key: cord-0860685-9fh9t6h6
authors: He, Liqun; Mäe, Maarja Andaloussi; Muhl, Lars; Sun, Ying; Pietilä, Riikka; Nahar, Khayrun; Liébanas, Elisa Vázquez; Fagerlund, Malin Jonsson; Oldner, Anders; Liu, Jianping; Genové, Guillem; Zhang, Lei; Xie, Yuan; Leptidis, Stefanos; Mocci, Giuseppe; Stritt, Simon; Osman, Ahmed; Anisimov, Andrey; Hemanthakumar, Karthik Amudhala; Räsänen, Markus; Mirabeau, Olivier; Hansson, Emil; Björkegren, Johan; Vanlandewijck, Michael; Blomgren, Klas; Mäkinen, Taija; Peng, Xiao-Rong; Arnold, Thomas D.; Alitalo, Kari; Eriksson, Lars I; Lendahl, Urban; Betsholtz, Christer
title: Pericyte-specific vascular expression of SARS-CoV-2 receptor ACE2 – implications for microvascular inflammation and hypercoagulopathy in COVID-19
date: 2020-07-26
journal: bioRxiv
DOI: 10.1101/2020.05.11.088500
sha: 72c17f42b2fda19ba91ab173ac501b7a39b4c49f
doc_id: 860685
cord_uid: 9fh9t6h6

Accumulating clinical observations implicate vascular inflammation as an underlying cause of coagulopathy in severely ill COVID-19 patients and it was recently suggested that SARS-CoV-2 virus particles infect endothelial cells. Here, we show that endothelial cells do not express angiotensin-converting enzyme-2 (ACE2), the SARS-CoV-2 receptor. Instead, pericytes and microvascular smooth muscle cells express ACE2 in an organotypic manner. Pericyte deficiency leads to increased endothelial expression and release of Von Willebrand factor and intravascular platelet and fibrin aggregation, suggesting that pericytes limit endothelial pro-thrombotic responses. That pericytes and not endothelial cells express ACE2 may provide important clues to the pathology of COVID-19, as pericytes are normally shielded behind an endothelial barrier and may get infected only when this barrier is compromised by COVID-19 risk factors.

the initial range of COVID-19 symptoms, including cough, fever, respiratory impairment, lost sense of smell and taste, nausea and diarrhea. Later in the disease course, however, some COVID-19 patients, experience a second round of severe symptoms and complications, including venous and arterial thrombosis with pulmonary embolism, myocardial infarction and stroke, acute kidney injury and neurological manifestations [10] [11] [12] [13] [14] [15] [16] . Moreover, some patients display severe hypoxemia without concomitant respiratory dysfunction early in the disease course 17 . These severe and partly paradoxical manifestations pose questions about possible vascular involvement secondary to the initial viral pneumonia. Laboratory blood tests reveal coagulation abnormalities that differ from those observed in certain other severe diseases. The COVID-19-associated coagulopathy (CAC) appears distinct from disseminated intravascular coagulation (DIC), for example [18] [19] [20] . In addition, severely ill COVID-19 patients display indicators of systemic inflammation 21, 22 . The pathophysiological basis of these problems is not known, but involvement of the vascular endothelium has been suspected, posing the question if SARS-CoV-2 virus infects endothelial cells. Endothelial ACE2 expression has been reported based on immunodetection 5, 23, 24 , and recently the presence of SARS-CoV-2 virus particles in endothelial cells in COVID-19 patients was proposed 25, 26 , but also questioned 27 .

Recent single-cell RNA-sequencing (scRNAseq) studies have implicated low-level ACE2 expression by endothelial cells across multiple organs 8 but also vascular mural cells (pericytes and vascular smooth muscle cells (VSMC)) have been suggested to express ACE2 based on immunodetection 23 and RNA sequencing [28] [29] [30] [31] [32] . However, these interpretations are clouded by ambiguities concerning antibody specificity and cell contaminations in scRNAseq data.

