ARTICLE

Received 16 Sep 2016 | Accepted 20 Apr 2017 | Published 16 Jun 2017 DOI: 10.1038/ncomms15700 OPEN Single-cell profiling reveals heterogeneity and functional patterning of GPCR expression in the vascular system

H. Kaur1, J. Carvalho1, M. Looso2, P. Singh1, R. Chennupati1, J. Preussner2,S.Gu¨nther3, J. Albarra´n-Jua´rez1, D. Tischner1, S. Classen4, S. Offermanns1,5 & N. Wettschureck1,5

G-protein-coupled receptor (GPCR) expression is extensively studied in bulk cDNA, but heterogeneity and functional patterning of GPCR expression in individual vascular cells is poorly understood. Here, we perform a microfluidic-based single-cell GPCR expression analysis in primary smooth muscle cells (SMC) and endothelial cells (EC). GPCR expression is highly heterogeneous in all cell types, which is confirmed in reporter mice, on the protein level and in human cells. Inflammatory activation in murine models of sepsis or atherosclerosis results in characteristic changes in the GPCR repertoire, and we identify functionally relevant subgroups of cells that are characterized by specific GPCR patterns. We further show that dedifferentiating SMC upregulate GPCRs such as Gpr39, Gprc5b, Gprc5c or Gpr124, and that selective targeting of Gprc5b modulates their differentiation state. Taken together, single-cell profiling identifies receptors expressed on pathologically relevant subpopulations and provides a basis for the development of new therapeutic strategies in vascular diseases.

1 Department of Pharmacology, Max Planck Institute for Heart and Lung Research, Ludwigstr 43, 61231 Bad Nauheim, Germany. 2 ECCPS Bioinformatics Facility, Max Planck Institute for Heart and Lung Research, Ludwigstr 43, 61231 Bad Nauheim, Germany. 3 ECCPS Deep sequencing platform, Max Planck Institute for Heart and Lung Research, Ludwigstr 43, 61231 Bad Nauheim, Germany. 4 Harvey Vascular Centre, Kerckhoff-Klinik, Benekestrae 2–8, 61231 Bad Nauheim, Germany. 5 Medical Faculty, J.W. Goethe University, Theodor-Stern-Kai 7, 60590 Frankfurt, Germany. Correspondence and requests for materials should be addressed to N.W. (email: [email protected]).

NATURE COMMUNICATIONS | 8:15700 | DOI: 10.1038/ncomms15700 | www.nature.com/naturecommunications 1 ARTICLE NATURE COMMUNICATIONS | DOI: 10.1038/ncomms15700

-protein-coupled receptors (GPCRs) are the largest family or at least comparable, with respect to their GPCR repertoire. of transmembrane receptors in eukaryotes; they transduce In contrast to this, studies in other fields indicate that gene Gsignals of numerous physicochemical stimuli including expression is rather heterogeneous in vivo17,18, and it is crucial neurotransmitters, hormones, local mediators, metabolic or for further development of GPCR-based therapeutic strategies olfactory cues, and light1. The human genome encodes B800 to understand whether this is also true for GPCR expression, and if GPCRs, the majority of them being olfactory receptors. Among so, whether certain GPCRs are associated with functional subgroups the 367 non-olfactory GPCRs are still B150 orphan receptors, within a given cell population19. Activated EC, for example, that is, GPCRs for which ligand and function are still unknown2–4. upregulate adhesion molecules and proinflammatory mediators GPCRs have regulatory functions in almost all organ systems, and and are crucial for the pathogenesis of inflammatory vascular dysregulation of GPCR signalling has been implicated in the disease20; whether this inflamed subpopulation of ECs is endowed pathogenesis of many diseases5–9. The unique combination of with a specific GPCR repertoire, is unclear. Also vascular SMC diversity and specificity within the GPCR family, together with the undergo phenotypical changes in response to noxious stimuli, fact that they are readily targetable by exogenous agonists and resulting in a dedifferentiated state characterized by downregulation antagonists, has made GPCRs a most successful group of drug of contractile proteins and upregulation of pro-proliferative, pro- targets4. In the vascular system, GPCRs modulate critical migratory and proinflammatory markersaswellasenhancedmatrix parameters such as vessel tone or endothelial permeability10–12; synthesis21,22. Understanding in what way the GPCR repertoire pharmacological modulation of receptors for angiotensin II, differs between healthy and diseased vascular cells will be crucial to catecholamines or histamine are therefore crucial in the therapy tailor new therapeutic strategies selectively targeting the latter. of arterial hypertension or allergic fluid extravasation, respectively. To address this issue, we used here a microfluidic-based system However, although the market share of GPCR-targeting drugs is for single-cell reverse transcription polymerase chain reaction with 30–40% high, the overall number of targeted GPCR is with (RT-PCR) to determine GPCR expression in individual freshly B30 rather low, suggesting that the potential of GPCRs as drug isolated EC and SMC. We found GPCR expression to be highly targets is not yet fully exploited4. heterogeneous in all cell types and describe characteristic changes The search for new GPCR-based therapies encompasses various in single-cell GPCR repertoires in response to inflammatory strategies, among them the identification of new biased or allosteric activation. Furthermore, we identify functionally relevant ligandsatGPCRswithknownfunctionandligandorthe subgroups of cells that are characterized by specific GPCR deorphanization of GPCRs for which ligands are not yet known13,14. patterns and show examples of how this information can be used A third approach is the identification of new pathophysiologically to modulate cell differentiation. relevant functions for specific GPCRs, in particular for orphan receptors. One useful strategy in the identification of new GPCR functions is the ever more detailed expression analysis in Results functionally relevant cell subpopulations, for example, in Array design and quality control. To narrow down the spectrum subgroups of vascular cell types. While GPCR expression has been of GPCRs to be tested on the single-cell level, we determined studied in bulk cDNA of whole vessels or cultured vascular cells15,16, GPCR expression in bulk RNA of vascular EC and SMC. Of our knowledge about GPCR expression in freshly isolated vascular 424 tested GPCRs, 122 GPCRs were expressed in at least one of cell types, in particular on the single-cell level, is insufficient. This is these cell types (Supplementary Fig. 1A). For these 122 GPCRs, a major limitation, since current interpretations of expression data as well as for 32 additional GPCRs, a primer array for single-cell rely on the assumption that all cells of a given population are equal, expression analysis was designed (Table 1). In addition, 13 genes

Table 1 | Overview over the genes included in the array.

Genes included No. GPCRs – Adrenergic: Adra1a, Adra1b, Adra1d, Adra2c, Adrb1, Adrab2 154 (inton-span- – Chemokine: Ccbp2/Ackr2, Ccr10, Ccr1, Ccr2, Ccr3, Ccr4, Ccr5, Ccr6, Ccr7, Ccr8, Ccr9, Ccrl1, Ccrl2, Cx3cr1, Cxcr1, Cxcr2, Cxcr3, ning: 132) Cxcr4, Cxcr5, Cxcr6, Cxcr7, Xcr1 – Lysophospholipid: Lpar1, Lpar2, Lpar3, Lpar4, Lpar6, S1pr1, S1pr2, S1pr3, S1pr4 – Miscellaneous: Adcyap1r1, Adora1, Adora2a, Agtr1a, Aplnr, Avpr1a, Bdkrb1, Bdkrb2, C3ar1, C5ar1, Calcrl, Chrm2, Chrm3, Cmklr1, Cnr2, Crhr2, Cysltr1, Ednra, Ednrb, Fpr1, Fpr2, Gabbr1, Glp1r, Glp2r, Hrh1, Hrh2, Htr1b, Htr2a, Niacr1, Npy1r, Olfr78, Prokr1, Ptafr, Pth1r, Smo, Sstr4, Sucnr1, Tas2r126, Tas2r135, Tas2r143, Vipr1, Vipr2 – Orphan: Cd97, Celsr2, Darc, Eltd1, Emr1, Emr4, Gpr107, Gpr108, Gpr111, Gpr114, Gpr116, Gpr124, Gpr125, Gpr126, Gpr132, Gpr133, Gpr137, Gpr137b, Gpr146, Gpr153, Gpr171, Gpr174, Gpr176, Gpr18, Gpr182, Gpr183, Gpr19, Gpr21, Gpr30, Gpr34, Gpr35 Gpr39, Gpr4, Gpr52, Gpr56, Gpr63, Gpr64, Gpr65, Gpr83, Gpr97, Gprc5a, Gprc5b, Gprc5c, Lgr4, Lgr5, Lgr6, Lphn1, Lphn2, Lphn3, Mrgprf, Mrgprh – Prostanoid: Ptger1, Ptger2, Ptger3, Ptger4, Ptgfr, Ptgir, Tbxa2r – Protease: F2r, F2rl1, F2rl2, F2rl3 – Purinergic: P2ry1, P2ry10, P2ry12, P2ry13, P2ry14, P2ry2, P2ry6 Cell eGFP, Myh11 (smooth muscle), Cdh1 (epithelial), Cdh5 (endothelial), Ptprc (leukocyte), Itgam (myeloid), Ly6g (neutrophil), 13 identity Cd19 (B lymphocyte), Cd4 (CD4 T lymphocyte), Cd8 (CD8 T lymphocyte), Lyve1 (lymphatic EC), Cspg4 (pericyte), Tnni2 (skeletal muscle) Cell – Cell activation/differentiation: Cd25, Cd44, H2-Ab1, Pecam1, Acta2, Edn1, Dll4, Sele, Smtn, Icam1, Vcam1, Col1a2, Col3a1 36 function – Cytokines/Growth factors: Csf2,Csf2rb, Kdr, Pdgfb, Tgfb1, Tnf, Ifng, IL10, Il17a, Il1b, Il2, Il6 – Transcription factors: Rorc, Tbx21, Mki67, Egr1, Fos, Hif1a, Hey2, Klf2 – Reference genes: Actb, Gapdh, Hprt

In addition to the 122 GPCRs identified in NanoString multiplex RNA analysis, 32 receptors that were negative in NanoString analysis were included. Also 13 genes identifying individual cell types as well as 36 function-related genes, including three reference genes, were added. Whenever possible an intron-spanning design was used, but for 22 single exon GPCRs this was not possible (indicated by strikethrough).

