Despite the medical importance of G protein-coupled receptors (GPCRs), in vivo cellular heterogeneity of GPCR signaling and downstream transcriptional responses are not understood. We report the comprehensive characterization of transcriptomes (bulk and single-cell) and chromatin domains regulated by sphingosine 1-phosphate receptor-1 (S1PR1) in adult mouse aortic endothelial cells. First, S1PR1 regulates NFκB and nuclear glucocorticoid receptor pathways to suppress inflammation-related mRNAs. Second, S1PR1 signaling in the heterogenous endothelial cell (EC) subtypes occurs at spatially-distinct areas of the aorta. For example, a transcriptomically distinct arterial EC population at vascular branch points (aEC1) exhibits ligand-independent S1PR1/ß-arrestin coupling. In contrast, circulatory S1P-dependent S1PR1/ß-arrestin coupling was observed in non-branch point aEC2 cells that exhibit an inflammatory gene expression signature. Moreover, S1P/S1PR1 signaling regulates the expression of lymphangiogenic and inflammation-related transcripts in an adventitial lymphatic EC (LEC) population in a ligand-dependent manner. These insights add resolution to existing concepts of endothelial heterogeneity, GPCR signaling and S1P biology.
Abstract Despite the medical importance of G protein-coupled receptors (GPCRs), in vivo cellular heterogeneity of GPCR signaling and downstream transcriptional responses are not understood. We report the comprehensive characterization of transcriptomes (bulk and single-cell) and chromatin domains regulated by sphingosine 1-phosphate receptor-1 (S1PR1) in adult mouse aortic endothelial cells. First, S1PR1 regulates NFkB and nuclear glucocorticoid receptor pathways to suppress inflammation-related mRNAs. Second, spatially distinct S1PR1 signaling in the aorta is associated with heterogenous endothelial cell (EC) subtypes. For example, a transcriptomically distinct arterial EC population at vascular branch points (aEC1) exhibits ligand- independent S1PR1/ß-arrestin coupling. In contrast, circulatory S1P-dependent S1PR1/ß-arrestin coupling was observed in non-branch point aEC2 cells that exhibit an inflammatory signature. Moreover, an adventitial lymphatic EC (LEC) population shows suppression of lymphangiogenic and inflammation-related transcripts in a S1P/S1PR1-dependent manner. These insights add resolution to existing concepts of GPCR signaling and S1P biology.
Michel V. Levesque and Timothy Hla Vascular Biology Program, Boston Children's Hospital and Department of Surgery, Harvard Medical School, Boston, Massachusetts 02115, USA Correspondence: timothy.hla{at}childrens.harvard.edu
Article Figures and data Abstract Introduction Results Discussion Materials and methods Data availability References Decision letter Author response Article and author information Metrics Abstract Despite the medical importance of G protein-coupled receptors (GPCRs), in vivo cellular heterogeneity of GPCR signaling and downstream transcriptional responses are not understood. We report the comprehensive characterization of transcriptomes (bulk and single-cell) and chromatin domains regulated by sphingosine 1-phosphate receptor-1 (S1PR1) in adult mouse aortic endothelial cells. First, S1PR1 regulates NFκB and nuclear glucocorticoid receptor pathways to suppress inflammation-related mRNAs. Second, S1PR1 signaling in the heterogenous endothelial cell (EC) subtypes occurs at spatially-distinct areas of the aorta. For example, a transcriptomically distinct arterial EC population at vascular branch points (aEC1) exhibits ligand-independent S1PR1/ß-arrestin coupling. In contrast, circulatory S1P-dependent S1PR1/ß-arrestin coupling was observed in non-branch point aEC2 cells that exhibit an inflammatory gene expression signature. Moreover, S1P/S1PR1 signaling regulates the expression of lymphangiogenic and inflammation-related transcripts in an adventitial lymphatic EC (LEC) population in a ligand-dependent manner. These insights add resolution to existing concepts of endothelial heterogeneity, GPCR signaling and S1P biology. Introduction Sphingosine 1-phosphate (S1P), a circulating lipid mediator, acts on G protein-coupled S1P receptors (S1PRs) to regulate a variety of organ systems. S1PR1, abundantly expressed by vascular endothelial cells (ECs), responds to both circulating and locally-produced S1P to