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Distinct metabolic requirements regulate B cell activation and germinal center responses

Nature Immunology volume 24, pages 1358–1369 (2023)Cite this article

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Abstract

Following infection or vaccination, activated B cells at extrafollicular sites or within germinal centers (GCs) undergo vigorous clonal proliferation. Proliferating lymphocytes have been shown to undertake lactate dehydrogenase A (LDHA)-dependent aerobic glycolysis; however, the specific role of this metabolic pathway in a B cell transitioning from a naïve to a highly proliferative, activated state remains poorly defined. Here, we deleted LDHA in a stage-specific and cell-specific manner. We find that ablation of LDHA in a naïve B cell did not profoundly affect its ability to undergo a bacterial lipopolysaccharide-induced extrafollicular B cell response. On the other hand, LDHA-deleted naïve B cells had a severe defect in their capacities to form GCs and mount GC-dependent antibody responses. In addition, loss of LDHA in T cells severely compromised B cell-dependent immune responses. Strikingly, when LDHA was deleted in activated, as opposed to naïve, B cells, there were only minimal effects on the GC reaction and in the generation of high-affinity antibodies. These findings strongly suggest that naïve and activated B cells have distinct metabolic requirements that are further regulated by niche and cellular interactions.

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Fig. 1: LDHA governs aerobic glycolysis in B cells.
Fig. 2: LDHA is dispensable for lipopolysaccharide-dependent extrafollicular responses.
Fig. 3: Loss of LDHA in naïve B cells impairs germinal center responses.
Fig. 4: LDHA is required for pre-germinal center B cell proliferation.
Fig. 5: LDHA in T cells regulates germinal B cell responses.
Fig. 6: LDHA is largely dispensable for germinal center responses after B cell activation.
Fig. 7: Activated B cells do not rely on LDHA for affinity maturation.

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Data availability

All sequencing data generated in this study are deposited at the Gene Expression Omnibus under the accession code GSE232660. All custom pipelines developed for analysis of scRNA-seq data and Jh4 mutation data are available at https://github.com/ryashka/LDHA. Source data are provided with this paper.

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Acknowledgements

R.S. was supported by the National Cancer Institute (U54CA137788); J.C. was supported by grants from the National Institutes of Health (R01AI072194 and R01AI124186) and from the National Cancer Institute (U54CA137788 and P30CA008748), the Starr Cancer Research Foundation, the Ludwig Center for Cancer Immunotherapy, MSKCC Functional Genomics and the Geoffrey Beene Cancer Center. M.O.L. was supported by a grant from the National Institutes of Health R01 (AI 102888). This work was supported in part by a grant from the Tri-Institutional Metabolomics Training Program (R25 AI140472) to J.R.C. J.R.C. is also supported by the Donald B. and Catherine C. Marron Cancer Metabolism Center. We thank A. Bravo for help with maintenance of the mouse colony. We thank all members of the laboratory of J.C. for helpful discussions and feedback. We acknowledge the use of the MSKCC Single-cell Analysis Innovation Lab for the generation of the scRNA-seq dataset and the Integrated Genomic Operation Core and the Molecular Cytology Core Facility at MSKCC supported by a Core Grant (P30CA008748).

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Author notes

  1. These authors contributed equally: Ryan M Smolkin, Priyanka Chowdhury.

Authors and Affiliations

  1. Immunology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA

    Rahul Sharma, Montserrat Cols, William Alread, Wei-Feng Yen, Wei Hu, Ming O. Li & Jayanta Chaudhuri

  2. Gerstner Sloan Kettering Graduate School of Biomedical Sciences, New York, NY, USA

    Ryan M. Smolkin, Zhong-Min Wang, Ming O. Li & Jayanta Chaudhuri

  3. Immunology and Microbial Pathogenesis Program, Weill Cornell Graduate School of Medical Sciences, New York, NY, USA

    Priyanka Chowdhury, Keith Conrad Fernandez, Youngjun Kim, Ming O. Li & Jayanta Chaudhuri

  4. Donald B. and Catherine C. Marron Cancer Metabolism Center, Memorial Sloan Kettering Cancer Center, New York, NY, USA

    Sara Violante & Justin R. Cross

  5. Computational and Systems Biology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA

    Ronan Chaligné

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Contributions

R.S. and J.C. conceptualized the work, analyzed the data and wrote the manuscript; R.M.S., P.C., K.C.F., Y.K., M.C., W.-F.Y., W.H., Z.-M.W. and S.V. collected, analyzed and validated data; R.M.S. and R.C. analyzed and interpreted scRNA-seq data; R.M.S. and K.C.F. conceptualized and carried out sequencing for the SHM assay; W.A. genotyped mice and made general reagents for experiments; M.O.L. generated conditional Ldha mice; J.R.C. analyzed data on B cell metabolism.

