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pH sensing controls tissue inflammation by modulating cellular metabolism and endo-lysosomal function of immune cells

Nature Immunology volume 23, pages 1063–1075 (2022)Cite this article

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Abstract

Extracellular acidification occurs in inflamed tissue and the tumor microenvironment; however, a systematic study on how pH sensing contributes to tissue homeostasis is lacking. In the present study, we examine cell type-specific roles of the pH sensor G protein-coupled receptor 65 (GPR65) and its inflammatory disease-associated Ile231Leu-coding variant in inflammation control. GPR65 Ile231Leu knock-in mice are highly susceptible to both bacterial infection-induced and T cell-driven colitis. Mechanistically, GPR65 Ile231Leu elicits a cytokine imbalance through impaired helper type 17 T cell (TH17 cell) and TH22 cell differentiation and interleukin (IL)-22 production in association with altered cellular metabolism controlled through the cAMP–CREB–DGAT1 axis. In dendritic cells, GPR65 Ile231Leu elevates IL-12 and IL-23 release at acidic pH and alters endo-lysosomal fusion and degradation capacity, resulting in enhanced antigen presentation. The present study highlights GPR65 Ile231Leu as a multistep risk factor in intestinal inflammation and illuminates a mechanism by which pH sensing controls inflammatory circuits and tissue homeostasis.

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Fig. 1: GPR65 Ile231Leu exacerbates bacterial infection-induced colitis.
Fig. 2: GPR65 Ile231Leu affects TH17 and TH22 cell polarization and pH-dependent release of IL-22.
Fig. 3: ScRNA-seq reveals cellular metabolism changes in Gpr65-null TH17 and TH22 cells.
Fig. 4: Fatty acid composition and TAG storage changes in Gpr65-null TH17 and TH22 cells.
Fig. 5: GPR65 Ile231Leu modulates TH17 cell differentiation through the cAMP–CREB–DGAT1 axis.
Fig. 6: GPR65 Ile231Leu promotes T cell-driven colitis with elevated inflammatory cytokine release.
Fig. 7: GPR65 Ile231Leu enhances antigen presentation in dendritic cells by influencing endo-lysosomal fusion and degradation capacity.

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Data availability

The scRNA-seq data generated during the present study are available under Gene Expression Omnibus accession no. GSE182767. The reference mm10 mouse transcriptome was obtained from GENCODE: GCF_000001635.26. Source data are provided with this paper.

Code availability

Code used for the present study is available at https://gitlab.com/xavier-lab-computation/public/gpr65-scrnaseq.

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Acknowledgements

We thank T. Reimels for assistance with editing. This work was supported by funding from the National Institutes of Health (grant nos. R01 DK117263, RC2 DK114784, U19 AI109725 and U19 AI142784 to R.J.X.) and the Helmsley Charitable Trust (to R.J.X.).

Author information

Authors and Affiliations

  1. Broad Institute of MIT and Harvard, Cambridge, MA, USA

    Xiangjun Chen, Alok Jaiswal, Zachary Costliow, Elizabeth A. Creasey, Noriko Oshiro-Rapley, Mark J. Daly, Kimberly L. Carey, Daniel B. Graham & Ramnik J. Xavier

  2. Center for Computational and Integrative Biology, Massachusetts General Hospital, Boston, MA, USA

    Xiangjun Chen, Paula Herbst, Elizabeth A. Creasey, Noriko Oshiro-Rapley, Daniel B. Graham & Ramnik J. Xavier

  3. Department of Molecular Biology, Massachusetts General Hospital, Boston, MA, USA

    Xiangjun Chen, Paula Herbst, Elizabeth A. Creasey, Noriko Oshiro-Rapley, Daniel B. Graham & Ramnik J. Xavier

  4. Experimental Medicine Unit, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA

    Xiangjun Chen, Noriko Oshiro-Rapley & Daniel B. Graham

  5. Analytic and Translational Genetics Unit, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA

    Mark J. Daly

  6. Institute for Molecular Medicine Finland, Helsinki, Finland

    Mark J. Daly

  7. Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, USA

    Daniel B. Graham & Ramnik J. Xavier

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Contributions

R.J.X. and X.C. conceived of the study. X.C. designed and conducted most of the experiments. A.J. analyzed the scRNA-seq data. Z.C. performed the lipidomic and metabolomic experiments. P.H. and E.A.C. helped with the mouse experiments. N.O.-R. helped with immunoblotting. M.J.D. helped with genetics. X.C. wrote the manuscript. A.J., M.J.D., K.L.C., D.B.G. and R.J.X. revised the manuscript. K.L.C., D.B.G. and R.J.X. supervised the research.

