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The metabolic ER stress sensor IRE1α suppresses alternative activation of macrophages and impairs energy expenditure in obesity

Nature Immunology volume 18, pages 519–529 (2017)Cite this article

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Abstract

Obesity is associated with metabolic inflammation and endoplasmic reticulum (ER) stress, both of which promote metabolic disease progression. Adipose tissue macrophages (ATMs) are key players orchestrating metabolic inflammation, and ER stress enhances macrophage activation. However, whether ER stress pathways underlie ATM regulation of energy homeostasis remains unclear. Here, we identified inositol-requiring enzyme 1α (IRE1α) as a critical switch governing M1–M2 macrophage polarization and energy balance. Myeloid-specific IRE1α abrogation in Ern1f/f; Lyz2-Cre mice largely reversed high-fat diet (HFD)-induced M1–M2 imbalance in white adipose tissue (WAT) and blocked HFD-induced obesity, insulin resistance, hyperlipidemia and hepatic steatosis. Brown adipose tissue (BAT) activity, WAT browning and energy expenditure were significantly higher in Ern1f/f; Lyz2-Cre mice. Furthermore, IRE1α ablation augmented M2 polarization of macrophages in a cell-autonomous manner. Thus, IRE1α senses protein unfolding and metabolic and immunological states, and consequently guides ATM polarization. The macrophage IRE1α pathway drives obesity and metabolic syndrome through impairing BAT activity and WAT browning.

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Figure 1: Myeloid IRE1α abrogation protects mice from diet-induced obesity and metabolic syndrome.
Figure 2: Myeloid IRE1α ablation increases energy expenditure via enhancing brown- and beige-fat activation.
Figure 3: Myeloid IRE1α ablation augments adaptive thermogenesis.
Figure 4: Depletion of ATMs abolishes cold-induced scWAT browning.
Figure 5: IRE1α deficiency reverses the M1–M2 imbalance of ATMs.
Figure 6: Abrogation of IRE1α promotes M2 but decreases M1 polarization of macrophages.
Figure 7: IRE1α augments M2 polarization via an RNase-dependent mechanism.

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Acknowledgements

We thank S. Kajimura from UCSF for the beige preadipocytes and C. Jiang from Peking University for assistance with the macrophage depletion experiments. This work was supported by grants from the Ministry of Science and Technology (2016YFA0500100 and 973 Program 2012CB524900) and the National Natural Science Foundation of China (81420108006, 31690102 and 31230036) to Y.L.; the National Natural Science Foundation of China (31671181 and 31371153) to S.Z.D.; the National Natural Science Foundation of China (91539107) to Jianmiao Liu; and the National Natural Science Foundation of China (31671227 and 91642113) to Y.Q. This work was also supported by a research grant from the European Foundation for the Study of Diabetes/Chinese Diabetes Society/Lilly Programme to Y.L.

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Author notes

  1. Bo Shan, Xiaoxia Wang and Ying Wu: These authors contributed equally to this work.

Authors and Affiliations

  1. Key Laboratory of Nutrition and Metabolism, Institute for Nutritional Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, University of the Chinese Academy of Sciences, Shanghai, China

    Bo Shan, Xiaoxia Wang, Ying Wu, Jianli Dai, Feng Zhao, Shengqi He & Sheng-Zhong Duan

  2. Key Laboratory of Computational Biology, Chinese Academy of Sciences–Max Planck Partner Institute for Computational Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, China

    Chi Xu & Jing-Dong J Han

  3. Cellular Signaling Laboratory, Key Laboratory of Molecular Biophysics of the Ministry of Education, Huazhong University of Science and Technology, Wuhan, China

    Zhixiong Xia, Jianmiao Liu & Jianfeng Liu

  4. Department of Internal Medicine, Touchstone Diabetes Center, University of Texas Southwestern Medical Center, Dallas, Texas, USA

    Mengle Shao

  5. Hubei Key Laboratory of Cell Homeostasis, College of Life Sciences, Institute for Advanced Studies, Wuhan University, Wuhan, China

    Shengqi He, Baoliang Song & Yong Liu

  6. Department of Endocrinology and Metabolism, Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Clinical Center for Diabetes, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China

