells expressing choline acetyltransferase (ChAT), the enzyme that synthesizes acetylcholine (ACh), are linked to the production of high-affinity antibodies in the GC response. However, whether B cells in the GC also express ChAT, and the details of the interplay of cholinergic circuits within the GC, remain unclear. Here we show that Chat expressed by GC B cells contributes to the early accumulation of high-affinity GC B cells following antigen encounter. We identify key transcriptional regulators of Chat expression in GC B cells and demonstrate that ACh receptor (AChR) expression is dynamically coordinated during B cell activation. In vitro, we show that ACh binding to muscarinic AChRs limits plasma cell differentiation and dampens BCR signal transduction to fine-tune the threshold for affinity-based positive selection. Together, these findings reveal a previously unrecognized regulatory axis that operates early during GC selection and uses cholinergic signals to shape B cell fate decisions and humoral immunity.

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Fig. 1: Chat is expressed by GC B cells and TFH cells and supports higher-affinity GC B cell accumulation.
Fig. 2: Loss of ChAT influences B cell fate decisions and alters affinity maturation.
Fig. 3: Chat is induced in positively selected GC B cells.
Fig. 4: Chat expression identifies an activated TFH cell subset.
Fig. 5: Expression of AChRs is coordinated during B cell activation, and mAChR activity limits B cell differentiation.
Fig. 6: ACh reduces BCR signal transduction and sets a threshold for selection of GC B cells.

Data availability

RNA sequencing data have been deposited in the Gene Expression Omnibus under accession number GSE316392; BCR repertoire sequencing data have similarly been deposited under accession number GSE315161. Source data are provided with this paper.

Code availability

The algorithms used for statistical analysis using existing software packages have been previously reported and are outlined in the Methods. No custom algorithms were developed for this study.

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Acknowledgements

We wish to thank R. Brink (Garvan Institute, Australia) for graciously providing the SWHEL mouse line. We also thank the Princess Margaret Genomics Centre and the UHN Bioinformatics and HPC Core for RNA sequencing; CD Genomics for BCR repertoire sequencing; and R. Harrietha, K. T. Gill and the Genotyping Facility and the Animal Resource Centre at the Princess Margaret Cancer Centre (Toronto) for support with animal breeding and genotyping. We are grateful to P. Kubes (University of Calgary, Canada) for supportive feedback. We additionally thank L. D. Hendrikse for his insights and assistance with data organization and the preparation of datasets for public repository submission. This work was supported by grants to T.W.M. from the Canadian Institutes of Health Research (CIHR application 470754), Ottawa, Canada, and from the Centre for Oncology and Immunology under the Health@InnoHK Initiative funded by the Innovation and Technology Commission, The Government of Hong Kong SAR, China.

Author information

Author notes

  1. These authors contributed equally: Duygu Nechanitzky, Logan K. Smith, Robert Nechanitzky.

Authors and Affiliations

  1. Princess Margaret Cancer Centre, Ontario Cancer Institute, University Health Network, Toronto, Ontario, Canada

    Duygu Nechanitzky, Logan K. Smith, Robert Nechanitzky, Soode Moghadas Jafari, Jillian Haight, Parameswaran Ramachandran, Matthew J. Gold, Andrew C. Wakeham, Mary E. Saunders & Tak W. Mak

  2. Department of Microbiology, Immunology, and Infectious Diseases, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada

    Robert Nechanitzky

  3. Zymeworks BC Inc., Vancouver, British Columbia, Canada

    Robert Nechanitzky

  4. Department of Pathology, Cancer University Institute of Toulouse-Oncopole, University Hospital of Toulouse, University of Toulouse III Paul Sabatier, INSERM U1037, Cancer Research Center in Toulouse, Toulouse, France

    Christophe Bontoux

  5. Department of Physiology and Pharmacology, University of Calgary, Calgary, Alberta, Canada

    Justin F. Deniset

  6. Departments of Immunology and Medical Biophysics, University of Toronto, Toronto, Ontario, Canada

    Tak W. Mak

  7. Department of Pathology School of Clinical Medicine, Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong, China

    Tak W. Mak

  8. Centre for Oncology and Immunology, Hong Kong Science Park, Hong Kong, China

    Tak W. Mak

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Contributions

D.N., L.K.S. and R.N. conceived the study. D.N., L.K.S., R.N. and M.E.S. wrote the manuscript. D.N., L.K.S. and R.N. designed experiments and analyzed data. D.N., L.K.S., R.N., S.J., C.B. and M.G. performed experiments with support from J.H., J.D. and A.C.W. P.R. performed RNA sequencing bioinformatic analyses. T.W.M. and R.N. supervised the research. All authors reviewed and approved the manuscript.