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Correspondence to Ramnik J. Xavier.

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Competing interests

R.J.X. is co-founder of Jnana Therapeutics and Celsius Therapeutics and M.J.D. is a scientific founder of Maze Therapeutics. These organizations played no role in the present study. The remaining authors declare no competing interests.

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Extended data

Extended Data Fig. 1 GPR65 I231L mice generated by CRISPR-Cas9 have no evident colitis-related phenotypes at steady state.

(a) Design of GPR65 I231L knock-in by the CRISPR-Cas9 system. Gpr65 gene sequence from NCBI database is shown with annotated sgRNA target sequences and protospacer adjacent motif (PAM) and mutation sites. Mutated alleles are highlighted. (b) Alignment of the sequencing data of WT and I231L mice. Mutated alleles are highlighted. (c) Gating strategy of immune populations in the small intestinal lamina propria. (d,e) Statistical analysis of immune populations in the small intestinal lamina propria (SI LP) and colonic lamina propria (Co LP) of WT (n = 3) and I231L (n = 3) mice. Data are mean values. P values determined by unpaired two-tailed t-test; ns, not significant.

Source data

Extended Data Fig. 2 GPR65 I231L mice are more susceptible to bacterial infection-induced colitis.

(a,b) Colony forming units (CFU) in the stool (a) and body weight changes (b) of mice during C. rodentium infection. nWT = 6; nI231L = 7; nKO = 6 mice. (c) H&E-stained sections of distal colon from mice on day 3 after Citrobacter infection. Representative images from one of two independent experiments. Scale bar, 0.5 mm. (d) Statistical analysis of myeloid and CD4+ T cells in the colonic LP on day 12 after C. rodentium infection. nWT = 6; nI231L = 7; nKO = 6 mice. (e) Cytokine-producing CD4+ T cells in the mLN from WT (n = 6), I231L (n = 6) and KO (n = 6) mice on day 12 after infection. (f,g) Cytokine profiles of colonic tissue from C. rodentium-infected mice detected by qPCR (f) and multiplex bead-based cytokine assay (g). n = 4 mice per genotype (f); nWT = 6; nI231L = 7; nKO = 6 mice (g). (h-j) CFU, body weight change and colonic H&E histology of WT (n = 7), I231L (n = 7) or KO (n = 7) CD4+ T cell-transferred mice after Citrobacter infection. CFUs in colonic tissue and H&E staining were performed on day 12. (k,l) Immunophenotyping of CD4+ T cells and inflammatory innate immune cells in the mLN or colonic LP on day 12 after infection. n = 7 mice per genotype. (m) Cytokine profiles of colonic tissue on day 12 were detected by qPCR. n = 4 mice per genotype. Scale bar, 0.5 mm (c,j). Data represent at least two independent experiments. Data are mean values (a,b,d-i,k-m) + SEM (a,b,h,i). P values determined by unpaired two-tailed t-test; ns, not significant.

Source data

Extended Data Fig. 3 GPR65 regulates Th17 differentiation.

(a) Flow profiles of cell viability of CD4+ T cells after 48 h and 72 h of ex vivo culturing without stimulation. (b) Flow profiles of divided CD4+ T cells after 48 h and 72 h of stimulation with anti-CD3/CD28 dynabeads. (c) In vitro polarization of different Th cells (Th1, Th2, non-pathogenic Th17, pathogenic Th17) and induced Tregs. (d) Cytokine responses to different pH stimulation in Th22 cells polarized in vitro. Intracellular cytokine staining and qPCR were performed after restimulation of resting day 3-polarized Th22 cells by anti-CD3ε and anti-CD28 antibodies for 24 h. (e) Il17a and Rorc expression in polarized Th17 cells and Il22 and Ahr expression in polarized Th22 cells detected by qPCR. Data are mean values (c-e). n = 4 biological replicates for each group (c-e). P values determined by unpaired two-tailed t-test; ns, not significant. Data represent at least two independent experiments.

Source data

Extended Data Fig. 4 Single-cell RNA-seq profiling in in vitro polarized Th17 and Th22 cells.