    Liu Yang, Mingliang Zhang & Weiping Jia

  7. National Center for Drug Screening, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, China

    Fajun Nan & Jia Li

  8. Institute of Molecular Medicine, Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Beijing Key Laboratory of Cardiometabolic Molecular Medicine, Peking University, Beijing, China

    Yifu Qiu

  9. Department of Molecular and Integrative Physiology, University of Michigan Medical School, Ann Arbor, Michigan, USA

    Liangyou Rui

Authors
  1. Bo Shan
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  2. Xiaoxia Wang
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Contributions

B. Shan, S.-Z.D. and Y.L. conceived and designed the studies. B. Shan, X.W. and Y.W. performed most of the experiments and analyzed the data. C.X. and J.-D.J.H. conducted the bioinformatics analysis. Z.X., J.D., M.S., S.H., F.Z., L.Y. and M.Z. performed some of the animal and cell experiments. F.N., J. Li, Jianmiao Liu, Jianfeng Liu, Y.Q., W.J., B. Song, S.-Z.D. and L.R. provided essential reagents and assisted with experimental design and data analysis. B. Shan and Y.L. wrote the manuscript.

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Correspondence to Sheng-Zhong Duan or Yong Liu.

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Integrated supplementary information

Supplementary Figure 1 Metabolic ER stress and inflammation in white adipose tissue (WAT) of mice with dietary obesity.

Male C57BL/6J mice were fed a normal chow (NC, 10% fat) or a high-fat diet (HFD, 60% fat) for 16 weeks, starting at 6 weeks of age (n=18 per group). (a) Body weight. (b) Body fat content. (c-f) Stromal vascular fraction (SVF) and adipocytes were prepared from epididymal (ep) WAT. Total RNA was extracted for quantitative RT-PCR analysis. (c,d) Xbp1 mRNA splicing and relative mRNA abundance of the indicated UPR marker genes in SVF (c) and adipocytes (d). (e,f) Relative mRNA abundance of the indicated proinflammatory genes in SVF (e) and adipocytes (f). (g,h) CD11b+ cells were isolated by magnetic MicroBeads from SVF of epWAT. Quantitative RT-PCR analysis of Xbp1 mRNA splicing and relative mRNA abundance of the indicated UPR marker and RIDD target genes (g) along with proinflammatory genes (h). Data are shown as mean ± s.e.m., *P < 0.05; **P < 0.01; ***P < 0.001 by Student’s t-test.

Supplementary Figure 2 Metabolic characterization of Ern1f/f; Lyz2-Cre mice.

(a) Immunoblot analyses of IRE1α protein in the indicated tissues of male Ern1f/f (f/f) and Ern1f/f; Lyz2-Cre (f/f:Cre) mice. (b-l) Male Ern1f/f; Lyz2-Cre mice and age-matched Ern1f/f littermates were fed an NC (n=8 per group) or HFD (n=10 per group) for 16 weeks, starting at 8 weeks of age. (b) Representative image of mice of the indicated genotype. (c) The tibia length of NC-fed mice. (d) Weight of epWAT from NC-fed mice. (e) Body weight gain of HFD-fed mice. (f) Representative images and weight of the indicated WAT from HFD-fed mice. (g) Lean mass was determined for mice fed an NC or HFD. (h) Immunoblot analyses of phosphorylation of AKT (p-AKT) at Ser473 in livers, muscle, and epWAT of HFD-fed mice after they were injected intravenously with PBS (-) or insulin (2 U/kg). (i) Liver weight was measured for NC- and HFD-fed mice. (j) Averaged daily food intake of NC- and HFD-fed mice. (k) Fecal TG content from HFD-fed mice. (l) Locomotor activity measured over a 24-h period. Results are shown as mean ± s.e.m., *P < 0.05; ***P < 0.001 by Student’s t-test or two-way ANOVA.

Supplementary Figure 3 Analysis of ATMs in NC-fed mice and ER stress in WAT of HFD-fed mice.