2 NATURE COMMUNICATIONS | 8:15700 | DOI: 10.1038/ncomms15700 | www.nature.com/naturecommunications NATURE COMMUNICATIONS | DOI: 10.1038/ncomms15700 ARTICLE identifying individual cell types and 36 function-defining genes, isolated SMao from Mrgprf-, Gabbr1- or Gprc5b-reporter mice including the three reference genes b-actin (Actb), glyceraldehyde closely matched the results of the single-cell RT-PCR expression 3-phosphate dehydrogenase (Gapdh) and hypoxanthine analysis, while mRNA sequencing data underestimated GPCR phosphoribosyltransferase (Hprt), were included in the array expression (Fig. 2c,d). We also sequenced single-cell RT-PCR (Table 1). Whenever possible intron-spanning primer design was amplicons to exclude off-target amplification or amplification of used, but for 22 single exon GPCRs this was not possible. These highly homologous GPCRs and found that the amplified 22 non-intron-spanning primer pairs gave positive results in sequences were in all cases specific for the targeted receptor all tested cell types (Supplementary Fig. 1B,C), indicative of (Supplementary Fig. 3 and Supplementary Data 2). To investigate contamination with genomic DNA. GPCRs not allowing intron- whether the same degree of heterogeneity was present on spanning primer design were therefore excluded from the analysis the protein level, we analysed expression of select GPCRs in (strikethrough in Table 1). Individual EC or SMC were pre-sorted individual SMao by flow cytometry. We found that also on the by flow cytometry from enzymatically digested tissues of mice protein level GPCR expression was heterogeneous, and that the expressing enhanced green fluorescent protein (EGFP) in EC or percentages roughly matched the values obtained by single-cell SMC and subjected to single-cell isolation, cDNA synthesis and RT-PCR (Supplementary Fig. 4A,B). Ex vivo culture of primary RT-PCR amplification using a microfluidic-based system. Various SMao (passage 1) resulted not only in an upregulation of genes vascular beds were analysed, including aorta (ao), skeletal muscle indicative of a dedifferentiated SMC phenotype, for example, vasculature (sk), lung (lu) or brain (br). All primer pairs included intercellular adhesion molecule 1 (Icam1), vascular cell adhesion in the array produced amplification products with the predicted molecule 1 (Vcam1), marker of proliferation Ki-67 (Mki67) melting behaviour in at least one of three cell types tested (EC, or interleukin-6 (Il6), but also in strongly increased expression SMC and leukocytes) (Supplementary Table 3). Despite stringent frequency for the majority of GPCRs (Fig. 2e). Some GPCRs also sorting criteria, single-cell analysis of individual EC or SMC showed decreased expression, such as Lgr6, Npy1r, Crhr2 or showed 10–18% contamination with other cell types (Table 2). Bdkrb2 (Fig. 2e), but the average number of GPCRs per cell was Only cells with clear identity (‘Cdh5 only’, ‘Myh11 only’) and still strongly increased (Fig. 2f). GPCR expression frequencies in positive expression of reference genes Gapdh and Hprt as quality cultured human aortal SMC (passage 1) matched in most cases control were included in further analyses (Fig. 1a). A systematic the murine data (Fig. 2g middle), though some GPCRs showed comparison of expression data obtained by bulk RNA analysis or notable difference between the species or between individual single-cell RT-PCR in SMC from skeletal muscle vasculature human donors (Fig. 2g right). (SMsk) showed that of 74 GPCRs undetectable in bulk RNA, 26 showed expression in individual SMsk cells (Fig. 1b, left). Of 11 GPCR repertoire in different types of SMC. We next GPCRs with uncertain result in bulk cDNA, all showed amplifi- investigated whether the strong heterogeneity of GPCR cation in individual cells (Fig. 1b, middle). Of 37 GPCRs clearly expression was a special feature of conductance arteries such as expressed in bulk RNA, two were completely absent in individual the aorta, or whether it was also present in resistance arteries, for cell analysis (Fig. 1b, right). These two GPCRs, Eltd1 and Gpr116, 23 example, from SMsk. Also in SMsk GPCR expression was very are known to be highly specific for EC , indicating that these heterogeneous (Fig. 3a), although the overall number of GPCRs discrepancies are due to contamination of SMsk with EC. per cell was higher than in SMao (Fig. 3a,b). The repertoire of GPCRs expressed in the two SMC types differed strongly: GPCRs GPCR heterogeneity in SMC. In individual aortal SMC (SMao) Lphn2, Cmklr1, Lpar1, Gpr133, P2ry6, Lgr6 and F2r were mainly of healthy adult mice, GPCR expression was very heterogeneous present in SMao, while a large number of other GPCRs were (Fig. 2a). In total, 76 GPCRs were detected in SMao, but only 19 predominantly expressed in SMsk (Fig. 3a). Among those of them were expressed in more than 50% of cells, and only eight receptors preferentially or selectively expressed in SMsk, the GPCRs (Lphn1, Lgr6, F2r, Adra1d, Cd97, Gpr107, Gpr108 and largest group were peptide hormone receptors (Fig. 3c), for Mrgprf) were expressed in more than 90% of cells (Fig. 2a). example, receptors for endothelin (Ednra, Ednrb), angiotensin II Reference genes Actb and Gapdh as well as SMC marker gene (Agtr1a), vasopressin (Avpr1a), neuropeptide Y (Npy1r), pituitary Myh11 were homogenously expressed (Fig. 2a, top). On average, adenylate cyclase-activating polypeptide (PACAP, acting on individual cells expressed 20.3±0.9 of the tested 132 GPCRs, Adyap1r1), vasoactive intestinal polypeptide (VIP, acting on though the individual values varied between 3 and 38 GPCRs per Vipr1 and Vipr2), corticotropin releasing hormone (Crhr2), cell (Fig. 2b). mRNA sequencing of individual SMao showed parathyroid hormone (Pth1r) or calcitonin gene-related peptide even lower frequencies of GPCR expression (selected data in (CGRP, acting on Calcrl) (Fig. 3d). Also a number of chemokine Supplementary Fig. 2, whole data set in Supplementary Data 1), and orphan receptors were preferentially expressed in SMsk which led us to verify single-cell expression data in GPCR (Fig. 3e). We also analysed GPCR expression in other SMC types, reporter mice that are genetically engineered to express for example, from the mesenteric vasculature (SMmes) or urinary b-galactosidase (bgal) under control of different GPCR bladder (SMub). K-means cluster analysis revealed that SMC promoters. Flow cytometric analysis of bgal expression in freshly from mesenteric or skeletal muscle vasculature, two regions rich

Table 2 | Contaminating cells in single-cell expression analysis.

Cell type Sorted for Marker gene expression (%) Cdh5 only Myh11 only Other markers No marker ECsk Cdh5-EGFP 81.5 0.0 17.8 0.7 EClu Cdh5-EGFP 80.8 0.0 11.6 7.6 ECbr Cdh5-EGFP 85.4 0.0 10.4 4.2 SMao Myh11-EGFP 0.0 81.5 15.2 3.2 SMsk Myh11-EGFP 0.8 84.0 12.0 3.2

Sorted EC and SMC were subjected to single-cell expression analysis and re-evaluated based on the expression of various identity-defining genes.

NATURE COMMUNICATIONS | 8:15700 | DOI: 10.1038/ncomms15700 | www.nature.com/naturecommunications 3 ARTICLE NATURE COMMUNICATIONS | DOI: 10.1038/ncomms15700

a SMao SMsk EClu ECsk 105

104

) 103

102 LoD Ct – 1 (2 10 Gene expression 100 0 Cd4 Cd8 Hprt Actb Ly6g Ptprc Cdh1 Cd19 Cdh5 Itgam Tnni2 eGFP Myh11 Gapdh

b SMsk ) 104

103 LoD Ct – 102

101 Gene expression 0 sc RT-PCR (2 10 0 F2r Hprt Lgr4 Actb Lgr6 Darc Ptgir Hrh2 Ptgfr Gpr4 F2rl1 Eltd1 Ccrl1 Vipr1 F2rl3 Ccrl2 Vipr2 Htr2a Cd97 Pth1r Lpar1 Crhr2 Lpar3 Cxcr4 S1pr1 Ednra P2ry6 P2ry2 Ednrb S1pr3 Cxcr7 Gpr21 Lphn1 Olfr78 Npy1r Gpr64 Gpr30 Gpr19 Lphn3 Gpr56 Lphn2 Ptger1 Agtr1a Celsr2 Ptger4 Ptger3 Ptger2 Gapdh Mrgprf Cmklr1 Sucnr1 Avpr1a P2ry14 Adora1 Adra1a Bdkrb2 Tbxa2r Adra1b Gprc5c Gprc5b Gabbr1 Adra1d Gpr114 Gpr124 Gpr108 Gpr133 Gpr153 Gpr116 Gpr126 Gpr176 Gpr132 Gpr125 Gpr137 Gpr107 Adora2a Gpr137b Adcyap1r1

Absent Below threshold Positive (increasing strength from left to right) QC Gene expression pooled cell RNA analysis

Figure 1 | Single-cell RT-PCR analysis in freshly isolated vascular cells. EC or SMC obtained from skeletal muscle vasculature (sk), lung (lu), aorta (ao) of Cdh5-Crepos; dTom/EGFP-reporterpos mice (Cdh5-EGFP) and tamoxifen-treated Myh11-CreERT2pos; dTom/EGFP-reporterpos mice (Myh11-EGFP), respectively, were subjected to single-cell RT-PCR. (a) Expression of identity-defining genes and quality control genes (Gapdh, Hprt and Actb) after exclusion of contaminating cells or marker negative cells (each dot one cell). (b) Comparison of expression data obtained by multiplex RNA expression analysis in pooled SMsk and single-cell RT-PCR (sc RT-PCR) in individual SMsk. GPCRs are arranged on the abscissa according to their expression strength in pooled RNA analysis, the ordinate shows the strength of gene expression in individual cells (each dot one cell). Green boxes indicate genes negativeinsc RT-PCR but positive in pooled RNA analysis (cell/animal numbers: sc RT-PCR: n ¼ 57 cells from seven mice; pooled RNA analysis: 500 ng from 106 cells per six mice. Values of genes that are not expressed were scattered around 0 to allow graphical estimation of cell counts). Expression data are calculated as follows: Gene expression ¼ 2(Limit of detection(LoD) Ct—sample Ct); LoD Ct is set to 24. in resistance arteries/arterioles, were quite similar in their GPCR Endothelial GPCR pattern after acute inflammatory activation. profile, but differed strongly from SMao or SMub (Fig. 3f,g). An We next investigated how the GPCR repertoire changes in analysis of differential gene expression for all SMC types is shown individual EC in response to acute inflammatory activation. To in Supplementary Fig. 5A–C; a comparison of GPCR frequencies do so, we used a murine sepsis model induced by intraperitoneal for all SMC types can be found in Supplementary Fig. 5D. An (i.p.) injection of bacterial endotoxin lipopolysaccharide (LPS), overview of the total number of cells, mice and independent which results in massive direct and indirect activation of EC24. experiments is shown in Supplementary Table 4. ECbr showed 12 h after LPS injection a clear upregulation of markers of inflammatory activation such as Icam1 or E-selectin (Sele), whereas expression of vascular endothelial growth GPCR heterogeneity in different types of EC. To determine factor receptor 2 (VEGFR2, encoded by Kdr) or endothelin-1 GPCR heterogeneity in primary murine EC from different (Edn1) was reduced (Fig. 5a). Also the GPCR pattern changed locations, we isolated individual EC from lung, skeletal muscle significantly: numerous orphan receptors (Gprc5a, Gpr97, or brain (EClu, ECsk, ECbr) (selected GPCRs in Fig. 4a, all data Gpr111, Gpr153, Lphn2, Gpr107, Gprc5b and Gpr56) were in Supplementary Fig. 6). Like SMC, EC showed a high hetero- upregulated, as well as select chemokine receptors (Darc, Ccrl2 geneity of GPCR expression, with only five receptors (Cd97, and Cxcr7) and purinergic receptors (P2ry2, P2ry6 and Adora2a). Calcrl, Gpr116, S1pr1 and Eltd1) being homogenously expressed Other GPCRs, such as Tbxa2r, Lphn1, Gpr125, Gabbr1, Gpr124, in all EC types (Fig. 4a, Supplementary Fig. 6). Individual EC Calcrl or Cd97, were downregulated (Fig. 5a), resulting in total in from different vascular beds expressed on average 20.9, 21.0 and a non-significant increase in the number of GPCRs per individual 16.3 of the tested 132 GPCRs (Fig. 4b). K-means cluster analysis cell (Fig. 5b). K-means cluster analysis confirmed ECbrLPS as a identified three-cell clusters, which largely corresponded to the distinct population characterized by a specific GPCR repertoire three different EC types (Fig. 4c) and are characterized by specific (Fig. 5c,d). Also in EClu characteristic changes in the GPCR GPCR repertoires: receptors Glp1r, Calcrl, Lphn3, Ccbp2, Celsr2 expression pattern were observed upon LPS treatment, though and Cd97 were strongest expressed in cluster 1 cells (containing with distinct differences to ECbr (select data in Fig. 5e,f; all data EClu) (Fig. 4d), whereas receptors Darc, Ptger4, P2ry6, Cysltr1 or in Supplementary Fig. 6); the average GPCR number per cell was Gprc5a were strongest in cluster 2 cells (containing mainly ECsk) clearly reduced ECluLPS (Fig. 5g). K-means analysis of all four (Fig. 4e). Cluster 3 cells (mainly ECbr) showed higher expression groups showed that upon LPS activation the originally very of Gpr30, Gpr124, Gpr4 or Lpar4 (Fig. 4f). dissimilar EC types became more similar, but are still recognized