regulate vascular development, endothelial barrier function, vasodilatation and inflammation (Proia and Hla, 2015). S1P binding to S1PR1 activates heterotrimeric Gαi/o proteins, which regulate downstream signaling molecules such as protein kinases, the small GTPase RAC1, and other effector molecules to influence cell behaviors such as shape, migration, adhesion and cell-cell interactions. Even though S1PR1 signaling is thought to evoke transcriptional responses that couple rapid signal transduction events to long-term changes in cell behavior, such mechanisms are poorly understood, especially in the vascular system. Subsequent to activation of Gαi/o proteins and RAC1, the S1PR1 C-terminal tail gets phosphorylated and binds to ß-arrestin, leading to receptor desensitization and endocytosis (Liu et al., 1999; Oo et al., 2007). While S1PR1 can be recycled back to the cell surface for subsequent signaling, sustained receptor internalization brought about by supra-physiological S1P stimulation or functional antagonists that are in therapeutic use leads to recruitment of WWP2 ubiquitin ligase and lysosomal/proteasomal degradation of the receptor (Oo et al., 2011). Thus, ß-arrestin coupling down-regulates S1PR1 signals. However, studies of other GPCRs suggest that ß-arrestin coupling can lead to biased signaling distinct from Gαi/o -regulated events (Wisler et al., 2018). Distinct transcriptional changes brought about by Gαi/o – and ß-arrestin-dependent pathways are not known. Studies of ß-arrestin and RAC1 knockout mice highlighted the unique physiological functions of these proteins in S1PR1 signaling. Deletion of S1pr1 or Rac1 in endothelium results in lethality at embryonic day (E)13.5 and E9.5, respectively (Allende et al., 2003; Tan et al., 2008). In contrast, mice with germline null alleles for barr1 (Conner et al., 1997) or barr2 (Bohn et al., 1999) survive without gross abnormalities while barr1-/-barr2-/- mice survive to term (Zhang et al., 2010). Our understanding of GPCR signaling in vivo, particularly with respect to direct transcriptional targets and spatial specificity of signaling, is limited. To address this, Kono et al. (2014) developed S1PR1 reporter mice (S1PR1-GS mice) which record receptor activation at single-cell resolution (Kono et al., 2014; Barnea et al., 2008). S1PR1-GS mice harbor one wild-type S1pr1 allele and one targeted knock-in allele, which encodes S1PR1-tTA and ß-arrestin-TEV protease fusion proteins separated by an internal ribosome entry sequence (Kono et al., 2014). Breeding the S1pr1 knock-in allele with the tTA-responsive H2B-GFP allele generates an S1PR1-GS mouse. In S1PR1-GS mice, the β-arrestin-TEV fusion protein triggers release of tTA from the C terminus of modified S1PR1 when β-arrestin-TEV and S1PR1-tTA are in close proximity. Free tTA enters the nucleus and activates H2B-GFP reporter gene expression. Since S1PR1-GS mouse embryonic fibroblast cells respond to S1P with an EC50 of 43 nM (Kono et al., 2014; Lee et al., 1998), the S1PR1 reporter system accurately reports S1PR1 activation. Indeed, structural and functional analyses of other GPCRs suggest that the C-terminal phosphorylation patterns determine the strength of ß-arrestin binding, which was accurately predicted by the ß-arrestin coupling (Zhou et al., 2017). The in vivo half-life of H2B-GFP protein is ~24 days in hair follicle stem cells (Waghmare et al., 2008). Therefore, GFP expression in this reporter mouse represents the cumulative record of S1PR1 activation in vivo. We previously showed that high levels of endothelial GFP expression (i.e. S1PR1/ß-arrestin coupling) are prominent at the lesser curvature of the aortic arch and the orifices of intercostal branch points (Galvani et al., 2015). In addition, inflammatory stimuli (e.g. lipopolysaccharide) induced rapid coupling of S1PR1 to ß-arrestin and GFP expression in endothelium in an S1P-dependent manner (Kono et al., 2014). These data suggest that the S1PR1-GS mouse is a valid model to study GPCR activation in vascular ECs in vivo. To gain insights into the molecular mechanisms of S1PR1 regulation of endothelial transcription and the heterogenous nature of S1PR1 signaling in vivo, we performed bulk transcriptome and open chromatin profiling of GFPhigh and GFPlow aortic ECs from S1PR1-GS mice. We also performed transcriptome and open chromatin