Corresponding author

Correspondence to Tak W. Mak.

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Competing interests

R.N. is employed by Zymeworks BC. M.G. is employed by Providence Therapeutics Holdings. T.W.M. owns equity in Treadwell Therapeutics and Agios Pharmaceuticals, and is a consultant for AstraZeneca and Tessa Therapeutics. The other authors declare no competing interests.

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Extended data

Extended Data Table 1 List of antibodies used for flow cytometry and functional analysis
Full size table
Extended Data Table 2 List of primer oligo sequences used for qPCR analysis
Full size table

Extended Data Fig. 1 Phenotyping of Chat expression dynamics during the GC reaction following SRBC immunization; related to Fig. 1.

a Representative flow cytometry plots and quantification of Chat-GFP+ cells among splenic populations from Chat-GFP mice at steady-state or day 5 post-SRBC immunization; N = 10. b Proportions of GFP+ cells derived from indicated cell types at steady-state and day 5-post SRBC immunization. B cells (CD45+CD19+); T cells (CD45+CD19−CD3+); plasmablasts (PB) (CD45+CD19−CD3−CD138+); NK cells (CD45+CD19−CD3−CD138−NK1.1+); N = 6. c Representative gating strategy and summary statistics of splenic B cell populations in Chat-GFP mice; N = 12. d Representative gating strategy and summary statistics of splenic T cell populations in Chat-GFP mice; N = 12. e Left: Representative SRBC binding to GC B cells at day 6 post-immunization. Right: SRBC gMFI of GC B cells across all time points in Fig. 1a. Matched samples are connected; N = 43. f Fold change in SRBC-binding gMFI of GC B cells in Extended Data Fig.1e. Matched samples are connected; N = 43. g Dark zone (DZ) to Light zone (LZ) GC B cell ratio (DZ:CD86lo, CXCR4hi; LZ: CD86hi, CXCR4lo) among the Chat-GFP+ GC B cells in Fig. 1a; N ≥ 10. h Frequency of Tfh cells among total splenic CD4+ T cells Chat-GFP mice post-SRBC immunization, as indicated; N ≥ 10. i Frequency of Chat-GFP+ Tfh cells among Tfh cells in Extended data Fig. 1g; N ≥ 10. j Gating strategy used to define B cells within the bone marrow. k Frequency of indicated B cell populations in Chatflox/flox and Chatflfl Mb1-cre+ mice at steady-state. l Frequency of higher affinity splenic GC B cells at day 10 post-SRBC immunization; N = 12. m Frequency of IgG- or IgM-expressing higher affinity GC B cells at day 10 post-SRBC immunization; N = 12. Data were collected over at least two independent experiments, where are the mean ± SEM. P values of *<0.05, **<0.01, ***<0.001, and ****<0.0001 were determined for Extended data Fig. 1c, d and j by two-sided Mann-Whitney test; for Extended data Fig.1f, g and h by Kruskal-Wallis test with Dunn’s multiple comparison test; for Extended data Fig. 1e by two-sided Wilcoxon matched-pairs test; for Extended data Fig. 1k and l by two-sided Mann-Whitney test relative to Chat flox/flox WT. Exact P values are reported in the Source Data.

Source data

Extended Data Fig. 2 Loss of ChAT influences GC dynamics; related to Fig. 2.