4 NATURE COMMUNICATIONS | 8:15700 | DOI: 10.1038/ncomms15700 | www.nature.com/naturecommunications NATURE COMMUNICATIONS | DOI: 10.1038/ncomms15700 ARTICLE

a Expression b SMao frequ. (%) 40 Gene Myh11 100 Actb 100 30 Gapdh 100 Lphn1 100 20 Lgr6 98 F2r 97 Adra1d 95 10

Cd97 90 GPCRs per cell Gpr107 90 0 Gpr108 90 Mrgprf 90 Individual cells

Npy1r 85 Aver. Gpr125 78 600 Gabbr1 77 Lphn2 72 1.06 Tbxa2r 72 c 400 Calcrl 67

5 Count

Lgr4 67 10 200 Control Cmklr1 60 Gpr137 52 104 Gpr137b 52 0 P2ry2 52 3 500 10 P2ry6 48 SSC-A 400 Ccrl2 47 0 69.2 Ednra 43 –103 300 Gpr153 40 gal reporter β 3 3 4 5 Count Celsr2 37 –10 0 10 10 10 200 - Gpr124 35 αSMA (PE) 100 Htr2a 35

Lpar1 33 0 Gabbr1 Pth1r 33 –103 0 103 104 105 Gpr133 30 βgal (FITC) Cxcr7 27 25 dfsc RT-PCR Adra1a sc mRNAseq Crhr2 25 100 FACS reporter 60 Bdkrb2 23 *** Gpr21 23 80 Agtr1a 22 17 40 F2rl1 60 Ptgir 17 Adra1b 15 15 40 Ptger3 20 Gpr4 13 Gpr64 13 20 GPCRs per cell Gprc5b 13 Lpar4 12 Expression frequency (%) 0 0 Gpr39 10 SMao Mrgprf

0 Gabbr1 Gprc5b SMao_cul 100 200 300 400 500 e 100

80

60

40 SMao SMao_cul 20

Expression frequency (%) 0 II6 Tnf Lgr4 Lgr6 Ptgir F2rl1 Htr2a Pth1r Lpar1 Tgfb1 Crhr2 Lpar4 Acta2 Cxcr4 Pdgfb Calcrl Ednra S1pr1 P2ry6 S1pr3 Icam1 Cxcr7 Npy1r Olfr78 Mki67 Gpr64 Gpr30 Gpr19 Lphn3 Ptger4 Myh11 Cysltr1 Vcam1 Avpr1a Tbxa2r Bdkrb2 Adra1b Gprc5a Gprc5b Gpr124 Gpr133 Gpr153 Gpr126 Gpr137 Adora2a Gpr137b Adcyap1r1

Identity Function GPCRs up GPCRs down g 100

80

60 SMao_cul 40 huSMao_ cul_#1 20 huSMao_

Expression frequency (%) 0 cul_#2 IL6 F2R LGR4 CD97 F2RL1 LPAR1 ICAM1 PTGIR ACTA2 S1PR1 P2RY6 P2RY2 LPHN1 LPHN3 LPHN2 GPR64 PTH1R GPR30 GPR56 EDNRA EDNRB GAPDH GPR124 GPR108 GPR153 GPR126 GPR125 TBXA2R CALCRL GPR137 GPR107 CELSR2 PTGER4 ADRA1B GABBR1 ADRA1D GPRC5B GPRC5C MRGPRF GPR137B

Identity / Species-matched GPCRs Species- Interindividually function mismatched mismatched GPCRs GPCRs Figure 2 | GPCR expression in individual aortal SMC (SMao). (a) Heat map of GPCR expression in 60 SMao (each column one cell) from eight mice (sorted by frequency; horizontal bars on the right side visualize expression frequency (in %); frequencies o10% not shown (for full data set, Supplementary Fig. 6); expression of Myh11, Actb and Gapdh as quality control). (b) Number of GPCRs expressed in individual SMao. (c) Example of flow cytometric analysis of bgal-positive SMao in control mice and Gabbr1-bgal reporter mice. (d) Comparison of GPCR expression frequency in individual cells as judged by single-cell RT-PCR (sc RT-PCR), single-cell mRNA sequencing (sc mRNAseq), and flow cytometric analysis of reporter-positive SMao from Mrgprf-/Gabbr1-/Gprc5b-reporter mice (FACS reporter, n ¼ 3 per group). (e) Percentage of cells expressing selected genes in freshly isolated SMao (n ¼ 60) and SMao cultured for one passage (7–10 days) (SMao_cul; n ¼ 29). (f) Average number of GPCRs expressed in freshly isolated SMao and SMao_cul. (g) Percentage of cells expressing a given gene in cultured murine (SMao_cul) and human (huSMao_cul) aortal SMC (#1: 2-year-old healthy male child, n ¼ 42 cells; #2: 51-year-old male adult, n ¼ 31 cells); Expression data are calculated as follows: Gene expression ¼ 2(Limit of detection(LoD) Ct—sample Ct); LoD Ct was set to 24. Data in b,d,f are shown as mean±s.e.m.; comparisons between groups were performed using two-tailed t-test; ***Po0.001.

NATURE COMMUNICATIONS | 8:15700 | DOI: 10.1038/ncomms15700 | www.nature.com/naturecommunications 5 ARTICLE NATURE COMMUNICATIONS | DOI: 10.1038/ncomms15700

a b c Expression 40 30 SMao SMsk frequ. (%) SMao SMsk Gene *** Gapdh 100 100 30 100 100 Actb 20 Myh11 100 100 Lphn2 72 32 20 Cmklr1 60 16 Lpar1 33 2 10 Gpr133 30 7 48 7 GPCRs per cell 10

P2ry6 Number of GPCRs Lgr6 98 32

Mainly SMao F2r 97 4 Ednrb 242 0 0 Adora2a 739 Gpr30 049 SMsk SMsk SMao SMao Vipr1 523 Mainly Mainly Gpr19 823 Ptger2 316 GPCR family Adcyap1r1 382 Orphan Gpr126 093 Chemokine Olfr78 2100 Peptide hormone Gprc5b 13 93 Lipid Avpr1a 061 Catecholamine Vipr2 765 Nucleotide/-side S1pr3 8100 d 15 32 4 Ptger3 ) 10 SMao Ptgir 17 40 SMsk Gprc5c 10 100 *** Adra1a 25 89 103 LoD Ct – Mainly SMsk Agtr1a 22 35 *** *** Gpr21 23 44 *** *** Cxcr7 27 93 102 *** * *** *** Crhr2 25 89 * *** Gpr124 35 91 Ccrl2 47 86 101 Ednra 43 98 Calcrl 67 96 Pth1r 33 81 (2 Gene expression 100 Npy1r 85 100 Mrgprf 90 96 100 100 Vipr1 Vipr2 Pth1r Lphn1 Crhr2 Calcrl Ednra Ednrb Npy1r Agtr1a 0 100 200 300 400 500 Avpr1a Adcyap1r1

efgSMao 4

) 10 SMsk SMsk 5 *** #3 Cluster 3 ** 50 10 *** * #1 LoD Ct – *** *** 4 *** *** SMmes #2 2 *** * #3

10 #2 3 0 SMao 101 * Cell type 2 SMmes 100 Dissimilarity SMsk t-SNE dimension 1 –50 #1 1 SMao Gene expression (2 Gene expression 10–1 SMub SMub