profiling of aortic ECs in which S1pr1 was genetically ablated (S1pr1 ECKO) (Galvani et al., 2015). In addition, we conducted single-cell (sc) RNA-seq of GFPlow and GFPhigh aortic ECs. Our results show that S1PR1 suppresses the expression of inflammation-related mRNAs by inhibiting the NFκB pathway. Second, the high S1PR1 signaling ECs (GFPhigh cells) are more similar to S1pr1 ECKO ECs at the level of the transcriptome. Third, scRNA-seq revealed eight distinct aorta-associated EC populations including six arterial EC subtypes, adventitial lymphatic ECs, and venous ECs, the latter likely from the vasa vasorum. S1PR1 signaling was highly heterogenous within these EC subtypes but was most frequent in adventitial LECs and two arterial EC populations. Immunohistochemical analyses revealed spatio-temporal regulation of aortic EC heterogeneity. In lymphatic ECs of the aorta, S1PR1 signaling restrains inflammatory and immune-related transcripts. These studies provide a comprehensive resource of transcriptional signatures in aortic ECs, which will be useful to further investigate the multiple roles of S1P in vascular physiology and disease. Results Profiling the transcriptome of GFPhigh and GFPlow mouse aortic endothelium To examine S1PR1/ß-arrestin coupling in the aorta, we used the previously described S1PR1-GS (Kono et al., 2014) mouse strain. Mice heterozygous for the knock-in allele (S1pr1ki/+) are born at the expected Mendelian frequency (Figure 1—figure supplement 1A) and do not show phenotypic abnormalities (Figure 1—figure supplement 1B and C). However, homozygous mice (S1pr1ki/ki) showed an ~2 fold reduction in circulating lymphocytes and ~2 fold increase in lung vascular leakage of Evans Blue dye suggesting that hypomorphism of the fusion S1pr1 allele in the signaling mouse. Therefore, all subsequent experiments were performed using heterozygous S1pr1ki/+ mice harboring one allele of the H2B-GFP (Tumbar et al., 2004) reporter gene, which do not exhibit S1pr1 hypomorphic phenotypes. S1PR1 expression in aortic endothelium is relatively uniform (Galvani et al., 2015). However, S1PR1 coupling to ß-arrestin, as reported by H2B-GFP expression in S1PR1-GS mice, exhibits clear differences in specific areas of the aorta. For example, thoracic aortae of S1PR1-GS mice show high levels of GFP expression in ECs at intercostal branch points (Galvani et al., 2015) but not in ECs of control (S1pr1+/+) mice harboring only the H2B-GFP reporter allele (Figure 1A), confirming that GFP expression in aortic ECs is dependent on the S1pr1 knock-in allele. The first 2–3 rows of cells around the circumference of branch point orifices exhibit the greatest GFP expression (Figure 1A). In addition, heterogeneously dispersed non-branch point GFP+ ECs were also observed, including at the lesser curvature of the aortic arch (Figure 1A). Areas of the aorta that are distal (>~10 cells) from branch points, as well as the greater curvature, exhibit relatively low frequencies of GFP+ ECs (Figure 1A). GFP+ mouse aortic ECs (MAECs) are not co-localized with Ki-67, a marker of proliferation, suggesting that these cells are not actively cycling (Figure 1A). However, fibrinogen staining was frequently co-localized with GFP+ MAECs, suggesting that ß-arrestin recruitment to S1PR1 was associated with increased vascular leak (Figure 1A). These findings suggest sharp spatial differences in S1PR1 signaling throughout the normal mouse aortic endothelium. Figure 1 with 2 supplements see all Download asset Open asset High S1PR1/ß-arrestin coupling in normal mouse aortic endothelium exhibits transcriptomic concordance with S1PR1 loss-of-function. (A) H2B-GFP control and S1PR1-GS mouse thoracic aorta whole-mount en face preparations. Representative images from different regions of the aorta are presented and show H2B-GFP (GFP), VE-Cadherin (VEC) or CD31, Ki67 (N = 3) or Fibrinogen (N = 2) immunostaining. Scale bars are 50 µM. (B) FACS gating scheme used for isolation of GFPhigh and GFPlow MAECs showing the uncompensated CD31-PE and GFP channels. S1pr1 ECKO and WT MAECs were isolated using the GFPlow gate of this scheme (see Figure 1—figure supplement 1A). (C) Venn diagram showing differentially expressed transcripts in the GFPhigh vs. GFPlow and S1pr1 ECKO vs. WT MAECs comparisons. The number of transcripts individually or co-enriched (p-value<0.05) are