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The transcription factor RFX5 coordinates antigen-presenting function and resistance to nutrient stress in synovial macrophages

Nature Metabolism volume 4, pages 759–774 (2022)Cite this article

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Abstract

Tissue macrophages (Mϕ) are essential effector cells in rheumatoid arthritis (RA), contributing to autoimmune tissue inflammation through diverse effector functions. Their arthritogenic potential depends on their proficiency to survive in the glucose-depleted environment of the inflamed joint. Here, we identify a mechanism that links metabolic adaptation to nutrient stress with the efficacy of tissue Mϕ to activate adaptive immunity by presenting antigen to tissue-invading T cells. Specifically, Mϕ populating the rheumatoid joint produce and respond to the small cytokine CCL18, which protects against cell death induced by glucose withdrawal. Mechanistically, CCL18 induces the transcription factor RFX5 that selectively upregulates glutamate dehydrogenase 1 (GLUD1), thus enabling glutamate utilization to support energy production. In parallel, RFX5 enhances surface expression of HLA-DR molecules, promoting Mϕ-dependent expansion of antigen-specific T cells. These data place CCL18 at the top of a RFX5–GLUD1 survival pathway and couple adaptability to nutrient conditions in the tissue environment to antigen-presenting function in autoimmune tissue inflammation.

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Fig. 1: Synovial Mϕ specialize in antigen presentation.
Fig. 2: Synovial Mϕ are resistant to glucose deprivation.
Fig. 3: RA Mϕ rely on glutamate as an energy source.
Fig. 4: Synovial Mϕ are produce high levels of CCL18.
Fig. 5: CCL18-induced GLUD1 renders Mϕ resistant to nutrient stress.
Fig. 6: The CCL18-induced transcription factor RFX5 extends Mϕ lifespan.
Fig. 7: CCL18-induced RFX5 enhances HLA-DR expression and antigen presentation.

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Data availability

All data that support the findings of this study are available from the corresponding author upon reasonable request. Source data are provided with this paper.

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Acknowledgements

This work was supported by the National Institutes of Health (R01AR042527, R01AI108906, R01HL142068, and P01HL129941 to CMW and R01AI108891, R01AG045779, U19AI057266, R01AI129191 to J.J.G.) and by the Encrantz Family Discovery Fund.

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  1. These authors contributed equally: Zhaolan Hu, Tuantuan V. Zhao.

Authors and Affiliations

  1. Department of Medicine, Mayo Clinic College of Medicine and Science, Rochester, MN, USA

    Zhaolan Hu, Tuantuan V. Zhao, Tao Huang, Shozo Ohtsuki, Ke Jin, Bowen Wu, Jörg J. Goronzy & Cornelia M. Weyand

  2. Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA

    Isabel N. Goronzy

  3. Department of Orthopedic Surgery, Mayo Clinic College of Medicine and Science, Rochester, MN, USA

    Matthew P. Abdel & Jacob W. Bettencourt

  4. Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA

    Gerald J. Berry

  5. Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA

    Jörg J. Goronzy & Cornelia M. Weyand

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Contributions

Conceptualization, C.M.W., J.J.G.; Formal Analysis, Z.H., T.V.Z.; Investigation, Z.H., T.V.Z., T.H., S.O., K.J., I.N.G., B.W., G.J.B.; Clinical Samples, M.P.A., J.W.B.; Writing (original), C.M.W., Z.H., T.V.Z., I.N.G.; Supervision, C.M.W., J.J.G., G.J.B.; Funding Acquisition, C.M.W., J.J.G.

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Correspondence to Cornelia M. Weyand.

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Nature Metabolism thanks Anne Davidson, Ping-Chih Ho and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Editor recognition statement Primary handling editors: Alfredo Gimenez-Cassina and George Caputa, in collaboration with the Nature Metabolism team.