To know what (if any) vascular cell types express ACE2 is important for the understanding of COVID-19 vascular pathophysiology. If endothelial cells carry ACE2 receptors, their infection would likely only require viral dissemination from the primary infected cells into the blood (viremia), which has been reported for SARS-CoV-2 33, 34 . However, infection of pericytes or other perivascular cells would require virus passage across the endothelial barrier, something that seems unlikely in a healthy vasculature given that corona virus particles are larger than the physiological endothelial pore size of most, if not all, blood vessels. However, in a number of Running title: COVID-19-pericyte hypothesis 5 July, 2020 5 pathophysiological conditions, including hypertension, inflammation, diabetes and obesity, the endothelial barriers are compromised and vascular permeability increased [35] [36] [37] [38] [39] . Notably, these conditions are also recognized as risk factors for severe COVID-19 disease 40, 41 .

Here, we report that there is strong and specific ACE2 expression in microvascular mural cells in a highly organotypic fashion, while vascular endothelial cells are consistently ACE2 mRNA and protein negative. We also find that pericyte deficiency promotes endothelial synthesis and release of Von Willebrand factor, platelet aggregation and fibrin deposition, showing that pericyte injury may trigger endothelial pro-coagulant responses.

It is an emerging view that COVID-19 patients in hospital care often display CAC and systemic inflammation, both associated with poor prognosis 10, 11, [42] [43] [44] [45] [46] [47] [48] . To assess the pathology spectrum in a Swedish patient cohort, we studied 20 critically ill patients admitted to the intensive care unit at the Karolinska University Hospital, Stockholm, Sweden with positive diagnostic test for COVID-19. These patients uniformly displayed indicators of systemic inflammation, including markedly elevated Creactive protein (CRP) and high circulating levels of pro-inflammatory cytokines, such as IL-6. They also displayed a typical CAC biochemistry and symptomatology, including elevated D-dimer levels and pulmonary embolism despite prophylactic anticoagulation therapy (Extended Data Table 1 ).

To explore the molecular basis for a direct infection of vascular cells by SARS-CoV-2 as a putative underlying case of CAC and systemic inflammation, we analyzed the expression of ACE2 and S priming proteases by vascular cells. Mice and humans frequently share gene and protein expression patterns across cell types, and we therefore first assessed the expression and distribution of Ace2/ACE2 in the mouse Running title: COVID-19-pericyte hypothesis 5 July, 2020 6 vasculature. Using our previously published scRNAseq database of adult mouse brain vascular gene expression patterns 29, 30 , we found that Ace2 mRNA is highly enriched in pericytes and venous VSMC, qualifying Ace2 among the top 15 specific markers for these cells (Extended Data Fig  1a, b and http://betsholtzlab.org/VascularSingleCells/database.html). At lower levels, Ace2

was also found in VSMCs negative for Cnn1 and other arterial VSMC markers (Extended Data Fig 1c,d) . A subpopulation of Ace2-positive type-2 fibroblasts (FB2)

cells and a few Ace2-positive endothelial cells were noted, however these cells coexpressed Kcnj8 (Extended Data Fig 1c) and several other pericyte markers (Extended Data Fig 1c, e) , suggesting that they were pericyte-contaminated. Deep analysis of the 23 Ace2-positive endothelial cells in this dataset revealed that 20 expressed at least one additional pericyte marker and 18 expressed multiple pericyte markers, whereas these markers were generally absent from Ace2-negative endothelial cells (Extended Data Fig 1e) . We failed to find any distinguishing gene expression pattern beyond the addition of pericytes markers onto the transcriptomes of FB2 and endothelial cells, respectively (Extended Data Fig 1f- 

together arguing that the presence of Ace2 RNA sequences in FB2 and endothelial cells is caused by pericyte contamination.

To deepen the analysis of brain vascular cells, we devised a computational pipeline for meta-analysis of scRNAseq data generated using SmartSeq2 and DropSeq (10x Genomics) platforms (see Methods). We used this pipeline to merge two published 29, 30, 49 and one unpublished dataset generated using both platforms.

The combined data are available for analysis gene-by-gene at http://betsholtzlab.org/Publications/BrainIntegration/search.html (login ID:

reviewer, password: reviewer). This analysis confirmed that Ace2 is specifically expressed in brain pericytes, venous VSMCs and Cnn1-negative arteriolar VSMCs (Fig   1a-c ). An additional Ace2-positive cell cluster contributed uniquely from the DropSeq dataset (cluster #17 in Fig 1a-c) contained both pericyte and endothelial markers but lacked other unique transcripts, and we therefore concluded that it was composed of pericyte-contaminated endothelial cells.