indicated for each overlap (see Supplementary file 1). (D) Selected upstream factors identified by IPA analysis of GFPhigh vs. GFPlow (top) and S1pr1 ECKO vs. WT (bottom) MAEC comparisons. Activation Z-scores and P-values are indicated for each selected factor (see Supplementary file 2). (E) Expression heatmaps (row Z-scores) of the 159 S1pr1 ECKO up-regulated transcripts also differentially expressed between GFPhigh and GFPlow MAECs. Values represent individual replicates from comparison of S1pr1 ECKO vs WT (left) and GFPhigh vs GFPlow (right) and selected transcripts are labeled. For both RNA-seq experiments, three cohorts of mice were used for MAEC isolation and downstream statistical analyses (N = 3 for each experiment). For insight into the aortic endothelial transcriptomic signature associated with high levels of S1PR1/ß-arrestin coupling, we harvested RNA from fluorescent-activated cell sorted (FACS) GFPhigh and GFPlow MAECs and performed RNA-seq (Figure 1B). To identify genes that are regulated by S1PR1 signaling, we sorted MAECs from tamoxifen-treated Cdh5-CreERT2 S1pr1f/f (S1pr1 ECKO) and S1pr1f/f (S1pr1 WT) littermates (Figure 1—figure supplement 2A). As expected, GFPhigh MAECs showed an ~20 fold increase in eGFP transcripts relative to GFPlow MAECs (Figure 1—figure supplement 2B). We noted that GFPhigh, GFPlow, S1pr1 WT and S1pr1 ECKO MAECs each expressed endothelial lineage genes (Pecam1, Cdh5) and lacked hematopoietic and VSMC markers (Ptprc, Gata1, and Myocd), validating our MAEC isolation procedure (Figure 1—figure supplement 2C). Efficient CRE-mediated recombination of S1pr1 was confirmed in sorted MAECs from S1pr1 ECKO mice (Figure 1—figure supplement 2C). Differential expression analysis identified 1,103 GFPhigh-enriched and 1,042 GFPlow-enriched transcripts (p-value<0.05) (Figure 1C and Figure 1—figure supplement 2D; see also Supplementary file 1). In contrast, S1pr1 ECKO MAECs showed fewer differentially expressed genes (DEGs), with 258 up- and 107 down-regulated transcripts (Figure 1C and Figure 1—figure supplement 2E; see also Supplementary file 1). Intersection of these two sets of DEGs showed that only 9.5% (204 transcripts) were common (Figure 1C and Supplementary file 1), suggesting that the majority (~90%) of transcripts that are differentially expressed in MAECs from S1PR1-GS mice are not regulated by S1PR1 signaling. Rather, S1PR1/ß-arrestin coupling correlates with heterogenous EC subtypes in the mouse aorta. Among the 204 common DEGs, 151 were both S1pr1 ECKO up-regulated and enriched in the GFPhigh population (Figure 1C). In contrast, much lower numbers of transcripts were found in the intersection of GFPhigh and S1pr1 ECKO down-regulated (seven transcripts), GFPlow and S1pr1 ECKO up-regulated (eight transcripts) and GFPlow and S1pr1 ECKO down-regulated (38 transcripts) (Figure 1C) (detailed gene set overlaps are provided in Supplementary file 1). We computed the statistical significance of these gene set overlaps using the GeneOverlap R package (Shen et al., 2013). The GFPhigh:S1pr1 ECKO-up overlap was significant (151 transcripts, p-value=3.80E-126), as was the GFPlow:S1pr1 ECKO-down overlap (38 transcripts, p-value=1.3E-22), and the other two tested overlaps were not significant (p-value>0.3) (Figure 1—figure supplement 2F). These data suggest that the transcriptome of MAECs exhibiting high S1PR1/ß-arrestin coupling (GFPhigh) is more similar to that of S1pr1 ECKO. We used Ingenuity Pathway Analysis (IPA, Qiagen) to examine biological processes regulated by S1PR1 signaling and loss of function in MAECs. Transcripts involved in inflammatory processes were prominently up-regulated in both GFPhigh and S1pr1 ECKO MAECs (Figure 1D; see also Supplementary file 2). For example, positive tumor necrosis factor (TNF)-α, lipopolysaccharide, and interferon-γ signaling were observed in both S1pr1 ECKO and GFPhigh MAECs. In contrast, a negative glucocorticoid signature was observed in these cells (Figure 1D). Examples of differentially regulated transcripts are chemokines (Ccl2, Clc5, Ccl7, Ccl21c), cytokines (Il33, Il7), inflammatory modulators (Irf8, Nfkbie, Tnfaip8l1) and cyclooxygenase-2 (Ptgs2) (Figure 1E and Figure 1—figure supplement 2D and E). This suggests that S1PR1 suppresses inflammatory gene expression in mouse aortic endothelium. We noted that transcripts in