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Correspondence to Jayanta Chaudhuri.

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

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Extended data

Extended Data Fig. 1 Confirmation of Ldha deletion in naïve B cells.

a, PCR analysis of genomic DNA from naïve splenic B cells. Two Ldhafl/flCd23Cre and two Ldha+/+Cd23Cre control mice were analyzed for the presence of the deleted (null), floxed and wild type Ldha alleles. Data is representative of 3 independent experiments. b, Naïve splenic B cells harvested from mice of the indicated genotypes (n = 2 for Ldha+/+Cd23Cre, n = 3 for Ldhafl/flCd23Cre) or splenic B cells activated with LPS + IL-4 for 48 h (n = 3 for each group) were examined for expression of Ldha by qPCR. Heart tissue harvested from Ldha+/+Cd23Cre mice (n = 1) was used as a control. c, Naïve splenic B cells were activated ex vivo with LPS + IL-4 for 72 h and whole cell protein extracts were analyzed by immunoblotting using antibodies against LDHA or α-tubulin (control). Data is representative of three independent experiments. d, Naïve and activated B cells were analyzed for expression of Ldhb by qPCR. n = 3 for each group, except n = 2 for naive Ldha+/+Cd23Cre B cells and n = 1 for heart tissue. For panels b and d, data represents mean ± s.d.

Source data

Extended Data Fig. 2 LDHA governs aerobic glycolysis in B cells.

a, Schematic representation of mito stress assays performed in a Seahorse analyzer. The mito stress assay measures the oxygen flux of cells cultured in glucose-sufficient media supplemented with glutamine and sodium pyruvate. During this assay, the oxygen consumption rate (OCR) is first measured at baseline and after the sequential addition of oligomycin (which inhibits ATP synthase and reduces OCR), FCCP (an uncoupling agent that disrupts the mitochondrial membrane potential without inhibiting the electron transport chain and allows oxygen consumption to reach a maximum), and a mixture of rotenone and antimycin A (AA) (which shuts down mitochondrial respiration). b, Representative graph of OCR of naïve B cells at baseline and following the indicated perturbations. c, Quantification of OCR and of spare respiratory capacity (SRC) of naïve splenic B cells from Ldhafl/flCd23Cre and Ldha+/+Cd23Cre (control) mice. SRC was calculated as the difference of FCCP-stimulated maximum OCR and basal OCR. d, e, Naïve splenic B cells were activated with LPS + IL4, anti-CD40 + IL4 or anti-CD40 + IL4+anti-IgM for 48 h and OCR and SRC was quantified. p values were calculated using unpaired, two-tailed t-tests. For panels b–e, n = 6 for each indicated genotype and representative of three independent experiments. Data points and bars represent mean ± s.e.m.

Source data

Extended Data Fig. 3 Cellular homeostasis in LDHA-deficient activated B cells.

a, Uptake of the fluorescent glucose analog 2-NBDG. Naïve B cells (n = 5 for each genotype) were activated ex vivo with LPS + IL4 for 48 h, incubated with 11 mM of 2-NBDG for 15 min, and 2-NBDG uptake was quantified by flow cytometry. Data is representative of two independent experiments. b, Splenic B cells from Ldhafl/flCd23Cre (n = 3) and Ldha+/+Cd23Cre (control, n = 3) mice were activated ex vivo as indicated for 48 h and intracellular ATP level was determined. Data is representative of two independent experiments. c, d, Splenic B cells from Ldhafl/flCd23Cre and Ldha+/+Cd23Cre (control) mice were labeled with Cell Trace Violet (CTV) dye, activated ex vivo for 48 h with LPS + IL4, and CTV dilution was determined by flow cytometry as a measure of cell proliferation. Data shown is representative of three independent experiments. d, Splenic B cells (1 × 106) were harvested from mice of the indicated genotypes (n = 7 for each group), stimulated with LPS + IL-4 and cell numbers were quantified at the indicated time points. e, Splenic B cells (1 × 106) harvested from mice of the indicated genotypes (n = 4 for each group) were stimulated with LPS + TGFβ + anti-IgD ex vivo and cell numbers were determined at 96 h post-activation. Data is representative of two independent experiments. Bars represent mean ± s.e.m. *p ≤ 0.05, ****p ≤ 0.0001 by unpaired, two-tailed t-test.