We next assessed the localization of ACE2 protein-expressing cells in the mouse brain vasculature by immune-fluorescence (IF) analysis. In agreement with 7 the scRNAseq data, we found the brain ACE2 IF signal was concentrated to periendothelial cells with typical morphology of pericytes: a distinct cell soma, primary longitudinally oriented processes and secondary short club-like extensions (Fig 1   d,e) . The endothelial cells were invariably ACE2 IF negative. As expected for a cell membrane-bound protein, ACE2 showed a similar sub-cellular distribution as platelet-derived growth factor receptor-beta (PDGFRB) and N-aminopeptidase (CD13), (Fig 1d and Extended Data Fig 2a) and a slightly distinct localization compared to the cytoplasmic Pdgfrb-GFP reporter (Extended Data Fig 2b) . Focusing on the cortex where the arterio-venous vascular hierarchy is readily distinguishable by morphology and marker expression 29 , we found strongly ACE2-positive mural cells associated with capillaries and veins/venules (Fig 1d) and weakly ACE2-positive Ace2-positive brain mural cells predicted from the scRNAseq data, revealing ACE2 as more specific to micro-vascular mural cells than other commonly used protein markers for mural cell (e.g. PDGFRB, CD13, and NG2), which also label arterial VSMC 50 .

To investigate the generality of the microvascular pattern of mural cell ACE2 expression in the central nervous system (CNS), we additionally analyzed spinal cord and eye. Similar to the brain, spinal cord ACE2 was concentrated to cells with the 3d) , demonstrating that mural cell ACE2 expression is highly organotypic. We further noted that the surface epithelium of the conjunctiva and cornea was ACE2-positive (Extended Data Fig 3g) , confirming recent observations by others 8 .

To extend the analysis of Ace2 expression to non-vascular cell types in several regions of the brain, we explored the mousebrain.org atlas, which confirmed that Ace2 is not appreciably expressed outside of the vasculature across >250 different central and peripheral nervous system cell types 51 (http://mousebrain.org/genesearch.html). More specifically, the mousebrain.org atlas report Ace2 mRNA in cells annotated as pericytes, but also in a cluster of endothelial cells 51 , which, however, we found to co-express numerous pericyte markers (including Pdgfrb and Notch3) suggesting contamination. The mousebrain.org atlas denotes weak Ace2 expression also in neurons in dorsal root ganglia 51 .

To analyze ACE2 expression in mural cells of the human CNS is currently challenging, given the scarcity of scRNAseq data for these cells. However, in a dataset representing the developing human prefrontal cortex 52 , we identified six ACE2-positive cells expressing at least one pericyte marker, and three of them expressed multiple pericyte markers (Extended Data Fig 4a) . We also assessed a human glioblastoma Drop-Seq (10 x Genomics) scRNAseq dataset consisting of 69,125 endothelial and immune cells sorted using anti-CD31 antibodies (Zhang et al, unpublished). Among these, we found only two ACE2-positive cells, both of which had pericyte markers (Extended Data Fig 4b) , suggesting that the ACE2 mRNA sequences were derived by pericyte contamination, and that endothelial cells were ACE2-negative. Finally, we assessed the scRNAseq data from an analysis of human retinas 53 and found enrichment for ACE2 in pericytes as compared to other retinal cells types, including endothelial cells (data not shown). Together, these observations indicate that pericytes express ACE2 in the human brain, but additional 9 analysis are needed to confirm these conclusions. We failed to find any indications for endothelial ACE2 expression in the analyzed human datasets.

We next analyzed Ace2/ACE2 expression in mouse and human heart. Based on scRNAseq and single-nucleus (sn)RNAseq data, it was recently suggested that ACE2 expression occurs across multiple human cardiac cell types, including cardiomyocytes, endothelial cells, pericytes, fibroblasts and macrophages 8, 31, 32 .

When examining adult mouse heart scRNAseq data enriched for mesenchymal cells collected by fluorescence-activated cell sorting (FACS) from Pdgfrb-GFP transgenic mice (Muhl et al, in press), we found prominent expression of Ace2 in pericytes, whereas we could not detect Ace2 mRNA in fibroblasts and VSMC (data not shown).

To expand this analysis to additional cardiac cell types, we used our meta-analysis pipeline to integrate three unpublished and one published 49 datasets. These suggesting that the rare Ace2-sequences found in cardiac endothelial cells were contributed by pericyte-contamination.