the TGFß signaling pathway (Thbs1, Smad3, Bmpr1a, Col4a4, Pcolce2) were prominently down-regulated in the GFPhigh population (Figure 1D and Figure 1—figure supplement 2D). Furthermore, both GFPhigh and S1pr1 ECKO MAECs were enriched with Lyve1, Flt4, and Ccl21c transcripts, which encode proteins with well-defined roles in lymphatic EC (LEC) differentiation and function (Ulvmar and Mäkinen, 2016; Figure 1E, Figure 1—figure supplement 2G). Taken together, these data suggest that S1PR1 represses expression of inflammatory genes in aortic endothelium and that GFPhigh MAECs include aorta-associated LECs and are heterogeneous. Chromatin accessibility landscape of MAECs We used the assay for transposase-accessible chromatin with sequencing (ATAC-seq) (Buenrostro et al., 2013) to identify putative cis-elements that regulate differential gene expression between GFPhigh versus GFPlow and S1pr1 WT versus S1pr1 ECKO MAECs. ATAC-seq utilizes a hyper-active Tn5 transposase (Adey et al., 2010) that simultaneously cuts DNA and ligates adapters into sterically unhindered chromatin. This allows for amplification and sequencing of open chromatin regions containing transcriptional regulatory domains such as promoters and enhancers. After alignment, reads from three experiments were trimmed to 10 bp, centered on Tn5 cut sites, then merged. These merged reads were used as inputs to generate two peak sets (MACS2, FDR < 0.00001) of 73,492 for GFPlow MAECs and 65,694 for GFPhigh MAECs (Figure 2A). MAECs isolated from WT and S1pr1 ECKO mice harbored 93,859 and 76,082 peaks, respectively (Figure 2A). Peaks were enriched in promoter and intragenic regions (Figure 2—figure supplement 1A). We noted that the Cdh5 gene exhibited numerous open chromatin peaks, while Gata1 was inaccessible (Figure 2—figure supplement 1B). Furthermore, we observed a global correlation between chromatin accessibility and mRNA expression for all 20,626 annotated coding sequences (CDS's) in the NCBI RefSeq database (Figure 2—figure supplement 2). These data suggest that our ATAC-seq data is of sufficient quality for detailed interrogation. Figure 2 with 3 supplements see all Download asset Open asset S1PR1 loss-of-function and high levels of ß-arrestin coupling are associated with an NFκB signature in open chromatin. (A) Venn diagrams illustrating all peaks (FDR < 0.00001) identified after analysis of individual ATAC-seq replicates of GFPlow, GFPhigh, S1pr1 ECKO, and WT MAECs, and subsequent merging of these peaks into a single consensus peak set. (B) Volcano plots of all peaks for both the GFPhigh vs GFPlow and S1pr1 ECKO vs WT MAECs. Three individual experiments were performed for GFPlow vs GFPhigh and S1pr1 ECKO vs WT comparisons (N = 3). Differentially accessible peaks (DAPs) were determined using edgeR (FDR < 0.05, see Materials and methods) (colored dots). (C–F) Transcription factor (TF) binding motif enrichment analysis of DAPs. The DAPs were input to the HOMER 'findMotifsGenome.pl' script (see also Supplementary file 2) and observed vs expected frequencies of motif occurrances were plotted. (G–H) Graphs showing ATAC signal at predicted TF binding sites. ATAC-seq reads were centered on Tn5 cut sites, trimmed to 10 bp, and nucleotide-resolution bigwig files were generated using DeepTools with reads per genomic content (RPGC) normalization. Reads were subsequently centered on TF binding motifs identified in (C–F) and viewed as mean read densities across 600 bp windows. Differential chromatin accessibility analysis of GFPhigh versus GFPlow MAECs identified 501 peaks with reduced accessibility (GFPlow peaks) and 3612 peaks with greater accessibility (GFPhigh peaks) in GFPhigh MAECs (FDR < 0.05, Figure 2B and Supplementary file 3). For WT and ECKO counterparts, this analysis identified 303 peaks with reduced accessibility (S1pr1 WT peaks) and 472 peaks with enhanced accessibility (S1pr1 ECKO peaks) in S1pr1 ECKO MAECs (Figure 2B and Supplementary file 3). The ~7 fold higher number of GFPhigh-enriched peaks suggests that GFPhigh MAECs are more 'activated' (elevated number of chromatin remodeling events) and/or are a heterogeneous mixture of EC subtypes. To identify relevant transcription factors (TFs), we used the Hypergeometric Optimization of Motif EnRichment (HOMER) (Heinz et al., 2010) suite of tools to reveal over-represented motifs in each set