Source data

Extended Data Fig. 4 B cell subsets at homeostasis.

a, Representative flow plot of splenic transitional T1 (B220+CD93+CD23−IgMhi), T2 (B220+CD93+CD23+IgMhi) and T3 (B220+CD93+CD23+IgMlow) B cells. Live singlets from the spleen were first gated for B220+CD93+ cells and then gated for surface expression of IgM and CD23 as indicated. b, Quantification of T1, T2, and T3 B cells in the spleens of mice of indicated genotypes. c, Representative flow plots of B1a (B220lowCD19+CD5+) B cells in the peritoneum of mice. Live singlets from the peritoneal cavity were first gated for B220lowCD19+cells and then gated for surface expression of CD52. d, Quantification of B1a cells in the peritoneum of mice of the indicated genotypes. e, Representative flow plots of marginal zone (MZ) B cells and follicular zone (FO) B cell subsets in the spleen of mice of the indicated genotypes. Live singlets from the spleen were first gated for mature B220+CD93−B cells and then analyzed for surface expression of CD21 and CD23. f,g, Frequency and absolute number of FO B cells. h, i, Frequency and absolute number of MZ B cells. j, Frequency of CD4+ and CD8+ T cells (among live singlets) in peripheral blood and k, in the spleen of mice of the indicated genotypes. Each datapoint represents a single mouse. Bars represent mean. *p ≤ 0.05, **p ≤ 0.01, p-values were calculated using unpaired, two-tailed t-test. For panels b, d, f–k, n = 5 of each genotype and data is representative of two independent experiments.

Source data

Extended Data Fig. 5 Confirmation of Ldha deletion in CD138+ plasmablasts, marginal zone (MZ) and follicular (FO) B cells; IgM ELISA of culture supernatants of ex vivo FO and MZ B cells.

a, Gating strategy for the analysis of B220lo CD138+ cells in the spleens of mice challenged with LPS. b, Representative PCR showing the genomic deletion of the floxed Ldha exon in CD138+ plasmablasts sorted from the spleens of Ldhafl/flCd23Cre and control mice at d5 after LPS challenge. Tail DNA was used as a control to detect both the null and floxed alleles. Image of ethidium bromide-stained gel shown is representative of three independent experiments. c, Purified FO or MZ B cells of the indicated genotypes (n = 3) were cultured ex vivo for 72 h with LPS + IL4 or LPS respectively and IgM concentration in the culture supernatants was determined by ELISA. Bars represent mean ± s.e.m. d, Representative PCR depicting genomic deletion of Ldha from sorted FO and MZ B cells cultured with LPS. Image of ethidium bromide-stained gel shown is representative of three independent experiments.

Source data

Extended Data Fig. 6 Gating strategy for analysis of GC B cells following NP-CGG immunization, quantification of GC density and gating strategy for sorting of GL7+ and GL7− B cells.

a, Gating strategy for analysis of GC B cells and associated populations in the spleens of NP-CGG immunized mice. b, Mice were immunized intraperitoneally with NP-CGG, boosted at d10 and the GC density in the spleen sections from Ldha+/+ Cd23Cre (grey bar) and Ldhafl/fl Cd23Cre (red bar) mice was quantified at d14 post-immunization. Each data point represents one independent experiment in which data from the spleen sections of 3 mice per genotype were pooled. Data presented is mean ± s.e.m. c, Detection of pre-GC B cells. Wild type mice were immunized intraperitoneally with NP-CGG or with PBS and the frequency of GL7+ cells quantified at d4 post-immunization. d, Gating strategy for the sorting of GL7+ and GL7− cells from the spleens of NP-CGG immunized mice at d4 post-immunization. Sorted GL7+ and GL7− cells were mixed 3:1 and subjected to scRNA sequencing analysis. Flow cytometry of the post-sort cells is shown.

Source data

Extended Data Fig. 7 LDHA in T cells regulates GC B cell responses.