0 Low High #1 #2 #3 –500 50 Ccrl2 Cxcr7 Olfr78 Gpr21 Lphn1 Gpr19 (Mainly SMsk (Mainly (Mainly t-SNE dimension 2 Mrgprf Gprc5c Gprc5b Gpr124 Gpr126 and SMmes) SMao) SMub) Figure 3 | Single-cell GPCR expression in different SMC types. (a) Heat map of GPCR expression in SMao and SMsk (60 and 57 cells per SMC type, from seven to eight mice each); horizontal bars on the right side visualize expression frequency (in %) (for full data sets, Supplementary Fig. 6). (b) Average number of GPCRs expressed in individual SMao and SMsk. (c) GPCRs preferentially expressed in SMao or SMsk grouped by GPCR family. (d,e) Comparative analysis of expression strength for different peptide hormone receptors (d) or members of the chemokine/orphan family (e) in SMao and SMsk. (f,g) K-means clustering results for different SMC types: (f) Heat map indicating degree of similarity between individual cells as measured by Euclidian distances of the transcriptome correlation matrix. K-means clustering identified three major groups of cells which are colour-coded along the axes. (g) t-SNE map representation of clusters identified in f: the more similar two cells are, the closer together they are plotted (each dot one cell). Cluster assignment is indicated by colour, cell type is indicated by symbols. SMmes, SMC from mesenteric vasculature (29 cells from eight mice); SMub, SMC from urinary bladder (25 cells from eight mice). Expression data are calculated as 2(Limit of detection(LoD) Ct—sample Ct); LoD Ct was set to 24. Data in b,d,e are shown as mean±s.e.m.; comparisons between groups were performed using two-tailed t-test. *Po0.05; **Po0.01; ***Po0.001. as separate clusters (Fig. 5h). Detailed analysis of transcriptional the same time reduced expression of GPCRs such as Darc, Gpr97, changes showed that both EC types showed upregulation of Gabbr1 and others (Fig. 5k). Though expression of Fpr2, C5ar1 Icam1, Vcam1 and Sele, whereas Kdr, platelet-derived growth and Ccr1 is normally restricted to myeloid cells (Supplementary factor b (Pdgfb), and Edn1 were downregulated (Supplementary Fig. 6), this subpopulation was clearly positive for Cdh5, Pecam1 Fig. 7A). Both EC types showed upregulation of GPCRs Ccrl2, and EC-specific GPCRs such as Gpr116 or Eltd1, but negative for Cxcr7, Gpr111 and others (Supplementary Fig. 7B), whereas leukocyte markers Ptprc, Itgam and Ly6g (Fig. 5k), indicating they Calcrl, Cd97, Gabbr1, Lphn1 and so on were downregulated are indeed an EC population that assumed a myeloid-like GPCR (Supplementary Fig. 7C). However, some GPCRs were expression pattern. differentially regulated: Ptger2, P2ry10, F2rl1, Ccbp2, Glp1r, To also assess the endothelial GPCR repertoire under Celsr2 or Cxcr4 were up- or downregulated selectively in EClu conditions of chronic vascular inflammation, we investigated (Fig. 5i), while Gpr107, Gpr97, Adora2a, Gpr153, Darc, Fpr2, aortal EC from ApoE-deficient mice kept for 16 weeks on a C5ar1 and Ccr1 were only upregulated in ECbr (Fig. 5j). Western-style high-fat diet25. Surprisingly, all Cdh5-positive EC Interestingly, upregulation of Fpr2, C5ar1 and Ccr1 was obtained from aortae were also positive for SM marker Myh11, restricted to a small subpopulation of ECbrLPS that showed at although Myh11 levels were very low compared to normal SMC

6 NATURE COMMUNICATIONS | 8:15700 | DOI: 10.1038/ncomms15700 | www.nature.com/naturecommunications NATURE COMMUNICATIONS | DOI: 10.1038/ncomms15700 ARTICLE

abc Expression ECbr 30 100 frequ. (%) Cluster EClu ECsk ECbr Gene EClu ECsk ECbr 50 #1 Gapdh 100 100 100 #2 Cd97 98 98 98 20 #3 Calcrl 100 98 87 0 Glp1r 98 3 0 ECsk Cell type Ccbp2 73 20 0 10 –50 EClu Lphn3 94 0 23 EClu GPCRs per cell Mainly EClu Celsr2 56 18 6 t-SNE dimension 1 ECsk Average number of number Average –100 Gprc5b 13 83 56 ECbr Gpr56 25 98 98 0 Ednrb 19 75 0 –100 –50 0 50 100 Ptger4 0430 EClu ECbr ECsk t-SNE dimension 2 Darc 2180 P2ry6 2132 d Cysltr1 0152 3 Gprc5a 8300 Mainly ECsk Adora2a 25 53 2 F2r 31 48 13 2 Gpr126 19 18 8 Gpr4 38 65 81 Gpr124 69 30 90 Gpr30 0317 1 ECbr Mainly 22335

Lpar4 all (EClu) versus 98 100 100

Gpr116 change cluster 1 Fold S1pr1 100 100 98 0 96 98 98

Similar Eltd1 F2r

0 200 400 600 Lgr4 Darc Gpr4 Eltd1 Htr2a Cd97 Glp1r Lpar4 Cxcr4 S1pr1 Calcrl P2ry6 P2ry2 Cxcr7 Gpr30 Lphn3 Gpr56 Celsr2 Ccbp2 Ptger4 Cysltr1 Bdkrb2 Gprc5b Gpr124 Gpr125 Gpr137 Gpr137b

e f 2.5 4 2.0 3 1.5 2 1.0

1 0.5 Fold change cluster 3 Fold Fold change cluster 2 Fold (mainly ECbr) versus all (mainly ECbr) versus (mainly ECsk) versus all (mainly ECsk) versus 0 0 F2r F2r Darc Darc Gpr4 Eltd1 Eltd1 Ccrl2 Cd97 Cd97 Glp1r Glp1r Lpar4 Cxcr4 Calcrl Calcrl Ednrb Ednrb P2ry6 P2ry2 Lphn1 Gpr30 Gpr30 Lphn3 Lphn3 Gpr56 Gpr97 Gpr97 Celsr2 Ccbp2 Ccbp2 Ptger4 Ptger4 Cysltr1 Cysltr1 Gprc5a Gprc5a Gprc5b Gpr124 Gpr124 Gpr108 Gpr126 Gpr126 Gpr125 Gpr125 Adora2a Adora2a Figure 4 | Single-cell GPCR expression in different EC types. (a) Heat map of GPCR expression in EClu, ECsk, ECbr (48, 40, 52 cells per EC type, from six to eight mice per group); horizontal bars on the right side visualize expression frequency in % (for full data sets, Supplementary Fig. 6). (b) Average number of GPCRs expressed in individual EC types (mean±s.e.m.). (c) T-SNE plot of k-means clustering data for different EC types: cluster assignment is indicated by coloured numbers, cell type is indicated by symbol (each dot one cell; distance between dots indicates degree of similarity). (d–f) Genes differentially expressed in cluster 1 (EClu, d), cluster 2 (mainly ECsk, e), and cluster 3 (mainly ECbr, f) (only genes significantly regulated (P40.05) and with fold change o0.7 or 41.5 are displayed). Data in b are mean±s.e.m.

(Fig. 6a). Cdh5pos; Myh11low aortic cells expressed EC-specific GPCR repertoire in SMC from atherosclerotic mice. We next GPCRs such as Gpr116 or Eltd1, whereas GPCRs normally studied GPCR patterns in SMC from atherosclerotic aortae. present in SMao, such as Lgr6 or Mrgprf, were low or absent After 16 weeks of high-fat diet, SMao showed clear signs of (Fig. 6b). We therefore concluded that these Cdh5-positive cells inflammatory activation and dedifferentiation26,27: Icam1, Vcam1 are despite low levels of Myh11 expression aortic EC (ECao). and Il6 were upregulated, whereas contractile proteins such as Compared to cells from healthy aortae, ECao from atherosclerotic Acta2 and Myh11 were reduced in expression strength, though aortae showed clear changes in the expression of both function- not in frequency (Fig. 7a, upper part). In addition, numerous related genes and GPCRs (Fig. 6c). In detail, markers of GPCRs showed increased expression frequency (Fig. 7a, lower inflammatory activation such as Icam1, Vcam1 or Il6 were part), resulting in a significantly increased number of GPCRs per upregulated, whereas expression of Kdr and Edn1 was reduced individual cell (Fig. 7b). K-means cluster analysis assigned the (Fig. 6c,d). Most GPCRs showed diminished expression majority of SMao from atherosclerotic mice (squares in Fig. 7c) to (Fig. 6c,d), resulting in a reduction of the GPCR number a cluster characterized by increased expression of GPCRs such as expressed per cell (Fig. 6e). However, a trend to increased gene Olfr78, Ednrb, Adcyap1r1, Ptger2, Avpra1a, S1pr3, Ptgir, Vipr2, expression was observed for Ccrl2, S1pr3, Darc and Gpr153 Ccrl2, Cxcr7, Gprc5b or Gprc5c (Fig. 7d). ApoE-deficient mice (Fig. 6c,d). A comparison of expression changes in acutely and without high-fat diet showed an intermediate phenotype, but no chronically activated EC showed that adhesion molecules and clear upregulation of inflammatory genes such as Icam1 or selected GPCRs such as Ccrl2, Darc, F2r, Gpr153 or Lphn2 were Vcam1; comparable changes were observed in aged but otherwise upregulated both in acute and chronic inflammation, whereas healthy C57BL/6 mice (Fig. 7e). To understand the mechanisms Kdr, Edn1, Pdgfb and various GPCRs were downregulated in both regulating GPCR expression in healthy and dedifferentiating conditions (Fig. 6f). Interestingly, a number of GPCRs were SMao, we analysed transcription factor (TF) binding sites in upregulated in acute inflammatory activation, but downregulated promoters of GPCRs that were either up- or downregulated in chronic inflammation, for example, Cxcr7, Gpr56, Gprc5a and in dedifferentiating SMC. GPCRs that were upregulated in others (Fig. 6f). atherosclerotic SMao were more likely to contain binding sites

NATURE COMMUNICATIONS | 8:15700 | DOI: 10.1038/ncomms15700 | www.nature.com/naturecommunications 7 ARTICLE NATURE COMMUNICATIONS | DOI: 10.1038/ncomms15700 for TFs such as heat shock factors proteins 1,2,4 (HSF1,2,4), contain bindings sites for, among others, estrogen-related nuclear retinoic acid receptor a/b (RARA, RARB), NF-kB2, AP2 receptors ESRRA and ESRRB, sterol regulatory element-binding (TFAP2A,B,C), KLF5 and others (Fig. 7f, left side). GPCRs that transcription factor 1 (SREBF1), or T box TFs TBX1 and TBX19 were downregulated in atherosclerotic SMao were more likely to (Fig. 7f, right side; complete list in Supplementary Table 5).

Expression frequ. (%) ECbr ECbr ECbrLPS abcECbr LPS Actb 100 100 Gapdh 100 100 20 NS Hprt 100 100 High Cdh5 100 100 2 Pecam1 100 100 15 Cluster 2 Hif1a 81 100 (ECbrLPS) 67 86 Up Tgfb1 Sele 2 27 Icam1 21 91 10 Function Vcam1 15 27 1 Pdgfb 100 82

98 77 Dissimilarity

Kdr 5 (ECbr) GPCRs per cell

Edn1 63 32 Cluster 1 Darc 0 68 Gprc5a 0 23 0 P2ry6 2 27 0 Low Gpr97 4 27 Cluster 1 Cluster 2

Gpr111 2 23 LPS ECbr Gpr153 0 14 d ECbr (ECbr) (ECbrLPS) Adora2a 2 23 4 P2ry2 33 86 Lphn2 21 77 Up Down Gpr107 44 68 3 Gprc5b 56 82 Ccrl2 60 64 Cxcr7 69 86 2 Gpr56 98 100 S1pr1 98 100 GPCR

Tbxa2r 27 0 change Fold Lphn1 56 9 1

Gpr125 46 18 all ECbrLPS versus Gpr30 17 0 Gabbr1 65 45 0 Gpr124 90 59 Kdr

Down Calcrl

64 Lgr4 87 Sele Darc Eltd1 Edn1 Hif1a Ccrl2 Htr2a Cd97 Tgfb1 Lpar4 Pdgfb Calcrl P2ry6 P2ry2 Icam1 Cd97 Cxcr7 Lphn1 Gpr30 Lphn3 Gpr56 98 Lphn2