of differentially accessible peaks (DAPs). GFPhigh peaks were enriched with p65-NFκB, AP-1, STAT3, SOX17, COUP-TFII, and NUR77 motifs (Figure 2C and Supplementary file 3). In contrast, GFPlow peaks showed reduced occurrence of these motifs (Figure 2D). S1pr1 ECKO peaks were enriched with p65-NFκB motifs, while S1pr1 WT peaks were markedly enriched with glucocorticoid response elements (GREs) and modestly enriched with STAT3, GATA2, ATF1, SOX17 and COUP-TFII motifs (Figure 2E and F). Examination of ATAC-seq reads centered on selected binding sites (p65, NUR77, COUP-TFII, ATF1, GATA2, and GRE) showed local decreases in accessibility at motif centers, suggestive of chromatin occupancy by these factors (Figure 2G and H). We used the ATAC-seq footprinting software HINT-ATAC (Li et al., 2019) to assess genome-wide putative chromatin occupancy by TFs. HINT-ATAC identified enhanced footprinting scores at NFKB1 and NFKB2 motifs in S1pr1 ECKO MAECs, whereas GFPhigh MAECs showed increased scores at RELA motifs and to a lesser extent at NFKB1 and NFKB2 motifs (Figure 2—figure supplement 3A and B). This analysis also identified motifs of the TCF/LEF family (LEF1, TCF7, TCF7L2) as GFPhigh-enriched, but not S1pr1 ECKO-enriched (Figure 2—figure supplement 3A–D). Consistent with HOMER analysis of DAPs, HINT-ATAC identified COUP-TFII, NUR77, TCF4, and SOX17 motifs as exhibiting greater footprinting scores in GFPhigh MAECs, while GFPlow MAECs showed enhanced putative chromatin occupancy at ATF1 motifs. Analysis of DAPs showed that only the p65-NFκB motif was commonly enriched between GFPhigh and S1pr1 ECKO MAECs. This observation is consistent with our RNA-seq analysis, which identified cytokine/NFκΒ pathway suppression by S1PR1 signaling in MAECs (Figure 1D). Enrichment of COUP-TFII, NUR77, and AP-1/bZIP motifs in open chromatin of GFPhigh MAECs, but not S1pr1 ECKO MAECs, further suggests that high levels of S1PR1/ß-arrestin coupling occurs in heterogenous populations of aortic ECs. Single-cell RNA-seq analysis of GFPhigh and GFPlow MAECs reveals eight distinct EC clusters Imaging studies demonstrated that GFPhigh MAECs are restricted to specific anatomical locations. To test the hypothesis that these represent specific EC subpopulations, we employed single-cell RNA-seq (scRNA-seq) on FACS-sorted GFPhigh and GFPlow MAECs. In total, 1152 cells were sequenced (768 GFPhigh and 384 GFPlow) using the Smart-seq2 protocol. An average of 300,000 aligned reads/cell were obtained and corresponded to ~3200 transcripts/cell. Cdh5 transcripts were broadly detected, consistent with endothelial enrichment of sorted cells (Figure 3—figure supplement 1A). S1pr1 and Arrb2 were also broadly detected (Figure 3—figure supplement 1A), suggesting that receptor activation rather than expression of these factors accounts for heterogenous reporter expression in MAECs. eGFP mRNA was primarily restricted to GFPhigh MAECs, particularly in the cluster designated aEC1 (Figure 3—figure supplement 1A). Analysis of GFPhigh and GFPlow MAECs using the velocyto/pagoda2 pipeline (R code in Source Code File 3) (Fan et al., 2016; La Manno et al., 2018) revealed nine clusters upon T-distributed stochastic neighborhood embedding (t-SNE) projection (Figure 3A). 6 of the nine clusters grouped together in a 'cloud', whereas three clusters formed distinct populations. We used hierarchical differential expression analysis to identify signature marker genes of each cluster (Figure 3B). Figure 3 with 4 supplements see all Download asset Open asset Single-cell RNA-sequencing of GFPhigh and GFPlow MAECs. (A) t-SNE projection from Pagoda2 multilevel clustering of 767 GFPhigh and 384 GFPlow MAECs. Dash-line circles highlight each of the nine clusters identified. Cells and cluster names are color-coded according to cluster assignment. (B) Dendrogram from hierarchical clustering and expression heatmap of selected genes. The dendrogram (top) reveals an upstream split between LEC, vEC, aEC1 and aEC2, aEC3, aEC4, aEC5, and aEC6 populations. The heatmap shows the gradient of expression, from low (white) to high (dark blue), for a selection of transcripts with distinctive expression patterns. (C–F) Expression of transcripts specific to VSMCs (C) lymphatic ECs (D), venous ECs (E) and arterial ECs (F) are shown on the t-SNE embedding. (G–J) Representative transcripts enriched