Ldhafl/fl and Ldhafl/flCd4Cre mice were immunized intraperitoneally with NP-CGG, boosted at d10, and analyzed at d14. a, Immunofluorescence staining of frozen spleen sections harvested at d14. Image is representative of n = 3 mice per genotype. Scale bar represents 50 μm. b–e, Splenic B cells (5 × 105) from wild type mice were co-cultured with TFH cells (3 × 105) purified from Ldhafl/flCd4Cre (n = 2 pooled samples) or Ldhafl/fl (n = 2 pooled samples) control mice. The cells were analyzed at d6 post initiation of culture. b, c, Number of B and TFH cells at d6. d, e, Antibody titers of IgM and IgG1 in culture supernatant. *p ≤ 0.05, by unpaired, two-tailed t-test. Data represents two biological samples, each pooled from 4 mice per genotype. Bars represent either mean ± s.e.m (panels b, c, and e) or mean ± s.d. (panel d).

Source data

Extended Data Fig. 8 LDHA in T cells is dispensable for LPS-dependent extrafollicular responses.

The spleen of Ldhafl/flCd4Cre (n = 8) and Ldhafl/fl (control, n = 7) mice were analyzed at d5 after LPS administration. a, Staining of Ki67 in activated (GL7+) and unactivated (GL7−) B cells in mice of indicated genotypes. b, mTORC1 activity was quantified from the frequency of phosphorylated S6 (p-S6) positive cells in activated (GL7+) B cells. c, Frequency of CD4+ and CD8+ T cells among live singlets. d, Ki67 staining of CD4+ and CD8+ T cells. e, Quantification of naïve (CD62LhiCD44lo), central memory (CD62LhiCD44hi) and effector (CD62LloCD44hi) CD4+ and CD8+ T cells at d5 post-LPS challenge. Data is representative of three independent experiments. Bars represent mean ± s.e.m.

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Extended Data Fig. 9 Ldhafl/flAicdaCre/+ mice can mount a robust GC response.

Ldhafl/flAicdaCre/+ and Ldha+/+AicdaCre/+ (control) mice were immunized intraperitoneally with NP-CGG, boosted at d10, and analyzed at d14. a, Viability of GC B cells as measured by cells negative for Zombie Red viability dye. b, Cell size of viable GC B cells as measured by quantifying the MFI of forward scatter (FSA). c, Mitochondrial mass was quantified by measuring the MFI of MitoTracker™ Green FM Dye among the GC and non-GC B cells. d, Frequency of dysfunctional mitochondria was measured by quantifying the fraction of live GC and non-GC B cells negative for MitoTracker™ Red CMXRos. e, PCR of genomic DNA of GC and non-GC B cells sorted from spleens of mice of the indicated genotypes. f, Immunoblotting of whole cell extracts prepared from GC and non-GC B cells sorted from the Peyer’s patches and spleens of mice of the indicated genotypes to detect LDHA and α-tubulin (control) proteins. g, Expression of Ldha and Ldhb in sorted GC B cells. Bars represent mean. Each datapoint represents a single mouse (n = 3). The box plot depicts the first quartile, third quartile, and the median of the dataset. Values that fall within 1.5 times the interquartile range above the third quartile and below the first quartile are represented by the whiskers. The gating strategy for the sorting of GC B cells is the same as that in Extended Data Fig. 6a. For panels a and b, n = 8 for each genotype; data is representative of two independent experiments. For panels c and d, n = 5 for each genotype and data is representative of two independent experiments. For panels e, and f, data is representative of 2 independent experiments with 3 to 5 mice per experiment.

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Extended Data Fig. 10 Working model depicting metabolic requirements in naïve and in activated B cells.

Proposed model suggesting different metabolic constraints in B cells committed to either a T-dependent or a T-independent pathway for an optimal humoral response. LDHA-mediated glycolysis is essential for the early activation of B cells during a T-dependent GC response but is largely dispensable once the activated B cells are fully engaged in a GC reaction ('>' sign symbolizes 'greater than'). On the other hand, a T-independent extrafollicular response is not reliant on LDHA-mediated glycolysis.

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Supplementary Information

Supplementary Table 1: Antibody catalog numbers

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Sharma, R., Smolkin, R.M., Chowdhury, P. et al. Distinct metabolic requirements regulate B cell activation and germinal center responses. Nat Immunol 24, 1358–1369 (2023). https://doi.org/10.1038/s41590-023-01540-y

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