77 Gpr97 Cmklr1 Tbxa2r Gprc5a Gprc5b Gabbr1 Gpr111 Gpr124 Gpr108 Gpr153 Gpr125 Gpr137 EItd1 98 100 Gpr107 Gpr116 100 100 Gpr137b 0 150 300 450 600

e f 3 3 g 30 High

Cluster 2 2 20 (ECluLPS) 2 **

1 10

1 change Fold Dissimilarity GPCRs per cell ECluLPS versus all ECluLPS versus (EClu) Cluster 1 0 0

0 Low F2r Kdr Sele LPS Ptafr Eltd1 EClu EClu Edn1 Hif1a Ccrl2 Htr2a Cd97 Glp1r Cxcr4 Pdgfb Calcrl S1pr1 Ednrb P2ry6 P2ry2 Icam1 Cxcr7

Cluster 1 Cluster 2 Lphn1 Lphn3 Gpr56 Lphn2 Gpr97 Ccbp2 Vcam1 Cmklr1 Bdkrb2 Gprc5c Gprc5a Gprc5b Gpr111 Gpr124 Gpr126 Gpr125 (EClu) (ECluLPS) Pecam1 hi j ) ) 3 104 10 *** *** *** 50 ** 0.06 **

ECbr EClu 103 ** * * LoD Ct – LPS LoD Ct – 2 LPS 0.08 10 * 0 ECbr * * * 102 0.08

Cell type Cluster 1 –50 EClu 1 10 ECbr #1 10 ECbrLPS #2 t-SNE dimension 1 EClu #3 0 10 100 –100 ECluLPS #4 0 Gene expression (2 Gene expression Gene expression (2 Gene expression 0 –60 –40 –20 0 20 40 F2rl1 Darc Fpr2 Ccr1 t-SNE dimension 2 Ptger2 Ccbp2 Glp1r Celsr2 Cxcr4 Gpr97 C5ar1 P2ry10 Gpr107 Adora2a Gpr153 ECbr ECbrLPS EClu ECluLPS

k Identity/function GPCR

800 Actb Gapdh Cdh5 Pecam1 Ptprc Itgam Ly6g Hif1a Icam1 Eltd1 Gpr116 Cxcr7 Gprc5b Ccrl2 P2ry2 Gpr107 Cd97 Darc Gpr125 Gprc5a P2ry6 Gpr97 Gpr153 Gpr111 Bdkrb2 Gabbr1 Lpar4 Gpr137b Htr2a Gpr137 C5ar1 Fpr2 Fpr1 Ccr1 F2r Tnf

600

400

200

0

8 NATURE COMMUNICATIONS | 8:15700 | DOI: 10.1038/ncomms15700 | www.nature.com/naturecommunications NATURE COMMUNICATIONS | DOI: 10.1038/ncomms15700 ARTICLE

Dedifferentiating SMC of the healthy aorta. We noticed that expression analysis has three crucial advantages: First, it allows some SMao from healthy mice were assigned to the cluster of to rigorously exclude contaminating cells and thereby precludes dedifferentiating SMC in Fig. 7c (marked by arrows), indicating misinterpretation of data. Second, single-cell expression analysis that a spontaneously dedifferentiating population exists in the is able to detect transcripts in rare cell populations that might be healthy aorta. Indeed, k-means analysis of SMao from healthy below threshold in bulk RNA/cDNA analyses: 37 GPCRs that mice identified a small subpopulation of cells as being clearly were judged negative or uncertain in SMsk by NanoString different from the rest (cluster 3 in Fig. 8a). These cells were analysis were detected in individual SMsk, though in some cases characterized by a reduced expression of contractile proteins only in 1.5% of cells. However, due to the limited amount of RNA Myh11 or Acta2, but increased expression of Icam1, Vcam1, obtained from an individual cell also single-cell expression may Col1a2 and Col3a1 (Fig. 8b). This dedifferentiated phenotype was overlook very low abundance transcripts, in particular if the associated with reduced expression of GPCRs such as Lgr6 and RNA quality is compromised. Since GPCRs are in many cases Adra1d, and increased expression of Ptgir, Vipr2, Gpr39, Lpar1, expressed at low levels29, we directly compared the two major Gprc5b, Gpr124, Cxcr7, Gpr137b, Ednra and others (Fig. 8b). readout systems for single-cell expression analysis, RT-PCR and Spearman’s rank correlation analysis confirmed the positive mRNA sequencing, with respect to their sensitivity for GPCR correlation between Myh11, Acta2, Lgr6, Adra1d on the one hand detection in SMao. RT-PCR detected most GPCRs with and Icam1, Vcam1, CD44, Ptgir, Gpr39, Vipr2, Cxcr7, Gprc5b and higher frequency than mRNA sequencing, and sequencing of so on on the other hand (Fig. 8c). A direct comparison of changes the single-cell amplificates as well as analyses in GPCR reporter in dedifferentiating SMC from healthy mice and atherosclerotic mice and on the protein level largely confirmed the RT-PCR data. mice showed that both cell types behaved similarly with respect to A possible explanation for this difference in sensitivity lies in the upregulation of adhesion molecules and GPCRs such as Ptgir, fact that single-cell RT-PCR uses target-specific pre-amplification Vipr2, Gprc5b, Gprc5c, Cxcr7 and so on, as well as down- of mRNAs, while pre-amplification for mRNA sequencing is regulation of Acta2, Myh11, Adra1d and Lgr6 (Fig. 8d, left side). unbiased. However, a number of GPCRs were upregulated only in The third and probably most relevant advantage of single-cell the context of atherosclerotic dedifferentiation, and not in expression analysis is that it allows to estimate the degree of spontaneous dedifferentiation, such as Olfr78, Ednrb, Adcyap1r, GPCR heterogeneity within a cell population and, consecutively, Ptgfr and others (Fig. 8d, right side). to identify correlations between GPCR profile and functional state Since vascular SMC dedifferentiation is believed to occur of a given cell. We found that all types of SMC and EC showed a mainly in regions of disturbed flow, for example, the inner surprisingly high heterogeneity of GPCR expression, and reporter curvature of the aortic arch28, we used Gprc5b-bgal reporter mice analysis, as well as studies on the protein level confirmed these to investigate the localization of spontaneously dedifferentiating findings. Studies in other fields, mainly developmental biology, SMC in vivo. Immunohistochemical analysis of the expression suggest that this is not a specialty of GPCRs, but is also of bgal and SMC marker a-smooth muscle actin (aSMA) in observed in other gene families17,18. These findings have major transverse section of the aortic arch (Fig. 8e) showed only sparse implications for pharmacotherapy, since current interpretations bgal expression in SMC of the outer curvature, but an enrichment of GPCR expression data rely on the assumption that all cells of a of bgal/aSMA-positive cells in the inner curvature (Fig. 8f,g). given population are equal, or at least comparable15,16,30,31. These data confirm the notion that GPCRs such as Gprc5b are Our data not only clearly disprove this assumption for the selectively expressed in SMC in atheroprone regions. We finally majority of GPCRs, they also open up the possibility to selectively investigated whether selective targeting of GPCRs that are target pathologically altered cells based on their specific GPCR specifically expressed in dedifferentiating SMao may be used to repertoire. modulate their functional state. Knockdown of Gprc5b resulted in We show, for example, that dedifferentiated SMao differ from freshly isolated SMao from ApoE-deficient mice in a significant normal SMao not only in the expression of typical markers increase in expression of Icam1 and Il6, indicating that this indicating inflammatory activation and dedifferentiation, but also receptor plays a modulatory role in inflammatory gene expression in their GPCR repertoire. Among those receptors that are in dedifferentiating SMC (Fig. 8h). preferentially expressed in dedifferentiating SMao are a number of Gs-coupled receptors with known anti-inflammatory and anti-proliferative properties, such as the prostacyclin receptor Discussion Ptgir or the VIP receptor Vipr2 (refs 32,33). It is tempting We report here the analysis of GPCR expression in primary to speculate that also other Gs-coupled receptors upregulated vascular cells on the single-cell level. Compared to conventional in dedifferentiating SMao will exert anti-proliferative effects, expression analysis in pooled cell RNA/cDNA, single-cell for example, the PACAP receptor Adcyap1r1, or the adenosine

Figure 5 | Endothelial GPCR pattern after acute inflammatory activation by LPS in vivo. (a–d) Analyses in brain EC (ECbr): (a) Heat map of GPCR expression in ECbr from healthy mice and LPS-treated mice (ECbrLPS) (52 and 22 cells from seven and four mice, respectively). Horizontal bars on the right side visualize expression frequency (in %) (for full data set, Supplementary Fig. 6); function-defining genes are shown in blue. (b) Average number of GPCRs expressed in individual ECbr from healthy or LPS-treated mice. (c) Heat map indicating dissimilarities between individual ECbr. K-means clustering identified two cell clusters that are colour-coded along the axes and correspond to ECbr from healthy and LPS-treated mice, respectively. (d) Fold difference in gene expression in ECbrLPS compared to all cells. (e–g) Analyses in lung EC (EClu) (48 and 25 cells from eight and four mice, respectively): (e) Heat map indicating dissimilarities between individual EClu. K-means clustering identified two cell clusters that are colour-coded along the axes and correspond to EClu from healthy and LPS-treated mice, respectively. (f) Fold difference in gene expression in ECluLPS compared to all cells. (g) Average number of GPCRs expressed in individual EClu from healthy or LPS-treated mice. (h–j) Comparison of LPS effects in EClu and ECbr: (h) T-SNE plot of k-means clustering data for different EC types with and without LPS treatment: cluster assignment is indicated by coloured numbers, cell type is indicated by symbol (each dot one cell; distance between dots indicates degree of similarity). (i,j) Comparative analysis of expression strength of selected GPCRs in different EC types. (k) Rearranged and extended heat map of ECbrLPS shown in a: Fpr1/Fpr2/Ccr1/C5ar1-expressing cells are indicated by red box. All expression data are calculated as 2(Limit of detection(LoD) Ct—sample Ct); LoD Ct was set to 24. Function-defining genes are shown in blue. Data in b,g,i,j are means±s.e.m.; comparisons were made using two-sample t-test. *Po0.05; **Po0.01; ***Po0.001.