a Representative flow cytometry plots showing pre-plasmablast GC B cells in spleens of mice at day 5 post-immunization with either HEL-SRBC (top) or DEL-SRBC (bottom). Plots were gated on single/viable/B220+ B cells/CD95+IgD− GC B cells/CD45.1+ SWHEL B cells. Pre-plasmablasts defined as CD138+ and IRF4+. b Frequency of pre-plasmablast SWHEL GC B cells; N = 6. c Frequency of pre-memory SWHEL GC B cells (CD138−CCR6+ GC B cells) in the mice in Extended data Fig. 2a; N = 9. d Representative flow cytometry plots showing IgM and IgG expression on the SWHEL GC B cells at day 5 post-immunization with HEL or DEL. e Proportions of IgG- or IgM-expressing SWHEL GC B cells; N = 9. f Quantitation of DEL-specific serum IgM and IgG1 in Fig. 2d and g, using the upper asymptote of the fitted 4PL curves as a measure of antibody abundance; N = 6. g Germline SWHEL heavy chain reference sequence (FR1-CDR3), with annotated CDRs. h Sequence divergence of the SWHEL reads defined as % amino acid mismatch across the sequence coverage, as a measure of total mutational burden N ≥ 173. i Top3 fraction analysis of SHM hotspots with CDR2, calculated as the frequency of mutations occurring at the three most mutated positions, reflecting the focusing of mutations onto hotspot positions; N ≥ 2. j CDR2 entropy values describing the bredth of mutations within the CDR2. Lower entropy reflects focused hotspot targeting, while higher entropy indicates diffuse SHM; N ≥ 2. k Minimum distance to the dominant mutation hotspot (epicenter), quantifying the clustering of mutations. Lower values indicate SHM more tightly clustered around the dominant peak; N ≥ 173. l Frequency of S52N/R mutations within the CDR2 regions of the SWHEL reads in G according to genotype, as indicated; N ≥ 2. Data were collected over at least two independent experiments. Data in Extended data Fig. 2i and j reflect sample-level quantifications and were analyzed by two-sided unpaired T tests. Data are the mean ± SEM. n.d. denotes “not detected”. P values of *<0.05, **<0.01, ***<0.001, and ****<0.0001 were determined for remaining comparisons by Mann-Whitney test; statistics are reported relative to ChATflox/flox WT control. Exact P values are reported in the Source Data.

Source data

Extended Data Fig. 3 Chat-GFP expressing cells in the GC are functionally distinct; related to Fig. 3.

a qPCR validation of mRNA levels of the indicated genes in the Tfh cells examined in the RNAseq analysis in Fig. 3b. Relevant genes were chosen from the list of significantly upregulated DEGs (adjusted p-value > 0.05) based on relevance to GC biology rather than highest rank fold change; N = 4. b qPCR validation of mRNA levels of the indicated genes in GC B cells examined in the RNAseq analysis in Fig. 3a. Relevant genes were selected as in Extended data Fig.3a; N = 4. c Left: Representative flow cytometry plot of CD36 expression on GC B cells of Chat-GFP mice at day 10 post-immunization with SRBCs. Plots were gated on single cells/viable cells/B220+ B cells/CD95+CD38− GC B cells/Chat-GFP+ or Chat-GFP−. Right: Summary statistics showing gMFI of CD36 on GC B cells pooled from mice at days 6 and 10 post-immunization; N = 12. d Left: Representative flow cytometry plot of OX40L expression on GC B cells of Chat-GFP. Right: Summary statistics showing gMFI of OX40L on GC B cells pooled from mice at days 6 and 10 post-immunization; N = 12. e Dose-response curve to detect ACh standards using ACh GFP-reporter cells (see Methods). f Summary statistics showing the change in Chat-GFP induction in B cells that were treated in vitro with the NFκB inhibitors NIK-SM1 or IMD-0354, and then stimulated with the indicated agents. Values shown were normalized to “no inhibitor” (vehicle control). Statistics were calculated against the vehicle control; N = 7. g Left: Representative flow cytometry plots showing Chat-GFP expression gated on CD45.1+ SWHEL B cells following adoptive transfer into WT mice at day 5 post immunization with HEL- or DEL-conjugated SRBCs. Right: Summary statistics; N = 6. Data were collected over two independent experiments, data are the mean ± SEM. P values of *<0.05, **<0.01, ***<0.001, and ****<0.0001 were determined for Extended data Fig. 3a – b and f by two-sided paired T tests; for Extended data Fig. 3c-d by two-sided Wilcoxon matched-pairs test; for Extended data Fig. 3g by Mann-Whitney; n.s., not significant. Exact P values are reported in the Source Data.

Source data

Extended Data Fig. 4 Phenotypic features of Chat-GFP+ Tfh cells; related to Fig. 4.

a GSEA analysis revealing enrichment for ChAT-dependent hallmark pathways in the Tfh cells in Fig. 3b. b Left: Representative flow cytometry plots of GL7+ cells, gated on Chat-GFP+ and Chat-GFP− Tfh cells at day 5 post-SRBC immunization. Right: Summary statistics; N = 10. c Representative flow cytometry plots of cytokine production by the Tfh cells in Fig. 4b. d Representative flow cytometry plots of Chat-GFP expression in isolated Tfh cells cultured in vitro for 16 h with either no stimulus or the indicated stimuli as in Fig. 4g. Data in Extended data Fig.4b are the mean ± SEM. P value of ****<0.0001 was determined by two-sided Wilcoxon matched-pairs test. Exact P values are reported in the Source Data.