in arterial EC (aEC) clusters 1 (G), 2 (H), 3 (I) and 4 (J) are shown on the t-SNE embedding. MAECs used for scRNA-seq were isolated from two independent cohorts of S1PR1-GS mice. Genes uniquely detected in one of the distinct clusters included vascular smooth muscle cell (VSMC)-specific transcripts such as Myh11, Myom1, and Myocd (Figure 3B and C; Figure 3—figure supplement 1B). Therefore, this cluster was designated VSMC-like as these cells may represent MAECs sorted along with fragments of VSMCs, or 'doublets' of ECs and VSMCs. Because these cells may represent contamination in an otherwise pure pool of aortic ECs, we omitted this VSMC-like cluster from subsequent analyses. The remaining eight EC clusters were further analyzed. Lymphatic EC (LEC) markers such as Flt4 (VEGFR3), Prox1, and Lyve1, as well as the venous marker Nr2f2 (COUP-TFII), were detected in a distinct cluster (Figure 3B and D; Figure 3—figure supplement 1B). A smaller but nonetheless distinct cluster of ECs was also enriched with Nr2f2 transcripts but lacked lymphatic markers, suggesting that these cells are of venous origin (Figure 3B and E; Figure 3—figure supplement 1B). Arterial lineage markers Sox17, Gja5 and Notch4 were expressed in the six clusters comprising the 'cloud' of ECs (aEC1-6) (Figure 3B and F; Figure 3—figure supplement 1B). We individually compared LECs, vECs, and VSMCs to the remainder of ECs as a 'pseudo-bulk' cluster to generate a list of transcripts enriched (Z-score >3) for each of these three clusters. We performed the same analysis for aEC1, aEC2, aEC3, aEC4, aEC5, and aEC6, but used only arterial ECs as the comparator. For example, aEC1-enriched transcripts were identified by generating a 'pseudo-bulk' merge of all aEC2, aEC3, aEC4, aEC5, and aEC6 cells, while aEC2-enriched transcrips were compared to the pseudo-bulk merge of aEC1, aEC3, aEC4, aEC5, and aEC6. The top 32 transcripts that resulted from this analysis are shown in Figure 3—figure supplement 2. Among the arterial clusters, aEC1 and aEC2 harbored the greatest numbers of enriched transcripts (Z-score >3) with 411 and 1517, respectively (Figure 3—figure supplement 3A; see also Supplementary file 4). We noted that aEC5 exhibited the fewest (77) enriched transcripts (Figure 3—figure supplement 3A). Representative marker genes of aEC1, aEC2, aEC3, and aEC4 are shown in t-SNE embedding in Figure 3G–J. LEC (97% GFPhigh), vEC (100% GFPhigh), aEC1 (97% GFPhigh) and aEC2 (92% GFPhigh) harbored the greatest proportion of GFPhigh MAECs, suggesting that S1PR1/ß-arrestin coupling is robust in these ECs subtypes (Figure 3—figure supplement 3A and B). In contrast, aEC3-6 contained lower frequencies of GFPhigh MAECs. aEC4 (30% GFPhigh) exhibited the lowest frequency of MAECs with S1PR1/ß-arrestin coupling. The GFPhigh-dominated clusters (LEC, vEC, aEC1, and aEC2) were enriched with several transcripts related to sphingolipid metabolism, such as Spns2, Sptlc2, Ugcg, Enpp2, Ormdl3, Degs1, and Sgms2 (Figure 3—figure supplement 4A; see also Supplementary file 5). Notably, S1pr1 transcripts were enriched in aEC1 cells by ~1.8 fold relative to the remainder of arterial ECs (Figure 3—figure supplement 4A; see also Supplementary file 4). Pagoda2 clustering suggested that aEC1 cells were more similar to LECs and vECs than to the remainder of arterial ECs. This is illustrated by the first split of the hierarchical clustering dendrogram, which separated LEC, vEC, and aEC1 from the remainder of arterial ECs (aEC2-6) (Figure 3B). To identify genes that underlie the similarity between LEC, vEC, and aEC1, we identified all transcripts commonly enriched (46 transcripts, Z-score >3) and depleted (92 transcripts, Z-score < −3) in each of these three clusters when individually compared to a pseudo-bulk merge of aEC2-6 (Supplementary file 4). Examples of LEC, vEC, and aEC1 co-enriched transcripts were Itga6, Apold1, Kdr, Fabp4, Robo4, Tcf4, and Adgrf5 (Figure 3—figure supplement 4B). Conversely, Sod3, Pcolce2, Col4a4, Frzb, Sfrp1, Gxylt2, and Bmpr1a were depleted from LEC, vEC, and aEC1. Notably, these depleted transcripts were highly enriched in aEC4, which is 30% GFPhigh MAECs. In contrast, LEC, vEC, and aEC1 are each >95% GFPhigh. We note that the abovementioned transcripts (Figure 3—figure supplement 4B) were among those most differentially expressed between GFPhigh and