(a,b) SVFs of epWAT were prepared from NC-fed male Ern1f/f; Lyz2-Cre mice (n=4 per group) and their Ern1f/f littermates (n=3 per group) at 20 weeks of age. (a) Representative histograms of flow cytometry analysis of CD11b and F4/80 expression. Shown also are percentages of F4/80+CD11b+ cells. (b) Expression of CD206 in CD11b+ cells. Amounts of CD11b+CD206+ cells are quantified and shown as relative mean fluorescence intensity (MFI). (c-f) Ern1f/f; Lyz2-Cre mice (n=10 per group) and age-matched Ern1f/f littermates (n=8 per group) were fed an HFD for 16 weeks. Quantitative RT-PCR analysis of exon 2-containing Ern1 mRNA and Xbp1 mRNA splicing, along with the abundance of the indicated UPR genes in SVF (c,e) or adipocytes (d,f) from epWAT (c,d) and scWAT (e,f). Results are presented as mean ± s.e.m., *P < 0.05; **P<0.01; ***P<0.001 by Student’s t-test.

Supplementary Figure 4 Flow cytometry analysis of WAT macrophages and neutrophils.

SVFs were prepared from epWAT (a) and scWAT (b) of Ern1f/f or Ern1f/f; Lyz2-Cre mice following HFD feeding for 16 weeks (n=5 per group). CD11b+ cells were isolated with magnetic MicroBeads and then subjected to flow cytometry. Shown are representative histograms and percentages of CD45+CD11b+ cells, which were further analyzed for percentages of F4/80+CD11b+ macrophages and Ly6G+CD11b+ neutrophils.

Supplementary Figure 5 Analysis of IRE1α phosphorylation and UPR activation in LPS- or IL-4-stimulated BMDMs.

BMDMs from mice of the indicated genotype were stimulated with 100 ng/ml LPS (a,b) or 20 ng/ml IL-4 (c,d) for the indicated times (3 and 4 independent experiments, respectively). (a,c) Phos-tag gel analysis of phosphorylation of IRE1α. BMDMs treated with thapsigargin (Tg, 1 μM) for 4 hours were used as a control. Shown are representative immunoblots with two different exposure times. (b,d) Quantification of eIF2a phosphorylation and BiP protein expression from the immunoblots in Fig. 6a and 6d, respectively. Results are presented as mean ± s.e.m.

Supplementary Figure 6 Effects of IRE1α abrogation on the IL-4-induced transcriptome in BMDMs.

BMDMs from Ern1f/f or Ern1f/f; Lyz2-Cre mice were treated with IL-4 for 24 hours. Total cellular RNAs were subjected to RNA-seq analysis (2 independent experiments). (a) Heat maps showing IL-4 induction of differentially expressed genes. Pie charts indicate the percentage of IL-4-upregulated or -downregulated genes which are further enhanced, attenuated or unaltered by IRE1α ablation in the presence of IL-4 stimulation (Ern1f/f; Lyz2-Cre_Ern1f/f). Gene expression results were analyzed by two-tailed rank product non-parametric method. (b) Gene Set Enrichment Analysis (GSEA) using the KEGG database (http://www.genome.jp/kegg/) with a nominal P-value < 0.05 and false discovery rate (FDR) < 0.25. Shown are heat maps for the indicated IL-4-enhanced or -suppressed cellular function processes and signaling pathways, as aligned with those affected by IRE1α deficiency under stimulation by IL-4 (Ern1f/f; Lyz2-Cre_Ern1f/f). (c) Changes in the expression of genes encoding potential secretory proteins as a result of IRE1α deficiency. Shown are heat maps for IL-4-upregulated or -downregulated genes, as aligned with those altered in IRE1α-deficient BMDMs relative to control cells under IL-4 stimulation (Ern1f/f; Lyz2-Cre_Ern1f/f).

Supplementary Figure 7 Enforced expression of XBP1s has no effect on the mRNA abundance of M2 polarization regulators.

Mouse BMDMs were infected by control or XBP1s-expressing lentiviruses before treatment with veh. or IL-4 for 24 hours (4 independent experiments). Quantitative RT-PCR analysis of the mRNA abundance of the XBP1s target gene Erdj4 (a) and the indicated regulators of M2 polarization (b). Data are shown as mean ± s.e.m., **P < 0.01 by two-way ANOVA.

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Shan, B., Wang, X., Wu, Y. et al. The metabolic ER stress sensor IRE1α suppresses alternative activation of macrophages and impairs energy expenditure in obesity. Nat Immunol 18, 519–529 (2017). https://doi.org/10.1038/ni.3709

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