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Neuro-mesenchymal units control ILC2 and obesity via a brain–adipose circuit

Nature volume 597, pages 410–414 (2021)Cite this article

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Abstract

Signals from sympathetic neurons and immune cells regulate adipocytes and thereby contribute to fat tissue biology. Interactions between the nervous and immune systems have recently emerged as important regulators of host defence and inflammation1,2,3,4. Nevertheless, it is unclear whether neuronal and immune cells co-operate in brain–body axes to orchestrate metabolism and obesity. Here we describe a neuro-mesenchymal unit that controls group 2 innate lymphoid cells (ILC2s), adipose tissue physiology, metabolism and obesity via a brain–adipose circuit. We found that sympathetic nerve terminals act on neighbouring adipose mesenchymal cells via the β2-adrenergic receptor to control the expression of glial-derived neurotrophic factor (GDNF) and the activity of ILC2s in gonadal fat. Accordingly, ILC2-autonomous manipulation of the GDNF receptor machinery led to alterations in ILC2 function, energy expenditure, insulin resistance and propensity to obesity. Retrograde tracing and chemical, surgical and chemogenetic manipulations identified a sympathetic aorticorenal circuit that modulates ILC2s in gonadal fat and connects to higher-order brain areas, including the paraventricular nucleus of the hypothalamus. Our results identify a neuro-mesenchymal unit that translates cues from long-range neuronal circuitry into adipose-resident ILC2 function, thereby shaping host metabolism and obesity.

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Fig. 1: Sympathetic–mesenchyme interactions control ILC2s in the GAT.
Fig. 2: Sympathetic cues orchestrate mesenchyme-derived GDNF and innate type 2 cytokines.
Fig. 3: ILC2-intrinsic RET cues control adipose tissue physiology and obesity.
Fig. 4: An aorticorenal–adipose circuit connects to the brain and regulates ILC2.

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Data availability

Source data for quantifications shown in all graphs plotted in figures and extended data figures are available in the online version of the paper. The datasets generated in this study are also available from the corresponding author upon reasonable request. The RNA-seq datasets analysed are publicly available in the Gene Expression Omnibus repository with the accession numbers GSE179546 and GSE179551 for MSCs and ILC2s, respectively. Source data are provided with this paper.

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Acknowledgements

We thank the Vivarium, Flow Cytometry, Histopathology, Molecular Biology and Hardware platforms at the Champalimaud Centre for the Unknown. We thank Congento LISBOA-01-0145-FEDER-022170, co-financed by FCT (Portugal) and Lisboa2020, under the PORTUGAL2020 agreement (European Regional Development Fund). pAAV-Ef1a-mCherry-IRES-Cre was a gift from K. Deisseroth. PRV-614 (PRV-Bartha) was a gift from L. Enquist and E. Engel. F.C., C.G.-S., and R.G.D. were supported by Fundação para a Ciência e Tecnologia (FCT), Portugal. R.G.J.K.W. is supported by a Marie Skłodowska-Curie Individual fellowship (European Commission, 799810-TOPNIN), a Cancer Research Institute/Irvington Postdoctoral Fellowship and a Postdoctoral Junior Leader fellowship from la Caixa Foundation, ID100010434; LCF/BQ/PR20/11770004. H.V.-F. is supported by ERC (647274), EU, The Paul G. Allen Frontiers Group, US, and FCT, Portugal.

Author information

Author notes

  1. Rita G. Domingues

    Present address: Lydia Becker Institute of Immunology and Inflammation, Manchester Collaborative Centre for Inflammation Research (MCCIR), Division of Infection, Immunity and Respiratory Medicine, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK

Authors and Affiliations

  1. Champalimaud Research, Champalimaud Centre for the Unknown, Lisbon, Portugal

    Filipa Cardoso, Roel G. J. Klein Wolterink, Cristina Godinho-Silva, Rita G. Domingues, Hélder Ribeiro, Joaquim Alves da Silva & Henrique Veiga-Fernandes

  2. Faculdade de Medicina, Universidade de Lisboa, Lisboa, Portugal

    Filipa Cardoso

  3. Max Planck Institute for Metabolism Research, Köln, Germany

    Inês Mahú

  4. Department of Physiology, Anatomy & Genetics, Oxford University, Oxford, UK

    Ana I. Domingos

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Contributions

F.C. designed, performed and analysed the experiments shown in Fig. 1–4 and Extended Data Fig. 1–9. R.G.J.K.W. performed the clearing and imaging in Fig. 1a, and the viral tracing and manipulation experiments in Fig. 4 and Extended Data Fig. 8. C.G.-S. and R.G.D. performed the electroablation surgeries in Extended Data Fig. 8. H.R. provided assistance for the experiments shown in Figs. 1–4. A.I.D. and I. M. provided technical help for the experiment shown in Fig. 1c. J.A.d.S. provided help for the experiment in Extended Data Fig. 2d, e. H.V.-F. supervised the work, planned the experiments and wrote the manuscript.