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Extended data

Extended Data Fig. 1 Characterization of synovial Mϕ.

a,b. Reanalysis of the original data from Nat Commun. 2021 Aug 17;12(1):4977 “Single-cell sequencing of immune cells from anticitrullinated peptide antibody positive and negative rheumatoid arthritis” by Wu et al. a, tSNE visualization of pooled scRNA-seq data from 71,073 CD45 + cells isolated the synovial tissue of rheumatoid arthritis patients (n = 20). We identified 21 clusters, including T cells (4 clusters), NK cells (1 cluster), B cells (3 clusters), fibroblasts (2 clusters), pericyte (1 cluster), endothelial cells (1 cluster), mast cells (1 cluster), dendritic cells (2 clusters), and macrophages (6 clusters). b, Gene transcript expression related to antigen presentation in different cell clusters. Data are shown as violin blots, and the 6 macrophage subsets are marked by a red frame.

Extended Data Fig. 2 HLA-DR and trogocytosis of synovial Mϕ.

a, HLA-DR protein expression was measured by flow cytometry in CD206 + CD163 + cells and CD206-CD163low cells isolated from low- and high-grade synovitis (n = 5). b, Identification of trogocytic Mϕ in the synovial tissue. Single cell suspensions were prepared from synovial tissues collected from RA patients. Multiparametric flow cytometry identified CD68 + Mϕ, which had integrated T cell-derived membrane fragments. Captured membrane fragments stained positive with two independent anti-CD3 antibodies (UCHT clone (clone 2) and SK7 clone (clone 1)). CD68 + CD3/UCHTI + CD3/SK7 + cells were considered trogocytic macrophages. Gating strategy and a representative dot plot overlaying CD68 + cells from a tissue with low-grade and high-grade synovitis.

Extended Data Fig. 3 Dynamics of Mϕ ingress into human synovium engrafted into NSG mice.

a–c, Human synovial tissues were implanted into NSG mice subcutaneously. Mϕ were induced from monocytes with M-CSF. After 7 days, CFSE-labelled Mϕ were mixed with autologous PBMC (1:10) and adoptively transferred into the mice. Synovial tissue grafts were harvested and digested on days 3, 5, 7 and 14 and tissue-residing macrophages were analyzed in the single cell suspensions by flow cytometry. a, Gating strategy for CFSE-labeled CD68 + cells in the tissue. b,c, Representative dot blots and frequencies of CFSE + CD68 + Mϕ were measured in the peripheral blood (n = 4), the spleen (n = 4) and the synovial tissue (n = 8) on days 3, 5, 7 and 14 after adoptive transfer. Data presented as violin blots.

Source data

Extended Data Fig. 4 Glutamate and a-KG sustain survival and mitochondrial respiration in monocyte-derived Mϕ.

a,b, Oxygen consumption rates (OCR) of monocyte-derived Mϕ generated from RA patients and healthy controls were compared by Seahorse analysis (n = 4). Basal OCR, ATP-coupled OCR and maximum respiration were measured by seahorse experiment on day 3. c,d, Mϕ from healthy controls and RA patients were kept in glucose and glutamine-free medium. Parallel cultures were supplemented with increasing doses of glutamine (0–2 mM) or glutamate (0–1 mM). Cell survival was quantified by LDH release assays on day 7 (n = 4). e,f, RA patient derived Mϕ were cultured under glucose depleted conditions and supplemented with the amino acids glutamine or glutamate or α-KG (0.5 mM). e, Metabolic activity of these Mϕ was determined by Seahorse analysis (n = 6). (f) ATP-coupled OCR was measured by seahorse experiment on day 3 (n = 4). Data are mean ± SEM. b–d, Two-tailed unpaired t test. f, One-way ANOVA with post hoc Tukey’s multiple comparisons test.

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Extended Data Fig. 5 Expression of CCL18 in synovial cell populations and ex vivo induction of CCL18 transcripts.

a, Tissue samples from low-grade and high-grade RA synovitis were digested and single cell suspensions were treated with ionomycin/PMA and LPS. After 6 hours, CCL18 protein was measured via flow cytometry. Histograms comparing the mean fluorescence intensity (MFI) for CCL18 in fibroblasts, T cells and B cells. FMO shown in light grey. b, Monocyte-derived macrophages were induced ex vivo with M-CSF over 6 days and then stimulated with different stimuli as indicated. M0 cells remained unstimulated. CCL18 transcripts were quantified by RT-PCR. Data are mean ± SEM from 4 experiments.