(a,b) UMAP embeddings of single-cell RNA-sequencing profiles from in vitro polarized Th17 and Th22 cells (a). Expression of differential genes across cells reveals the features of different clusters (b). (c) Enrichment of gene ontology metabolic signature scores in cluster 2 single-cell transcriptomes for Th17 and Th22 cells. (d) Flux balance analysis to predict activity of various metabolic processes. Dots denote single biochemical reactions in different metabolisms, and only core biochemical reactions are shown.

Extended Data Fig. 5 Differential expression of genes related to metabolic pathways.

(a) Volcano plots show differential expression of genes related to oxidative phosphorylation (HALLMARK_OXIDATIVE_PHOSPHORYLATION), glycolysis (HALLMARK_GLYCOLYSIS), ATP metabolic process (GO_ATP_METABOLIC_PROCESS) and cellular amide metabolic process (GO_CELLULAR_AMIDE_METABOLIC_PROCESS) in polarized Th17 and Th22 cells (KO versus WT). (b) Dot plot shows the differential expression of genes related to different metabolic processes in all single-cell transcriptomes. (c) qPCR validation of differential gene expression in I231L Th17 and Th22 cells. Data are mean values from two independent experiments. n = 4 biological replicates for each group. P values determined by unpaired two-tailed t-test; ns, not significant.

Source data

Extended Data Fig. 6 Metabolomics analysis in polarized Th17 and Th22 cells.

Heatmap shows all 160 lipid metabolites detected in lipidomics.

Source data

Extended Data Fig. 7 GPR65 I231L exacerbates T cell-driven colitis.

(a) Body weight changes of Rag1 KO mice after transfer of Gpr65 WT, I231L or KO (n = 6 per genotype) CD45RBhigh CD4+ T cells. (b) Colon length of mice (n = 6 per genotype) in (a) after colitis induction. (c) H&E-stained sections of distal colon from mice with T cell-driven colitis. Representative images from one of two independent experiments. Scale bar, 0.5 mm. (d) Proportion analysis of cytokine-producing CD4+ T cells in the mLN and colonic LP of mice (n = 6 per genotype) in (a) after colitis induction. (e) Cytokine profiles (IFNγ, IL-17A, IL-22) of colonic tissue from mice (n = 4 per genotype) with colitis detected by multiplex bead-based cytokine assay. (f) Cytokine profiles (IFNγ, IL-17A, IL-22) of colonic tissue from mice (n = 4 per genotype) with T cell-driven colitis detected by qPCR. One dot denotes one biological replicate (b,d-f). (g) Gating strategy of immune populations in the colonic LP. Data are mean values (a,b,d-f) + SEM (a). P values determined by unpaired two-tailed t-test; ns, not significant. Data represent at least two independent experiments.

Source data

Extended Data Fig. 8 GPR65 I231L enhances antigen presentation to CD4+ T cells by dendritic cells.

(a,b) BMDC:OT-II T cell co-culturing-based antigen presentation assay. Cell numbers of OT-II CD4+ T cells (a) and IL-2 cytokine in the culture supernatant (b) on day 3 after co-culturing are shown. n = 5 (WT), n = 3 (I231L) and n = 2 (KO) biological replicates (a); n = 4 for each group (b). (c,d) BMDCs incubated with both DQ-Red BSA and AF647-BSA with or without treatment. Cells were treated with LPS (20 ng/ml) for 2 h and then incubated with DQ-Red BSA (3 μg/ml) and AF647-BSA (3 μg/ml) for 1 h before imaging. Representative images from one of two independent experiments are shown (c). Scale bar, 10μm. Statistical analysis of the ratio of DQ-Red BSA and AF647 fluorescence intensity (d). nWT = 39, nI231L = 28, nKO = 24 (NT); nWT = 27, nI231L = 20, nKO = 20 (LPS); nWT = 26, nI231L = 19, nKO = 20 (LPS + pH6.8); nWT = 21, nI231L = 18, nKO = 14 (Baf A1) cells. Data are mean values (a,b,d) + SEM (a,b). P values determined by unpaired two-tailed t-test; ns, not significant. Data represent at least two independent experiments.

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Chen, X., Jaiswal, A., Costliow, Z. et al. pH sensing controls tissue inflammation by modulating cellular metabolism and endo-lysosomal function of immune cells. Nat Immunol 23, 1063–1075 (2022). https://doi.org/10.1038/s41590-022-01231-0

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