Source data

Extended Data Fig. 5 AChR expression is coordinated during B cell activation; related to Fig. 5.

a Representative flow cytometry plots showing the gating strategy (top), and expression (bottom left panels), of the M2 and M4 mAChRs on the indicated B cell populations from WT mice at day 10 post-SRBC immunization. Plots were gated on single cells/viable cells/B220+ B cells, with non-GC B cells then subdivided into activated cells (CD86+CD95+) and naïve cells (CD86−CD95−). Bottom right panels: Summary statistics for M2 and M4 gMFI; N = 11. b Representative flow cytometry plots of protein expression of the indicated AChRs on GC B cells from the WT mice in Fig. 5d at days 5 and 10 post-SRBC immunization. c Summary statistics showing gMFI of expression of CD138 on the activated B cells in Fig. 5e. Statistics are reported relative to unstimulated cells; N = 6. d Summary statistics showing levels of secreted IgM in culture supernatants of the activated B cells in Fig. 5e. Statistics are reported relative to unstimulated cells; N = 6. e qPCR determination of the relative induction of Aicda in the B cells cultured and treated as in Fig. 5e; N = 4. f Flow cytometric determination of Ca2+ mobilization in WT splenic B cells that were activated in vitro for 48 h with 1 μg/mL α-IgM and loaded with Indo-I. Cells were then stimulated with ACh (10 mM) as indicated; N = 13. g Left: Representative flow cytometry plot showing p-CREB expression on GC B cells isolated from WT mice at day 6 post-SRBC immunization. Plot was gated on single cells/viable cells/B220+ B cells. Right: Summary statistics of p-CREB expression on GC B cells from mice of the indicated genotypes at day 6 post-SRBC immunization; N = 10. Data are the mean ± SEM. P values of *<0.05, **<0.01, ***<0.001, and ****<0.0001 were determined for Extended Data Fig. 5a by Friedman test with Dunn’s multiple comparison test; for Extended Data Fig. 5c-e by RM-ANOVA with Dunnett’s multiple comparison test reported relative to Unstim.; and for Extended Data Fig.5g by two-sided Mann-Whitney test, relative to Chat flox/flox WT control. Exact P values are reported in the Source Data.

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Extended Data Fig. 6 Acetylcholine modulates the threshold for GC B cell selection; related to Fig. 6.

a Left: Representative flow cytometry plots of total tyrosine phosphorylation (p-Tyr) in B cells that were isolated from spleens of WT mice, activated for 48 h in vitro. Cells were then treated (or not) with the indicated AChR inhibitors, with or without 10 mM ACh, and restimulated with 1 μg/mL α-IgM F(ab’)2 (BCR crosslinking) for 90 seconds. Right: Summary statistics showing gMFI of p-Tyr in the left panel, reported relative to unstimulated control cells; N = 8. b Representative flow cytometry plots of c-MYC expression on GC B cells that were isolated from spleens of WT mice and cultured for 24 h with 0.5 mM or 5 mM ACh, and then stimulated for 24 h with serial dilutions of a cocktail containing α-IgM, α-CD40, IL-21 and IL-4. Plots were gated on single cells/viable cells/B220+ B cells/CD95+CD38− GC B cells/activated caspase-3− cells before determining c-MYC expression. c Left: Proportion of activated caspase-3+ GC B cells among the B cells in B after 24 h in culture. Right: EC50 of the fitted dose-response curve in the left panel; N = 6. Data are representative of at least 2 experiments, where data are the mean ± SEM. P values of **< 0.01, ***< 0.001 and ****< 0.0001 were determined for Extended data Fig. 6a by Friedman test with Dunn’s multiple comparison test, and for Extended data Fig. 6c by two-sided Wilcoxon matched pairs test relative to 0 mM control. Exact P values are reported in the Source Data.

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Nechanitzky, D., Smith, L.K., Nechanitzky, R. et al. Lymphocyte-derived cholinergic circuits modulate germinal center output and B cell activation. Nat Immunol (2026). https://doi.org/10.1038/s41590-026-02444-3

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