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Extended Data Fig. 6 CCL18 and the CCL18 target GLUD1 regulate survival of tissue-infiltrating Mϕ.

CFSE-labeled Mϕ were adoptively transferred into NSG mice that had been engrafted with human synovium. Synovial grafts were harvested after 7 days and tissue-infiltrating Mϕ were analyzed by flow cytometry. a, Chimeric mice were treated with rhCCL18 (50 μg/mouse, n = 9) or vehicle control (n = 10) for 7 days. Grafts were explanted and percentages of CFSE + Mϕ within the CD3neg cell population were measured, Data are presented as violin plots. b, Before the adoptive transfer, Mϕ were transfected with a control (n = 10), GLUD1-expressing vector (n = 9). Synovial grafts were harvested and processed for flow cytometric analysis. Percentages of CFSE + Mϕ within the CD3neg cell population were measured. Data are presented as violin plots. c, Chimeras were reconstituted with CFSE-labeled Mϕ originating from RA patients and treated with the GLUD1 inhibitor R162 (10 mg/kg, n = 12) or vehicle control (n = 12). Frequencies of CFSE + Mϕ within the CD3neg cell population were measured. Data are presented as violin plots. d–f, Proliferation indices of Mϕ isolated from the explanted human synovial tissue were determined based on CSFE dilution. Data are in box and whisker plots.

Source data

Extended Data Fig. 7 CCL18-induced upregulation of transcription factors.

MDM from healthy individuals and RA patients were induced with M-CSF over 6 days and differentiated with LPS/IFN-γ. Color scales are presented by fold change. a, Gene expression profiling for 20 transcription factors in Mϕ treated with rhCCL18 (50 ng/mL, n = 5) or vehicle (n = 5) for 48 h. Transcripts were quantified by RT-PCR. b, Gene expression of 20 transcription factors in Mϕ generated from controls and RA patients. mRNA expression was measured by RT-PCR.

Source data

Extended Data Fig. 8 Knock down efficiency for CCL18, GLUD1 and RFX5.

MDM were generated from RA patients. a,b, CCL18 was knocked down by transfecting the Mϕ with CCL18 siRNA. CCL18 protein and transcripts were quantified by FACS (a, n = 6) and qPCR (b, n = 5). c,d, To knock down GLUD1, Mϕ were transfected with GLUD1 siRNA. GLUD1 expression was quantified by immunoblot (c, n = 3) and qPCR (d, n = 4). e,f, RFX5 was knocked down by transfecting Mϕ with RFX5 siRNA. RFX5 protein and transcripts were quantified by immunoblotting (e, n = 3) and qPCR (f, n = 4). Data are mean ± SEM from 3–5 experiments in each group. Two-tailed paired t test.

Source data

Extended Data Fig. 9 Gating strategy to detect antigen-reactive CD4+ T cells.

PBMC were stimulated with Candida albicans antigen (0.05 Units/mL) for 6 days. Antigen-reactive T cells were detected by flow cytometry. a–c, Cells of interest were identified by forward versus side scatter (FSC vs SSC) based on size and granularity (a). Alive cells were identified as 7-AADnegative (b). CD4 + T cells were identified as CD3 + CD4 + cells (c). d, Antigen-reactive CD3 + CD4 + T cells were identified as CD69 + CD40L +. Frequencies in FMO, in non-stimulated cells and in antigen-stimulated cells. e, T cells were primed with antigen as in a–d and restimulated with Mϕ that were loaded with vehicle or antigen. CD3 + CD4 + CD69 + CD40L + T cells were measured after 6 hours.

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Hu, Z., Zhao, T.V., Huang, T. et al. The transcription factor RFX5 coordinates antigen-presenting function and resistance to nutrient stress in synovial macrophages. Nat Metab 4, 759–774 (2022). https://doi.org/10.1038/s42255-022-00585-x

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