Corresponding author

Correspondence to Henrique Veiga-Fernandes.

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The authors declare no competing interests.

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Peer review information Nature thanks John Horn and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Extended data figures and tables

Extended Data Fig. 1 Gating strategy for ILC2s and MSCs.

a, ILC2s were defined as: live CD45+Lin−Thy1.2+Sca-1+KLRG1+ (lineage comprised CD3ε, CD8α, TCRβ, TCRγδ, CD19, GR1, CD11c, CD11b and TER119). b, Stroma cells were defined as: live PDGFRA+ MSCs (CD45–CD31–PDGFRA+gp38+SCa-1+), PDGFRA− MSCs (CD45−CD31−PDGFRA−gp38+), and endothelial cells (CD45−CD31+).

Extended Data Fig. 2 Sympathetic nervous system in the GAT and ILC2 function.

a, GAT. Red, sympathetic nerve fibres (TH); Green, endothelial cells (CD31). Scale bar, 300 μm. b, GAT ILC2-derived Met-enk after 6-OHDA administration. n = 5. c, CD4 T cells and TH+ CD4 T cells after 6-OHDA administration. n = 4. d, e, Distance covered by mice in the open field test. n = 3. Scale bar, 10 cm. f, GAT ILC2-derived Met-enk after clenbuterol administration. n = 5. g, Heatmap of Adrb1, Adrb2, and Adrb3 expression (read counts (fragments per kilobase of transcript per million mapped reads; FPKM) on ILC2s, n = 4). h, GAT ILC2s after CNO administration. R26/3Dfl n = 4, R26Th n = 4, and R26/3DTh n = 5. i, Heatmap of Adrb1, Adrb2, and Adrb3 expression (read counts (transcripts per million; TPM) on MSCs, n = 4). j, Gdnf expression after in vitro stimulation of MSCs, n = 3. Data are representative of three independent experiments. n represents biologically independent animals. Data are presented as mean ± s.e.m. Two-tailed unpaired Welch’s t-test. *P < 0.05; ***P < 0.005; ns, not significant

Source data.

Extended Data Fig. 3 Sympathetic regulation of GAT MSCs.

a, Heatmap of genes upregulated in MSCs upon 6-OHDA administration. Vehicle n = 4, 6-OHDA n = 5. b, GAT Il33 expression after 6-OHDA treatment. n = 5. c, GAT Il33 expression after clenbuterol administration. n = 5. d, MSC-derived Il33 after 6-OHDA and clenbuterol administration. n = 6. e, MSC-derived Il25 after 6-OHDA and clenbuterol administration. n = 6. f, GDNF on MSCs. Adrb2fl n = 6, Adrb2ΔPdgfra n = 4. Data are representative of three independent experiments. n represents biologically independent animals. Data are presented as mean ± s.e.m. Two-tailed unpaired Welch’s t-test. ns, not significant

Source data.

Extended Data Fig. 4 RET signals do not affect ILC2 differentiation and activation genes.

a, b, Heatmaps showing log(raw counts) of ILC2-related genes in ILC2s from Retfl (n = 4) and RetΔVav1 (n = 5) mice (a) and Rag1−/−RetWT (n = 3) and Rag1−/−RetMEN2B (n = 3) mice (b)

Source data.

Extended Data Fig. 5 ILC2-autonomous RET signals control type 2 innate cytokines in the GAT.

a–c, GAT ILC2 function. a, Gfra1−/− fetal liver chimeras. n = 5. b, Gfra2+/+, n = 10; Gfra2−/−, n = 5. c, Gfra+/+, n = 8; Gfra3−/−, n = 8. d, RetΔVav1 mixed BM chimeras scheme. e, GAT ILC2 from RetΔVav1 mixed BM chimeras. Retfl n = 6; RetΔVav1 n = 7. f, ILC2s from Rag1−/−RetWT (n = 6) and Rag1−/−RetΔIl5 (n = 6) mice. g, ILC2s from RetWT (n = 10) and RetΔIl5 (n = 8) mice. h, RetΔIl5 mixed bone marrow (BM) chimeras scheme. i, GAT ILC2 from RetΔIl5 mixed BM chimeras. RetWT n = 4, RetΔIl5 n = 4. j, GAT ILC2s in Rag1−/−RetMEN2B BM chimeras. Rag1−/−RetWT n = 5, Rag1−/−RetMEN2B n = 6. k, RetMEN2B mixed BM chimeras scheme. l, Mixed BM chimeras. Rag1−/−RetWT n = 6, Rag1−/−RetMEN2B n = 7. Data are representative of three independent experiments. n represents biologically independent animals. Data are presented as mean ± s.e.m. Two-tailed unpaired Welch’s t-test. *P < 0.05; **P < 0.01; ***P < 0.005; ns, not significant

Source data.