Cardiac ACE2 protein IF signal was detected only in cells with the typical location and morphology of pericytes: a round cell body and long processes adherent to the endothelial cells (Fig 2d) . The ACE2 IF signal overlapped with Pdgfrb-GFP, albeit with the expected difference in subcellular localization: ACE2 in cell membrane and processes and GFP in cytoplasm and nucleus. While ACE2 IF signal was thus confined to pericytes in both CNS and heart, we noticed two differences between these organs. First, in heart Ace2 mRNA and protein was found only in capillary pericytes (Fig 2c, d) , whereas in CNS small arteriolar and venous mural cells were also positive. Second, not all cardiac capillary pericytes were strongly ACE2 positive; some were weakly positive and some were negative (Fig 2d) .

In order to assess ACE2 expression in the human heart, we re-analyzed scRNAseq data from healthy adult human hearts 54 Fig 6b) , which, however, also expressed pericyte markers and were therefore concluded to be pericyte-contaminated (Extended Data Fig 6c) .

All other cardiac cells were ACE2-negative with the possible exception of cardiomyocytes, which although displaying lower ACE2 levels than pericytes did not show signs of pericyte contamination. Collectively, our analysis of scRNAseq data from mouse and human healthy hearts establishes pericytes as the major cellular source of Ace2/ACE2 in the adult heart, with putative low expression also in human fibroblasts and cardiomyocytes. ACE2 expression was consistently undetectable in cardiac endothelial cells in both mouse and human. (Fig 3c) . A strong ACE2 IF signal was observed in the bronchial epithelium throughout the bronchial tree (Fig 3d) . In the alveolar region distal to the terminal bronchioles, we found ACE2 IF signal in SFTPC-positive AT-2 cells (Fig 3d) . We failed to find ACE2 in any endothelial populations in the lung, including alveolar capillaries and large vessels (Fig 3d and Extended Data Fig 7) . Also CD68-positive alveolar macrophages were ACE2-negative (Extended Data Fig 7) . While the vast majority of lung pericytes were ACE2 IF negative, particularly in the alveolar region, we found a few ACE2 positive pericytes close to larger bronchi and abundantly in trachea capillaries (Extended Data Fig 7) .

In order to assess ACE2 expression in human lungs, we re-analyzed scRNAseq data from the lungs of adult human transplant donors and lung fibrosis patients 56 .

Here, AT-2 cells constituted the major cellular source of ACE2 transcripts, but expression was detected also in basal, club and multiciliated cells (Extended Data Fig   8) . Immune cells, endothelial cells and fibroblasts were ACE2-negative, but the vascular cell number was too small for a comprehensive analysis. Mural cells, for example, were not present in the dataset.

We also analyzed the expression of the SARS-CoV-2 S protein priming proteases in brain, heart and lung (Extended Data Fig 9) . We observed Ace2 and Tmprss2 co-expression in epithelial cells across the mouse lung dataset, whereas Ctsl and Ctsb were more broadly expressed (albeit weakly in hematopoietic cells)

(Extended Data Fig 9) . However, Tpmrss2 was not expressed in brain and heart pericytes, which instead exhibited co-expression of Ace2 with Ctsb and Ctsl (Extended Data Fig 9) .

Taken together, these observations reveal that in contrast to brain and heart and similar to ocular muscle, most vascular mural cells in the lung do not express ACE2. Instead our data show that in both mouse and human lung bronchial epithelial cells and alveolar AT-2 cells are the primary expression sites for ACE2 mRNA and protein. Furthermore, our data reveal differences in the S protein priming proteases that are expressed in pulmonary epithelial cells (TMPRSS2) versus brain and heart pericytes (CTSB/L).

We identify pericytes as the predominant Ace2-expressing cells in CNS and heart.