NATURE COMMUNICATIONS | 8:15700 | DOI: 10.1038/ncomms15700 | www.nature.com/naturecommunications 9 ARTICLE NATURE COMMUNICATIONS | DOI: 10.1038/ncomms15700

ac Expression 25,000 frequ. (%) ) 20,000 ECao ECao ECao Apo16w ECao Apo16w 100 100 LoD ct – 15,000 Actb Myh11 Gapdh 100 100 Hprt 100 100 10,000 Vcam1 33 88 Icam1 33 81 Average Average 5,000 Up II6 0 25 expression (2 expression Sele 0 25 Hif1a 83 69 0 Cdh5 100 100 low 100 94 e Pecam1 30 SMao SMsk Pdgfb 92 63

Function 100 63 ;Myh11 Kdr pos Edn1 50 31 75 38 aortic cells DII4 20 b Cdh5 Cd97 100 81 100 Gpr56 100 56 ** S1pr1 100 88 Eltd1 100 69 80 92 56 10

Gpr116 GPCRs per cell Gpr4 33 0 60 Gpr21 25 0

Down 67 0 P2ry12 0

GPCR 50 6 40 P2ry2 Gabbr1 50 6 Cxcr4 50 25 ECao ECao

20 Cxcr7 75 25 Apo16w

Expression frequency (%) Gpr107 92 6 0 Gprc5a 33 0 Prokr1 25 0

Lgr6 33 13

Eltd1 Htr2a Mrgrf S1pr1 Gpr56 25 38

Gpr116 Ccrl2 S1pr3 0 19 Up Down Darc 0 13 ECsk ECbr SMao Gpr153 0 38 pos low Cdh5 ;Myh11 aortic cells 0 50 100 150 200

d 104 ECao ECaoApo16w ** * 3 ** * * *

10 ** 0.07 * * ) * * *

2 0.06 ** *

10 0.07 0.07 ** 0.06 0.05 LoD Ct –

(2 101 Gene expression

100 0 II6 Kdr DII4 Hprt Sele Actb Darc Gpr4 Eltd1 Edn1 Hif1a Ccrl2 Htr2a Cdh5 Cd97 Cxcr4 Pdgfb S1pr1 P2ry2 S1pr3 Icam1 Cxcr7 Gpr21 Gpr56 Prokr1 Gapdh Vcam1 P2ry12 Gprc5a Gabbr1 Gpr153 Gpr116 Gpr107 Pecam1

Up Down Down Up Identity/function GPCR f 100 Acute activation (LPS) Chronic activation (ApoE –/–, 16 wk HFD) 10

1 n.e. Activation-induced change in Activation-induced gene expression (fold change) (fold gene expression 0.1 F2r Kdr Sele Darc Ptafr Eltd1 Edn1 Hif1a Ccrl2 Cdh5 Cd97 Cxcr4 Pdgfb Calcrl S1pr1 P2ry2 Icam1 Cxcr7 Lphn1 Gpr56 Lphn2 Gapdh Vcam1 Tbxa2r Gprc5a Gprc5b Gabbr1 Gpr111 Gpr124 Gpr153 Gpr116 Gpr107 Pecam1 Adora2a Gpr137b

Identity/function GPCR

Figure 6 | Endothelial GPCR pattern in atherosclerosis. (a) Average expression strength of SM marker Myh11 in SMC from aorta (SMao) or skeletal muscle vasculature (SMsk), or in Cdh5-positive aortal cells. (b) Percentage of cells expressing selected GPCRs in freshly isolated EC from skeletal muscle (ECsk) or brain (ECbr), as well as in Cdh5pos; Myh11low aortal cells or aortal SMC (SMao). (c) Heat map of GPCR expression in aortal EC from healthy mice (ECao) and ApoE-deficient mice kept for 16 weeks on high-fat diet (ECaoApo16 w) (12 and 16 cells from four to six mice, respectively). Horizontal bars on the right side visualize expression frequency (in %) (for full data set, Supplementary Fig. 6). (d) Comparative analysis of gene expression strength in ECao and ECaoApo16w. (e) Average number of GPCRs expressed in individual ECao from healthy and atherosclerotic mice. (f) Changes in endothelial gene expression in response to acute inflammatory activation by LPS or chronic inflammatory activation in atherosclerotic mice (n.e., not expressed). All expression data are calculated as 2(Limit of detection(LoD) Ct—sample Ct); LoD Ct was set to 24. Function-defining genes are shown in blue. Data in a,d,e, are means±s.e.m.; comparisons in d,e were performed using two-sample t-test. *Po0.05; **Po0.01.

10 NATURE COMMUNICATIONS | 8:15700 | DOI: 10.1038/ncomms15700 | www.nature.com/naturecommunications NATURE COMMUNICATIONS | DOI: 10.1038/ncomms15700 ARTICLE

abc Expression Cluster SMao 40 150 frequ. (%) WT ApoE–/– #1 0 wks HFD 16 wks HFD *** 100 #2 0 wks 16 wks 30 Myh11 100 100 Acta2 100 100 50 Vcam1 10 80 20 Icam1 10 56 0 Cell type Function & identity II6 350 SMao S1pr3 864 –50 GPCRs per cell 10

Gprc5c 10 80 t-SNE dimension 1 healthy Average number of number Average Gprc5b 13 68 SMao Avpr1a 014 –100 Apo16wk Ednrb 210 0 Adcyap1r1 310 Adora2a 714 SMao SMao –100 –50 0 50 100 150 Ptger2 38 Apo16w t-SNE dimension 2 Ptgfr 36 d S1pr1 520 3.0 Cxcr4 28 P2ry14 514 2.5 Olfr78 236 Ptgir 17 54 2.0 GPCR Ccrl2 47 74 Gpr124 35 72 1.5 Pth1r 33 54 Gpr133 30 42 1.0 Gpr19 828 change Fold

Gpr153 40 64 all cluster 1 versus 0.5 Cmklr1 60 90 Ednra 43 92 0

Cxcr7 27 74 II6 Lgr6 Ptgir Ptgfr Vipr2 Lgr6 98 90 Ccrl2 Acta2 Cxcr4 S1pr1 Ednrb S1pr3 Icam1 Cxcr7 Olfr78 Mki67 Myh11 Ptger2 Vcam1 Avpr1a P2ry14 Gprc5c Gprc5b Adra1d 95 90 Adra1d Adora2a

0 500 1,000 1,500 2,000 Adcyap1r1

ef 100

80

60

40 GPCRs KLF5 TCFCP2I1 TFAP2A(var.3) TFAP2C(var.3) TFAP2B(var.2) TP63 TFAP2C(var.2) RARA(var.2) NFKB2 HINFP RARB(var.2) ZEB1 MZF1 INSM1 HSF1 HSF4 HSF2 ZBED1 BCL6B BCL6 EHF NR2F6(var.2) T ESRRB SREBF1 ESRRA TBX19 NFE2 TAL1::TCF3 ZBTB18 CTCF RORA EWSR1-FLI1 ATOH1 GLIS3 NFE2I2 TBX1 FOSL1 NEUROG1 JUND DUX downreg. 20 upreg.

Expression frequency (%) TFs enriched in promoters TFs enriched in promoters 0 of upregulated GPCRs of downregulated GPCRs

II6 –3 0 3 Ptgir Cxcr7 S1pr1 S1pr3 Olfr78 Ednrb Icam1 Vcam1 Gprc5c Gprc5b

Adcyap1r1 SMao SMaoApo0w Under- Over- Represented SMaoAged SMaoApo16w Figure 7 | Disease-dependent changes within subgroups. (a) Heat map of GPCR expression in SMao from healthy mice compared to ApoE-deficient mice kept for 16 weeks on high-fat diet (60 and 50 cells from eight to six mice, respectively). Horizontal bars on the right side visualize expression frequency (in %) (for full data set, Supplementary Fig. 6). (b) Average number of GPCRs expressed in individual SMao from healthy and atherosclerotic mice. (c) T-SNE representation of k-means clustering data from healthy (circles) and atherosclerotic (squares) SMao. (d) Genes differentially expressed in cluster 1 compared to all cells. (e) Expression frequency of selected GPCRs (left) and function-defining genes (right) in SMao of healthy mice aged 2–4 months (SMao, 60 cells from eight mice), healthy mice aged 16 months (SMaoAged, 32 from six mice), ApoE-deficient mice on normal diet (SMaoApo0w, 34 cells from six mice) or after 16 weeks of high-fat diet (SMaoApo16w, 50 cells from six mice). (f) Selection of TF binding sites significantly (Po0.05) enriched (red) or depleted (green) in the promoters of GPCRs downregulated or upregulated in dedifferentiating SMao (cluster 1 from c,d) compared to a global promoter background set. Colour scale represents a rank based z score; for full list see Supplementary Table 5. Data in b are mean±s.e.m.; comparisons were performed using two-sample t-test. ***Po0.001. receptor Adora2a. In line with this notion, PACAP was shown to studies analysed the posttranslational regulation of GPCRs by inhibit SMC proliferation34, and enhanced SMC proliferation was phosphorylation, internalization or dimerization, their transcrip- observed in Adora2a-deficient mice35. Furthermore, it will be tional control is little understood. To address the mechanisms particularly interesting to investigate whether those orphan regulating GPCR expression in healthy and dedifferentiating receptors that are upregulated in dedifferentiating SMC, for SMao, we analysed TF binding sites in promoters of GPCRs example, Gpr39, Gpr124, Gpr153 or Gprc5b have the potential to upregulated in dedifferentiating SMao. The promoters of these positively or negatively regulate SMC differentiation. In support GPCRs were, among others, enriched in binding sites for TFs of this idea, we found that knockdown of Gprc5b enhanced AP2, KLF5, RARA/RARB, HSF1/2/4 and NF-kB2. Some of these proinflammatory gene expression in freshly isolated SMao, TFs have been implicated in SMC dedifferentiation: KLF5 suggesting that this receptor negatively modulates inflammatory has been shown to promote proliferation of vascular SMC36, gene expression in SMC. whereas activation of retinoic acid receptor a (RARA) increased How the GPCR repertoire of an individual vascular cell is migration and tissue-type plasminogen activator activity in shaped and how stable it is over time, is unclear. While numerous SMC37. Both HSF1 and NF-kB show increased activity in

NATURE COMMUNICATIONS | 8:15700 | DOI: 10.1038/ncomms15700 | www.nature.com/naturecommunications 11 ARTICLE NATURE COMMUNICATIONS | DOI: 10.1038/ncomms15700

a b SMao c Gene eGFP Lgr6 Myh11 Adra1d 0.8 Acta2 Acta2 Vcam1 Icam1 Myh11 eGFP

Function Col1a2 & identity 2 Col3a1 coefficient Lgr6 Spearman #2 Adra1d 0.3 Cxcr7 Col1a2 Gpr39 Col3a1 Cxcr7 Adora2a Lpar1

1 Vipr2 Gpr137b Vcam1

Dissimilarity High Gpr153 Ptgir Gpr39 Gpr124 Gpr124 Ednra

GPCR Lpar1 #1 Ednra Adora2a Icam1 Gprc5b Cmklr1 Vipr2 Gprc5b Gpr153 #3 0 Cmklr1 #3 #1 #2 Low Gpr137b Ptgir 0 500 1,000 1,500 2,000 Cluster3 d Spontaneously dedifferentiating SMao 10 Atherosclerotic SMao

1 (fold change) (fold in dedifferentiating SMao in dedifferentiating Changes in gene expression 0.1 Lgr6 Ptgir Ptgfr Vipr2 Ccrl2 Pth1r Lpar1 Acta2 Cxcr4 Ednra S1pr1 Ednrb Icam1 S1pr3 Cxcr7 Olfr78 Gpr64 Gpr39 Myh11 Ptger2 Vcam1 Avpr1a Cmklr1 P2ry14 Gprc5c Gprc5b Adra1d Gpr124 Gpr153 Gpr137 Adora2a Gpr137b Adcyap1r1

e β α Aortic arch f gal, DAPI SMA

Outer curvature h Section plane Outer curvature 4 Outer curvature * Inner ) 3 curvature ct ΔΔ