Extended Data Fig. 6 ILC2-intrinsic RET signalling is sufficient to control adipocyte physiology and obesity.

a, GAT ILC2s after 6-OHDA administration. RetWT n = 8 and RetΔIl5 n = 7. b, Weight gain during 16 weeks of HFD regimen. Rag1−/−RetWT n = 4, Rag1−/−RetΔIl5 n = 5. c, Intestinal lamina propria ILC3s. Rag1−/−RetWT n = 5, Rag1−/−RetΔIl5 n = 5. d, Weight gain during 16 weeks of HFD regimen. RetWT n = 5, RetΔIl5 n = 5. e, Frequency of ILC2 and ILC3 in Thy+Lin− lymphocytes from ILC2-chimeric mice after HFD. Each bar represents one mouse. n = 4. f, Total GAT RNA expression of Ucp1, Cox8b and Cidea. n = 5. Data are presented as mean ± s.e.m. Two-tailed unpaired Welch’s t-test (a, c, e); repeated measures ANOVA corrected for multiple comparisons with the Benjamini, Krieger and Yekutieli procedure (b, d); and Mann–Whitney test (f). *P < 0.05; **P < 0.01; ns, not significant

Source data.

Extended Data Fig. 7 RET signals control adipose tissue energy expenditure.

Total RNA expression of adipose tissue-related genes in GAT. a, Retfl n = 4; RetΔVav1 n = 6. b, Rag1−/−RetWT n = 4; Rag1−/−RetMEN2B n = 5. c, GAT co-cultures scheme. d, GAT co-cultures with ILC2 and GDNF. Data are presented as mean ± s.e.m. Two-sided Mann–Whitney test. *P < 0.05; ns, not significant

Source data.

Extended Data Fig. 8 An aorticorenal–adipose circuit connects to the brain.

a, DRG at thoracic 13 (T13) level. Green, viral tracing (VT); red, TH. Scale bar, 100 μm. b, Left, brain atlas schemes of coronal sections. Right, polysynaptic tracing from the GAT corresponding to the highlighted areas on the left. c, Left, brain atlas schemes of coronal section. Right, polysynaptic tracing from the ARG corresponding to the highlighted areas on the left. b, c, Central amygdala (CA), zona incerta (ZI), periaqueductal grey (PAG), subcoeruleus nucleus (SubCD). Scale bars, 200 μm. d, Electrolytic lesion of the PVH. Scale bar, 500 μm. e, GAT ILC2s in PVH-ablated mice. Sham n = 5; PVH-ablated n = 6. f, GAT Il33 expression in AAV(4D) mice compared to contralateral controls after CNO administration. n = 5. g, GAT Il33 expression in AAV(3D) mice compared to contralateral control after CNO administration. n = 4. h, Scheme of combinatorial viral approach. The ARG was injected with an AAV carrying a Cre construct (AAV-Cre). Next, the GAT was injected with a Cre-inducible AAV(3Dfl). AAV(Cre) n = 7 and AAV(Cre)+AAV(3Dfl) n = 6. Data are representative of three independent experiments. n represents biologically independent animals. Data are presented as mean ± s.e.m. Two-tailed unpaired t-test (e); two-tailed Mann–Whitney test (f, g); two-tailed unpaired Welch’s t-test (h). *P < 0.05; **P < 0.01; ns, not significant

Source data.

Extended Data Fig. 9 A sympathetic aorticorenal–adipose circuit connects to the brain and regulates ILC2s.

GAT neuro-mesenchymal units translate sympathetic cues into neurotrophic factor expression. In turn, neurotrophic factors control adipose ILC2 function via the neuroregulatory receptor RET, shaping the host metabolism, energy expenditure and obesity. SNS, sympathetic nervous system.

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Cardoso, F., Klein Wolterink, R.G.J., Godinho-Silva, C. et al. Neuro-mesenchymal units control ILC2 and obesity via a brain–adipose circuit. Nature 597, 410–414 (2021). https://doi.org/10.1038/s41586-021-03830-7

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