Given the roles of pericytes in vascular barrier formation and in restraining proinflammatory responses in endothelial cells 57-60 (Mäe et al, submitted), we analyzed pro-thrombotic responses in adult mice with constitutive hypoplasia of pericytes caused by decreased PDGF-B signaling via PDGFR-β (Pdgfb ret/ret mice) 61 . In addition to the pericyte loss and development of dilated capillaries reported previously for the Pdgfb ret/ret brain 57 , we found increased levels of Von Willebrand Factor mRNA (Vwf) and protein (VWF) compared to Pdgfb ret/+ littermate control mice, which had normal microvascular pericyte coverage (Fig 4a,b) . Increased capillary VWF expression was observed also in Pdgfb ret/ret heart in comparison with Pdgfb ret/+ littermate controls (Fig 5) , which correlated with decreased pericyte coverage also in this organ (Extended Data Fig 10) . VWF promotes platelet adhesion and blood coagulation in wounds through binding and stabilization of factor VIII. In controls, VWF mRNA and protein were mainly confined to arterioles and venules with limited or undetectable presence in capillaries, whereas the dilated capillaries showing signs of pro-inflammatory activation in Pdgfb ret/ret mice 57 (Mäe et al, submitted) were strongly and uniformly VWF-positive (Fig 4a,b) . The VWF IF signal was primarily localized to intracellular rod-shaped vesicles (Weibel-Palade bodies) (Extended Data , but it was also frequently observed as a "halo" around vessels in the Pdgfb ret/ret brain parenchyma, presumably due to local VWF release (Fig 4b,c) . We next assessed platelet adherence and aggregation in the Pdgfb ret/ret vessels by analyzing CD41 IF and fibrinogen (FBG) leakage and fibrin deposition (Extended Data Fig 12) . Sites displaying both platelet 13 aggregation and fibrin deposition were commonly observed in brain sections from Pdgfb ret/ret mice (Extended Data Fig 12) , whereas in controls, we observed only rarely individual adhered platelets, but no signs of platelet aggregation or FBG/fibrin deposition (data not shown). We also found that VWF release coincided with 70 kDa dextran tracer leakage into the brain parenchyma, demonstrating a local impairment of the blood-brain barrier at these sites (Extended Data Fig 12) . In summary, these data reveal an important role for pericytes in restricting pro-coagulant responses concomitant with vascular leakage in endothelial cells.

The "COVID-19-pericyte hypothesis"

Our results lead us to posit a COVID-19-pericyte hypothesis, schematically illustrated Besides endothelial cells, we also did not find Ace2/ACE2 expression in tissue macrophages or other hematopoietic cells, which have been reported to express 70 . For brain capillaries with blood-brain barrier, the upper pore size limit is <1 nm. Although the diameter of endothelial fenestrae is comparable to that of the coronavirus particle (i.e. ≈ 100 nm) 71 , the physiological upper pore size limit is ≈ 15 nm in kidney glomeruli and ≈ 60 nm in bone marrow sinusoids, lymph nodes and liver 70, 72, 73 . Furthermore, even if the virus were able to pass through endothelial pores, it would face a basement membrane with a pore size smaller than the virus diameter 74 . For viral infection of renal proximal tubular epithelial cells, which express ACE2 75 , and for SARS-CoV-2 dissemination into urine 76 , it is therefore conceivable that the virus must translocate through a damaged endothelium located either in the glomerular, or in the peritubular capillaries. In the context of risk factors 77, 78 .

While it appears unlikely that SARS-CoV-2 reaches pericytes in individuals with healthy microvasculature, the situation is different when the endothelial barrier is pathologically disrupted. Breakdown of endothelial junctions and transcytosis has been described in numerous inflammatory conditions 79 

While we still lack evidence that pericytes can become infected by SARS-CoV-2 in vitro and in vivo, we have provided evidence that pericytes regulate prothrombogenic responses in the microvascular endothelium. It has previously been shown in mouse models with pericyte hypoplasia that pericyte function is critical for endothelial quiescence, barrier integrity and inhibition of leukocyte adhesion [57] [58] [59] [60] 90, 91 . Herein, we report that endothelial cells in pericyte-deficient mouse microvasculature increase VWF production and release, which would be predicted to promote platelet aggregation and blood coagulation, something we also observe. 