GFPlow MAECs by bulk RNA-seq (Figure 1—figure supplement 1C). This is demonstrative of consistency between our bulk and single-cell datasets. For functional insights into arterial EC clusters, we analyzed aEC1-aEC4 enriched transcripts with the Gene Set Enrichment Analysis (GSEA) tool (Figure 4A–D and Supplementary file 5). aEC1 cells were enriched with transcripts associated with GPCR/MAPK signaling (Rasgrp3, Rapgef4, Rgs10, Mapk4k3, S1pr1) as well as VEGF, integrin, and tight-junction pathways (Flt1, Vegfc, Pgf, Igf2, Vcan, Sema3g, S100a4, Jam2, Cldn5). The aEC2 cluster presented a different profile with enriched terms related to immune/inflammatory pathways, TGFß signaling and mRNA processing. Elevated expression of Vcam1, Icam1, Traf6, Cxcl12 and NFkb1 may suggest that these ECs represent an inflammatory cluster. Figure 4 with 1 supplement see all Download asset Open asset Functional annotation of arterial MAECs clusters aEC1, aEC2, aEC3, and aEC4. (A–D) Selected pathways from GSEA analysis of cluster-enriched transcripts. Pathways enriched in aEC1 (A), aEC2 (B), aEC3 (C), and aEC4 (D) are shown with representeative transcripts identified in each pathway (see Supplementary file 5). The percent of GFPhigh cells in each of the four analyzed clusters are indicated at the bottom each heatmap. In contrast, aEC3 cells were enriched with 'immediate-early' transcripts, including those of the AP-1 transcription factor family (Atf3, Jun, Jund, Junb, Fos, Fosb). Enhanced expression of Atf3 and related TFs of the bZIP family in aEC3 may have contributed to increased chromatin accessibility at ATF, FOSB::JUN, and FOSB::JUNB binding sites in GFPlow MAECs (Figure 2D and G; Figure 2—figure supplement 3C). Notably, a recent study of young (8 week) and aged (18 month) normal mouse aortic endothelium also identified a cluster of Atf3-positive cell
High-density lipoprotein (HDL) nanoparticles promote endothelial cell (EC) function and suppress inflammation, but their utility in treating EC dysfunction has not been fully explored. Here, we describe a fusion protein named ApoA1-ApoM (A1M) consisting of apolipoprotein A1 (ApoA1), the principal structural protein of HDL that forms lipid nanoparticles, and ApoM, a chaperone for the bioactive lipid sphingosine 1-phosphate (S1P). A1M forms HDL-like particles, binds to S1P, and is signaling competent. Molecular dynamics simulations showed that the S1P-bound ApoM moiety in A1M efficiently activated EC surface receptors. Treatment of human umbilical vein ECs with A1M-S1P stimulated barrier function either alone or cooperatively with other barrier-enhancing molecules, including the stable prostacyclin analog iloprost, and suppressed cytokine-induced inflammation. A1M-S1P injection into mice during sterile inflammation suppressed neutrophil influx and inflammatory mediator secretion. Moreover, systemic A1M administration led to a sustained increase in circulating HDL-bound S1P and suppressed inflammation in a murine model of LPS-induced endotoxemia. We propose that A1M administration may enhance vascular endothelial barrier function, suppress cytokine storm, and promote resilience of the vascular endothelium.
Abstract High-density lipoprotein (HDL) particles suppress inflammation-induced tissue injury via vascular and myeloid cell-dependent mechanisms. As such, HDL-associated bioactive lipids such as sphingosine 1-phosphate (S1P) and prostacyclin (PGI 2 ) signal via their respective G protein-coupled receptors on target cells to promote vascular endothelial function and suppress platelet and myeloid-dependent pathophysiology. Here we have constructed a fusion protein of apolipoprotein A1 (ApoA1) and apolipoprotein M (ApoM) (A1M) that forms HDL-like particles and chaperones S1P and Iloprost, stable PGI 2 analog. The A1M/S1P complex activates S1P receptor-1 (S1PR1) as a Gα i -biased agonist and attenuates the inflammation-induced NFκB pathway while A1M/Iloprost acts via IP receptor to inhibit platelet aggregation and promote endothelial barrier function. In addition to enhancing the endothelial barrier, A1M/S1P suppresses neutrophil influx, oxidative burst and inflammatory mediator secretion in a sterile inflammation model. We propose that A1M could be useful as a therapeutic to induce S1P and PGI 2 -dependent anti-inflammatory functions and suppress collateral tissue injury.