(atheroprone) – Inner curvature Inner curvature 2 50 μm * g βgal, DAPI, αSMA, overlay βgal/αSMA 1 80 Normalized gene * (2 expression Outer curvature 60 0 II6 Icam1

40 Mki67 Myh11 Vcam1 Gprc5b SMA-pos.)  Inner curvature

(of 20

Gprc5b-pos. cells Gprc5b-pos. siScramble siGprc5b 0

Outer Inner Curvature Figure 8 | Functional subgroups within SMao. (a) Heat map indicating similarities/dissimilarities between 60 individual SMao. Cell clusters identified by k-means clustering are colour-coded along the axes. (b) Heat map of GPCR expression in SMao (cells sorted from left to right by clusters shown in a). (c) Graphical representation of Spearman’s rank correlation coefficients calculated for selected genes expressed in SMao (width of connecting line indicates strength of correlation). (d) Changes in gene expression in dedifferentiating SMC from healthy aortae or atherosclerotic aortae. (e–g) Immunohistochemical analysis of bgal and aSMA expression in transverse sections of the aortic arch of Gprc5b-bgal reporter mice (schematic diagram in e, exemplary photomicrographs in f, quantification in g.(h) Gene expression in SMao cultured for 7 days after knockdown of Gprc5b (normalized to Actb expression). Data in g,h are shown as mean±s.e.m.; comparisons were performed using two-sample t-test (g) or one-sample t-test (h)(n ¼ 4–6). *Po0.05.

12 NATURE COMMUNICATIONS | 8:15700 | DOI: 10.1038/ncomms15700 | www.nature.com/naturecommunications NATURE COMMUNICATIONS | DOI: 10.1038/ncomms15700 ARTICLE atherosclerotic vessels22,38, and NF-kB activation enhances Methods expression of inflammatory genes such as Vcam1 and reduces Experimental mice. All animal experiments were conducted in accordance with expression of SM-specific genes39. These data suggest that TFs the corresponding institutional guidelines and permission by the state of Hessen. C57BL/6J mice, ApoE-deficient mice25 and the double fluorescent reporter line implicated in the regulation of SMC dedifferentiation also control Gt(ROSA)26Sortm4(ACTB-tdTomato,-EGFP)Luo/Jpos (dTom/EGFP-reporter) (Stock changes in the GPCR repertoire, which in turn might modulate #007576)51 were purchased from the Jackson Laboratory. Mouse lines expressing the dedifferentiation process. recombinase Cre or the tamoxifen-inducible CreERT2 under control of the Our data also show that both SMC and EC express distinct EC-specific Cdh5 promoter (B6.FVB-Tg(Cdh5-cre)7Mlia/J) (Cdh5-Cre) or the SMC-specific Myh11 promoter (B6.FVB-Tg(Myh11-cre/ERT2)1Soff/J) GPCR repertoires depending on the vascular bed they originate (Myh11-CreERT2) were described previously52,53. Gprc5btm1a(EUCOMM)Wtsi from. SMC from vascular beds rich in resistance arteries, here (EPD0534_1_A10) mice were obtained from EUCOMM/The Sanger Institute. SMsk and SMmes, express significantly more GPCRs than aortic Gabbr1tm1a(KOMP)Wtsi mice were generated from targeted ES cells (CSD76009, SMC, in particular more peptide hormone receptors and orphan KOMP Repository) by injection into C57BL/6J blastocysts. Mrgprftm1a mice were generated by targeting v6.5 ES cells using vector Mrgprftm107656a(L1_L2_Bact_P) receptors. Most of the peptide hormones in question have been (KOMP Repository) and consecutive injection of targeted ES cells into C57BL/6J shown to affect vascular tone: vasorelaxation is, for example, blastocysts. All lines were kept on the C57BL/6J background and if not otherwise mediated by the gastrointestinal hormones VIP and PACAP indicated both male and female mice were used at an age of 8–18 weeks. Mice were (acting on receptors encoded by Vipr1, Vipr2 and Adcyap1r1), housed under a 12 h light–dark cycle with free access to food and water and under by urocortin and corticotropin releasing hormone (acting on the pathogen-free conditions. Cre-mediated recombination was induced in Myh11-CreERT2 mice by i.p. gene product of Crhr2), by parathyroid hormone (acting on injection of tamoxifen dissolved in Miglyol 812 (1 mg per mouse per day, the receptor encoded by Pth1r), or by calcitonin gene-related Sigma T5648) on 5 consecutive days. To induce atherosclerosis development, peptide or adrenomedullin (acting on the gene product ApoE-deficient mice were fed a high-fat diet (21% butter fat, 1.5% cholesterol of Calcrl)40–44; all these receptors are G coupled45. (Ssniff Cat. TD88137)) for 16 weeks. Animals were killed by i.p. injection of s ketamine (180 mg kg–1, Pfizer) and xylazine (16 mg kg–1, Bayer) and perfused via Vasoconstriction, in contrast, is induced by peptide mediators the left ventricle with phosphate-buffered saline (PBS). In some cases LPS serotype such as endothelin-1, angiotensin II, vasopressin or neuropeptide 0111:B4 (Sigma-Aldrich L2630) was injected i.p. at 10 mg kg–1 12 h before killing. Y acting on the Gi/o-, Gq/11-orG12/13-coupled receptors encoded by Ednra, Ednrb, Agtr1a, Avpra1a and Npy1r46–48. The Single-cell quantitative real-time PCR. For single-cell expression analysis, second-largest group of GPCRs with preferential expression in B1,500 cells were loaded in a volume of 5 ml onto the microfluidic C1 Single-Cell SMsk/SMmes are the orphan receptors, for example, Gpr19, Auto Prep System (5–10 mm mRNA Arrays, Fluidigm, San Francisco, CA, USA), Gpr21, Mrgprf, Gprc5b, Gprc5c, Gpr124, Gpr126 or Lphn1. This followed by RNA isolation and cDNA synthesis according to the manufacturer’s suggests that also orphan GPCRs expressed in SMsk are potential protocol. cDNAs derived from visually empty chambers or chambers containing targets for modulation of blood pressure, but due to the lack of more than one cell were excluded from further analysis; also cDNAs that showed poor expression of reference gene Hprt in conventional RT-PCR were excluded. known agonists/antagonists so far no data are available with High-throughput quantitative PCR on single-cell cDNAs was performed on 96.96 respect to their function in regulation of vascular tone or other Dynamic Array IFCs on the BioMark system (Fluidigm) using Sso-Fast EvaGreen SMC functions. Supermix low ROX (BioRad, Hercules, CA, USA) and Delta Gene primer assays Also EC show, depending on their anatomical location, (Fluidigm) as listed in Supplementary Table 1. Primers used for the single-cell analysis of human genes are shown in Supplementary Table 2. Only single-cell remarkable differences in the GPCR repertoire, and also their cDNAs negative for lineage markers Ptprc (CD45R, all leukocytes), Itgam (CD11b, responses to acute inflammatory activation differ. Brain EC, for monocytes/macrophages), Cd4 (CD4 T cells), Cd8 (CD8 T cells), Cd19 (B cells), example, were characterized by an upregulation of chemokine Ly6g (neutrophils), Cdh1 (E-Cadherin, epithelial cells), Tnni2 (skeletal muscle), receptor Darc and orphan receptor Gpr153, a response that but positive for Gapdh, Myh11 (for SMC), or Cdh5 (for EC) were included into analyses (exception: Cdh5pos; Myh11low ECao). Because C1 cDNA samples are was absent in lung EC. In line with this finding it was recently potentially contaminated with genomic DNA, intron-spanning primer design was shown that DARC is upregulated in brain EC during neuro- used for all genes. The limit of detection for the BioMark HD System has been inflammation, where it shuttles inflammatory chemokines across estimated to be at a Ct value of 24 cycles (Limit of detection (LoD) Ct); all sample 49,50 Ct values were therefore subtracted from the (LoD) Ct using the formula: gene the blood-brain barrier . The role of GPR153 in activated (LoD Ct—sample Ct)54 brain EC, in contrast, is completely unclear. Interestingly, we also expression ¼ 2 . detected a small subgroup of brain EC that were characterized by a myeloid-like GPCR expression pattern, but were devoid of any Tissue digestion and cell sorting. Animals were killed, perfused with PBS and myeloid lineage markers. The function of this subpopulation is different tissues (lung, skeletal muscle of lower limbs, brain, mesentery, whole aorta currently unclear, but the fact that expression of these GPCRs was including common carotid arteries) were dissected, minced and enzymatically digested for 90–120 min while shaking at 37 °C in a digestion mix containing negatively correlated with expression of Icam1 or chemokine collagenase II (2 mg ml–1; Worthington), elastase-I (0.04 mg ml–1; Sigma), and receptors involved in leukocyte trafficking, such as Darc or DNase1 (5 U ml–1; New England Biolabs). For lung digestion, also dispase II Cxcr7(ref. 50), suggests that this population is less supportive of (1.2 units per ml; Sigma) was added to the mix. Cell suspensions were serially leukocyte extravasation than other LPS-activated ECbr. It is also filtered through 70 and 40 mm cell strainers followed by washing twice with PBS. Cells from Cdh5-Crepos; dTom/EGFP-reporterpos mice or Myh11-CreERT2pos; interesting to note that chronic inflammatory activation during dTom/EGFP-reporterpos mice were sorted on a JSAN cell sorter (Bay Biosciences, atherosclerosis results in other changes than acute activation Japan) based on their EGFP expression; in other cases antibodies directed against by LPS, for example, with respect to atypical chemokine CD31 (Serotec MCA2388PE) or CD144-PE (ebioscience #12144180) were used to receptor Cxcr7, or orphan GPCRs Gpr111, Gpr107, Gprc5a and identify EC. Gprc5b. It is also noteworthy that ECao from atherosclerotic aortae showed reduced expression of endothelial genes such as Bioinformatic analysis of single-cell RT-PCR data. RT-PCR-based expression Cdh5, Pecam1, Gpr116 or Gpr56, suggesting that EC, very much values for individual cells were analysed by customized functions from the RaceID like SMC, undergo dedifferentiation in atherosclerotic aortae R package18. For k-means clustering, we utilized the clustexp and clustheatmap in vivo. functions; cluster specific genes (Po0.05, according to expected transcript count probability from binomial testing, see Methods section from18 were exported by a Taken together, our results show that expression profiling on customized clustdiffgenes function. Graphs show fold changes (41.5 or o0.7) the single-cell level allows the identification of receptors that are from cluster specific genes. T-SNE plots were generated by the plottsne function. predominantly or selectively expressed on pathologically relevant Heat maps based on RT-PCR expression data were generated in Perseus software55. vascular subpopulations. Understanding the GPCR profile of The correlation between expression of individual genes was determined using Spearman’s rank correlation coefficient; graphical representations of Spearman’s these cells will not only significantly enhance our knowledge rank correlation coefficients were generated using Cytoscape56. The width of a about the pathomechanisms of disease, it will also allow a more connector indicates the strength of the correlation; only correlation coefficients selective pharmacological targeting of these cells. 40.3 are displayed.