ScRNAseq data were obtained from internal mouse heart single cell projects and the published Tabula Muris heart dataset 49 , collectively including diverse cell types in the heart. All samples were obtained from 6-20 weeks old C57Bl6 mice. FACS-based cell capture into 384-well plates with subsequent scRNAseq data generation was conducted using the SMART-Seq2 protocol 94 and by microfluidic-droplet-based capture by the 10X Genomics protocol. Data processing and clustering were performed using the Seurat package (v. 3.1.1). Cells containing less than 200 expressed genes were filtered out. For the SMART-Seq2 data, cells that generated less than 50,000 reads were filtered out; for the droplet platform, cells containing less than 1000 UMIs were filtered out. Furthermore, genes that were expressed by less than three cells in a dataset were removed. After removing low quality cells from the dataset, the data were normalized using the LogNormalize function, by which feature counts for each cell are divided by the total counts for that cell and multiplied by a scale factor (1 million) and then logarithmically transformed. For integration of different datasets, the integration workflow "Reciprocal PCA" in the Seurat package was implemented, which integrated overall datasets using the mutual nearest neighbor (MNN) cell pairs that shared a common set of molecular features in their PCA spaces. After integration, we obtained a total of 18,378 genes and 10,101 cells for downstream analysis. The function "FindClusters" in the Seurat package was used to identify the clusters with a resolution parameter of 0.5.

The mouse lung datasets were obtained from internal lung single cell projects and the published Tabula Muris lung resource 49 . All samples were from 10-19 weeks old C57Bl6 mice. Data integration and clustering analysis for the lung were performed with the same methods as for the mouse heart data described above. We obtained a total of 20,114 genes and 11,085 cells in the integrated lung dataset.

Mouse brain datasets were integrated from two internal brain single-cell projects and one published (the Tabula Muris brain resource) 49 . The internal datasets included one unpublished and one previously published brain vasculature dataset 30 .

The cells were from 10-19 weeks old C57Bl6 mice. Data integration and clustering analysis were performed with the same methods as for the mouse heart and lung data described above. We obtained a total of 12,940 cells and 17,779 genes in the integrated brain dataset.

In order to provide detailed visualizations of the primary gene expression data cellby-cell for each cluster of the integrated dataset, we created bar plots using the normalized counts from each cell. In these graphs, a bar represents a cell and is colored according to its data source. The data source abbreviations "ss2" and "droplet" in the legend represent the SMART-Seq2 protocol and microfluidicdroplet-based capture by the 10X Genomics protocol, respectively. For the integrated dataset of lung, "TJA_ss2", "CBZ_ss2" and "H_droplet" represent in-house unpublished datasets; "TM_ss2" and "TM_droplet" represent published Tabula Muris data 49 . For the integrated dataset of heart, "L_ss2", "S_ss2" and "H_droplet" represent in-house unpublished datasets; "TM_ss2" and "TM_droplet" represent published Tabula Muris data. For the integrated dataset of brain, "C_ss2" and "K_droplet" represent in-house unpublished datasets; "TM_ss2" represents published Tabula Muris data.

Running title: COVID-19-pericyte hypothesis 5 July, 2020 20

The human heart single cell data were extracted from a published study 54 , and only cells from healthy donors were included in the current analysis. The Seurat package (version 3.1.1) was used for raw data processing, filtering, normalization, clustering and further downstream analysis 95 . Cells that had less than 500 expressed genes were filtered out. Genes expressed in less than 10 cells were also filtered out. In total, 8383 single cells from 14 previously healthy organ donors (12 males and 2 females) qualified for downstream analysis. The gene expression levels in each cell were normalized to a total read counts of 100,000 per cell. The top 2,000 variable genes in the dataset were used for linear dimensional reduction of the data using the PCA method. The first 30 principal components were used for UMAP visualization and clustering of the cells using default parameters in Seurat pipeline.

The human lung single cell data were obtained from a published study 56 

The following mouse strains were used: Pdgfb ret (Pdgfb-tm(ret)) 61 , Cspg4-DsRed 

For blood-brain barrier integrity assessment, dextran (100 μg/g body weight)

conjugated to tetramethylrhodamine (cat. #D1818, Life Technologies) was injected intravenously into the tail vein 16 hours before sacrifice, respectively 57 . For tracer in situ analysis, anaesthetized animals were perfused transcardially for 5 min with HBSS Running title: COVID-19-pericyte hypothesis 5 July, 2020 22 followed by 4 min with 4% buffered formaldehyde. Where after the brains were processed as described under Immunofluorescence staining.

Cryo-sections from brain, heart and lung

Tissues were harvested from euthanized mice without perfusion and fixed by immersion in 4% formaldehyde for 4-12h at 4 °C, followed by immersion in 20%

sucrose/PBS solution for at least 24h at 4°C. Thereafter, tissues were embedded for cryo-sectioning and sectioned on a CryoStat NX70 (ThermoFisher Scientific) to 14 or 30 µm thick sections collected on SuperFrost Plus glass slides (Metzler Gläser).

Sections were allowed to thaw at RT and thereafter blocked for > 60 min at RT with blocking-buffer (serum-free protein blocking solution, DAKO), supplemented with 0.2% Triton X-100 (Sigma Aldrich), followed by sequentially incubation with primary antibodies (overnight at 4 °C) (Extended Data Table 1 ) and corresponding fluorescently conjugated secondary antibodies (1h at RT) together with 10 µg/ml

Hoechst 33342 (trihydrochloride, trihydrate, ThermoFisher Scientific). Sections were mounted with ProLong Gold Antifade mounting medium, and micrographs acquired and graphically handled as described above. 

Extended Data Table 1 

Coronaviruses: an overview of their replication and pathogenesis

SARS-CoV-2 Cell Entry Depends on ACE2 and TMPRSS2 and Is Blocked by a Clinically Proven Protease Inhibitor

Receptor and viral determinants of SARS-coronavirus adaptation to human ACE2

Efficient activation of the severe acute respiratory syndrome coronavirus spike protein by the transmembrane protease TMPRSS2

Angiotensin converting enzyme-2 confers endothelial protection and attenuates atherosclerosis

Angiotensin (1-7) and other angiotensin peptides

SARS-CoV-2 entry factors are highly expressed in nasal epithelial cells together with innate immune genes

Integrated analyses of single-cell atlases reveal age, gender, and smoking status associations with cell type-specific expression of mediators of SARS-CoV-2 viral entry and highlights inflammatory programs in putative target cells. bioRxiv

SARS-CoV-2 receptor ACE2 is an interferon-stimulated gene in human airway epithelial cells and is detected in specific cell subsets across tissues

Abnormal coagulation parameters are associated with poor prognosis in patients with novel coronavirus pneumonia

High risk of thrombosis in patients with severe SARS-CoV-2 infection: a multicenter prospective cohort study

Neurologic Manifestations of Hospitalized Patients With Coronavirus Disease

Human kidney is a target for novel severe acute respiratory syndrome coronavirus 2

Acute Kidney Injury in COVID-19: Emerging Evidence of a Distinct Pathophysiology

Clinical course and outcomes of critically ill patients with SARS-CoV-2 pneumonia in Wuhan, China: a single-centered, retrospective, observational study

Confirmation of the high cumulative incidence of thrombotic complications in critically ill ICU patients with COVID-19: An updated analysis

Facing COVID-19 in the ICU: vascular dysfunction, thrombosis, and dysregulated inflammation

COVID-19-Related Severe Hypercoagulability in Patients Admitted to Intensive Care Unit for Acute Respiratory Failure

Hypercoagulability of COVID-19 patients in Intensive Care Unit. A Report of Thromboelastography Findings and other Parameters of Hemostasis

COVID-19 update: Covid-19-associated coagulopathy

Urgent avenues in the treatment of COVID-19: Targeting downstream inflammation to prevent catastrophic syndrome

COVID-19, Arrhythmic Risk and Inflammation: Mind the Gap! Circulation

Tissue distribution of ACE2 protein, the functional receptor for SARS coronavirus. A first step in understanding SARS pathogenesis

Angiotensin-converting enzyme 2 (ACE2) expression and activity in human carotid atherosclerotic lesions

Endothelial cell infection and endotheliitis in COVID-19

Pulmonary Vascular Endothelialitis, Thrombosis, and Angiogenesis in Covid-19

Electron microscopy of SARS-CoV-2: a challenging task

A molecular atlas of cell types and zonation in the brain vasculature

Single-cell RNA sequencing of mouse brain and lung vascular and vessel-associated cell types

The ACE2 expression in human heart indicates new potential mechanism of heart injury among patients infected with SARS-CoV-2

Cell type-specific expression of the putative SARS-CoV-2 receptor ACE2 in human hearts

A pneumonia outbreak associated with a new coronavirus of probable bat origin

Viral load dynamics and disease severity in patients infected with SARS-CoV-2 in Zhejiang province

Endothelial Barrier and Its Abnormalities in Cardiovascular Disease

Cerebral microvascular complications of type 2 diabetes: stroke, cognitive dysfunction, and depression

Diabetic microangiopathy: Pathogenetic insights and novel therapeutic approaches

Endothelial permeability, LDL deposition, and cardiovascular risk factors-a review

Microvascular permeability in diabetes and insulin resistance

Presenting Characteristics, Comorbidities, and Outcomes Among 5700 Patients Hospitalized With COVID-19 in the New York City Area

Are patients with hypertension and diabetes mellitus at increased risk for COVID-19 infection?