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To investigate the potential role of transcription factors (TFs) in cell Immunohistochemical analyses Aortic arches were cryosectioned transversally 57 . type-specific GPCR sets, we utilized the pscan tool . We investigated the (10 mm) and fixed with ice-cold acetone for 10 min. O.C.T. tissue freezing medium promoter region of GPCRs within a given set at a size of À 950 to þ 50 bp (Sakura) was removed by washing with PBS and sections were immunostained with around the respective transcription start site and tested for significantly (Po0.05) biotinylated anti-a-smooth muscle actin (aSMA) antibody (1:100, Abcam overrepresented/underrepresented TF binding sites listed in the current Jaspar ab125057) and chicken anti--galactosidase (1:400, Abcam ab9361) overnight. 58 2016 release (http://jaspar.genereg.net/) compared to a global promoter set of After washing, antibody binding was detected using strepatividin-alexa 647 the mouse organism. Resulting P values were z transformed and illustrated in a (ThermoFischer, S32357) and goat anti-chicken IgG (H þ L)-Alexa-568 multi column heat map generated by the heatmap2 R function (package gplots, (ThermoFischer, A11041) (both 1:200). 40,6-diamidin-2-phenylindol (DAPI) was version 3.01). used to label cell nuclei.

Single-cell mRNA sequencing and expression analysis. Single-cell Flow cytometric analysis. b-galactosidase expression in murine aortic SMC was transcriptome analysis was performed on a C1 Autoprep station (Fluidigm) using analysed using the FlouReporter lacZ flow cytometry kit (ThermoFischer) with 5–10 mm mRNA arrays and standard protocols. In total, 15,000 events sorted on a propidium iodide to identify viable cells and anti-aSMA antibody (ebioscience, JSAN swift sorter were suspended in 10 ml resuspension buffer (PBS þ 0.5% bovine #53976080) to identify SMC. For antibody-mediated detection of GPCR serum albumin þ 2 nM EDTA, sterile filtered) and further diluted (6:4) in expression, aortae of wild-type mice were digested, fixed in 0.01% formaldehyde suspension buffer. A volume of 3 ml was loaded to the C1 Array while remaining and permeabilized using Tween20 (0.5% v/v in PBS), followed by incubation of cells (B10,000) were used for total RNA isolation using mRNeasy micro kit resulting single-cell suspensions with PE- or FITC-labelled antibodies directed (Qiagen) combined with on-column DNase digest (Qiagen). RNA was against aSMA (ebiosciences) and APC-labelled antibodies directed against quantified by Qubit HS RNA Assay (Thermo Fisher) and used for tube control. receptors Cmklr1 (Miltenyi), Ccrl2 (R&D), Cxcr7 (R&D), Celsr2 (R&D) 6 Pre-amplification and cDNA synthesis were done with Smarter ultra-low RNA Kit (in all cases 10 ml antibody per 10 cells per 200 ml). For each GPCR-specific (Clontech) without changes to the standard protocol. cDNA obtained from C1 antibody the corresponding isotype control was used. Analyses were performed on system was quantified using PicoGreen assay (Thermo Fisher) and diluted to a FACS Canto II (Becton Dickinson) and data were analysed by FlowJo software 0.1–0.3 ng ml–1. Picking of positive cDNA samples and library preparation were (Tree Star). done with NGS Express pipetting robot (Perkin Elmer) using custom made protocols. Barcoded and amplified libraries were pooled in groups of 16 libraries General statistical analyses Data are presented as means±s.e.m. if not otherwise for final SRRI-bead based cleanup and quantified by Qubit HS dsDNA Assay . indicated. Comparisons between two groups were performed using two-sample (Thermo Fisher) and BioAnalyzer 2100 HS DNA Assay (Agilent). Sequencing was t-test; normalized data (control group set to 1) were analysed by one-sample t-test. performed on Nextseq500 Sequencer (Illumina) using v2 chemistry and High P values are indicated as follows: *P 0.05; **P 0.01; ***P 0.001. Output Flow Cell with 75 bp single end protocol. Raw data files were trimmed o o o using Reaper with a quality cutoff of 53 (length 20 bp, prefix 50 bp) and a minimum clean read length of 50 bp. Reads were then mapped to the genome (mm10) using Data availability. Single-cell RNA-Seq data have been deposited in GEO database STAR. FeatureCounts was used to assign reads to genes from the Gencode vM6 (https://www.ncbi.nlm.nih.gov/geo, under the accession code GSE97955. Full data annotation. Genes with less than 50 counts across all cells were discarded before sets generated during the current study are available from the corresponding 59 normalization. The knn.error.models function from SCDE was used to construct author on reasonable request. cell-specific error models by evaluating the gene counts for a observed cell versus the expected gene counts from the k most similar cells. The parameter k was chosen to resemble roughly three subpopulations. Estimated fragments References per million mapped reads (FPM, in log scale) were then obtained using the 1. Rosenbaum, D. M., Rasmussen, S. G. & Kobilka, B. K. The structure and scde.expression.magnitude function and are given in Supplementary Data 1. function of G-protein-coupled receptors. Nature 459, 356–363 (2009). 2. Vassilatis, D. K. et al. The G protein-coupled receptor repertoires of human and mouse. Proc. Natl Acad. Sci. USA 100, 4903–4908 (2003). NanoString analysis of GPCR expression in bulk RNA. NanoString analyses 3. Ngo, T. et al. Identifying ligands at orphan GPCRs: current status using were performed as described previously60,61. In brief, 250–500 ng RNA from sorted structure-based approaches. Br. J. Pharmacol. 173, 2934–2951 (2016). cells was applied in a total volume of 30 ml in the assay. Barcodes were counted for 4. Wise, A., Jupe, S. C. & Rees, S. The identification of ligands at orphan B1,150 fields of view per sample. Counts were first normalized to the geometric G-protein coupled receptors. Annu. Rev. Pharmacol. Toxicol. 44, 43–66 (2004). mean of the positive control spike count, then a background correction was done 5. Insel, P. A., Tang, C. M., Hahntow, I. & Michel, M. C. Impact of GPCRs in by subtracting the mean þ two s.d. of the eight negative control counts for each clinical medicine: monogenic diseases, genetic variants and drug targets. lane. Data were not normalized to reference genes because none of the reference Biochim. Biophys. Acta 1768, 994–1005 (2007). genes showed sufficiently stable expression in all cell types according to the 6. Salazar, N. C., Chen, J. & Rockman, H. A. Cardiac GPCRs: GPCR signaling in geNorm algorithm. Values that were o20 were fixed to background level. healthy and failing hearts. Biochim. Biophys. Acta 1768, 1006–1018 (2007). 7. Heng, B. C., Aubel, D. & Fussenegger, M. 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Gene expression in cultured SMao was analysed using the Universal ProbeLibrary System (Roche, Basal, Switzerland) with the following permeability. Physiol. Rev. 86, 279–367 (2006). primer pairs: 13. Wootten, D., Christopoulos, A. & Sexton, P. M. Emerging paradigms in GPCR Actb (probe #15): Fwd: 50 AAATCGTGCGTGACATCAAA 30/Rev: 50 allostery: implications for drug discovery. Nat. Rev. Drug Discov. 12, 630–644 TCTCCAGGGAGGAAGAGGAT 30; (2013). Acta2 (probe #80): Fwd: 50 TCTGGACTTTGAAAATGAGATGG 30/Rev: 50 14. Jacobson, K. A. New paradigms in GPCR drug discovery. Biochem. Pharmacol. CCCGTCAGGCAGTTCGTA 30 98, 541–555 (2015). Icam1 (probe #20): Fwd: 50 CGTGGGGAGGAGATACTGAG 30/Rev: 50 15. Regard, J. B., Sato, I. T. & Coughlin, S. R. Anatomical profiling of G GTGATCTCCTTGGGGTCCTT 30 protein-coupled receptor expression. Cell 135, 561–571 (2008). Vcam1 (probe #50): Fwd: 50 CCGGTCACGGTCAAGTGT 30/Rev: 50 16. Hakak, Y., Shrestha, D., Goegel, M. C., Behan, D. P. & Chalmers, D. T. Global CAGATCAATCTCCAGCCTGTAA 30 analysis of G-protein-coupled receptor signaling in human tissues. FEBS Lett. Gprc5b (probe #64): Fwd: 50 GCCTTCTCAATGGATGAACATA 30/Rev: 50 550, 11–17 (2003). CAAGCTGCTGGGCTTCTT 30 17. Buettner, F. et al. Computational analysis of cell-to-cell heterogeneity in Expression of Myh11, Mki67 and Il6 was determined using LightCycler 480 single-cell RNA-sequencing data reveals hidden subpopulations of cells. Nat. SYBR Green I Master (Roche) and primers listed in Supplementary Table 1. Biotechnol. 33, 155–160 (2015).

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NATURE COMMUNICATIONS | 8:15700 | DOI: 10.1038/ncomms15700 | www.nature.com/naturecommunications 15 https://doi.org/10.1038/s41467-019-09334-3 OPEN Author Correction: Single-cell profiling reveals heterogeneity and functional patterning of GPCR expression in the vascular system

H. Kaur1, J. Carvalho1, M. Looso2, P. Singh1, R. Chennupati1, J. Preussner2, S. Günther3, J. Albarrán-Juárez1, D. Tischner1, S. Classen4, S. Offermanns1,5 & N. Wettschureck1,5

Correction to: Nature Communications https://doi.org/10.1038/ncomms15700; published online 16 June 2017

The original version of this Article omitted the following from the Acknowledgements: 1234567890():,;

‘This project was supported by CRC128/Project A03 of the Deutsche Forschungsgemeinschaft (DFG).’

This has not been corrected in either the PDF or HTML versions.

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

© The Author(s) 2019

1 Department of Pharmacology, Max Planck Institute for Heart and Lung Research, Ludwigstr 43, 61231 Bad Nauheim, Germany. 2 ECCPS Bioinformatics Facility, Max Planck Institute for Heart and Lung Research, Ludwigstr 43, 61231 Bad Nauheim, Germany. 3 ECCPS Deep sequencing platform, Max Planck Institute for Heart and Lung Research, Ludwigstr 43, 61231 Bad Nauheim, Germany. 4 Harvey Vascular Centre, Kerckhoff-Klinik, Benekestraβe2–8, 61231 Bad Nauheim, Germany. 5 Medical Faculty, J.W. Goethe University, Theodor-Stern-Kai 7, 60590 Frankfurt, Germany. Correspondence and requests for materials should be addressed to N.W. (email: [email protected])

NATURE COMMUNICATIONS | (2019) 10:1448 | https://doi.org/10.1038/s41467-019-09334-3 | www.nature.com/naturecommunications 1