Clinical Characteristics of Coronavirus Disease 2019 in China

Is COVID-19 and endothelial disease? Clinical and basic evidence

Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study

Pulmonary Embolism in COVID-19 Patients: Awareness of an Increased Prevalence

Concomitant acute aortic thrombosis and pulmonary embolism complicating COVID-19 pneumonia

Pulmonary Embolism or Pulmonary Thrombosis in COVID-19? Is the Recommendation to Use High-Dose Heparin for Thromboprophylaxis Justified?

COVID-19 and Thrombotic or Thromboembolic Disease: Implications for Prevention, Antithrombotic Therapy, and Follow-up

Single-cell transcriptomics of 20 mouse organs creates a Tabula Muris

Pericytes: developmental, physiological, and pathological perspectives, problems, and promises

Molecular Architecture of the Mouse Nervous System

A single-cell RNA-seq survey of the developmental landscape of the human prefrontal cortex

Single-cell transcriptomics of the human retinal pigment epithelium and choroid in health and macular degeneration

Single-cell reconstruction of the adult human heart during heart failure and recovery reveals the cellular landscape underlying cardiac function

COVID-19: the vasculature unleashed

Single-Cell Transcriptomic Analysis of Human Lung Provides Insights into the Pathobiology of Pulmonary Fibrosis

Pericytes regulate the blood-brain barrier

Pericytes are required for blood-brain barrier integrity during embryogenesis

Pericytes regulate vascular immune homeostasis in the CNS. bioRxiv

Role of Tumor Pericytes in the Recruitment of Myeloid-Derived Suppressor Cells

Endothelial PDGF-B retention is required for proper investment of pericytes in the microvessel wall

Immunopathogenesis of coronavirus infections: implications for SARS

Detection of SARS-CoV-2 in Different Types of Clinical Specimens

Detectable 2019-nCoV viral RNA in blood is a strong indicator for the further clinical severity

Single-cell RNA-seq data analysis on the receptor ACE2 expression reveals the potential risk of different human organs vulnerable to 2019-nCoV infection

Myocyte Specific Upregulation of ACE2 in Cardiovascular Disease: Implications for SARS-CoV-2 mediated myocarditis

Vascular permeability--the essentials

Supramolecular architecture of severe acute respiratory syndrome coronavirus revealed by electron cryomicroscopy

Identification of Coronavirus Isolated from a Patient in Korea with COVID-19

Physiologic upper limits of pore size of different blood capillary types and another perspective on the dual pore theory of microvascular permeability

Structural and functional aspects of liver sinusoidal endothelial cell fenestrae: a review

The size of endothelial fenestrae in human liver sinusoids: implications for hepatocytedirected gene transfer

Phenotypic heterogeneity of the endothelium: I. Structure, function, and mechanisms

Characterization of endothelial basement membrane nanotopography in rhesus macaque as a guide for vessel tissue engineering

Renal ACE2 expression in human kidney disease

SARS-CoV-2 can be detected in urine, blood, anal swabs, and oropharyngeal swabs specimens

Mechanisms of disease: the hypoxic tubular hypothesis of diabetic nephropathy

Interstitial vascular rarefaction and reduced VEGF-A expression in human diabetic nephropathy

Endothelial dysfunction: a marker of atherosclerotic risk

Role of Endothelial Dysfunction in Cardiovascular Diseases: The Link Between Inflammation and Hydrogen Sulfide

Endothelial dysfunction in cardiovascular diseases: the role of oxidant stress

Vascular permeability in cardiovascular disease and cancer

Microalbuminuria, blood pressure load, and systemic vascular permeability in primary hypertension

Obesity, inflammation and endothelial dysfunction

Endothelial Dysfunction in Obesity-Induced Inflammation: Molecular Mechanisms and Clinical Implications

Endothelial Dysfunction in Obesity: Role of Inflammation

Blood-brain barrier breakdown is an early biomarker of human cognitive dysfunction

The role of brain vasculature in neurodegenerative disorders

Inhibition of SARS-CoV-2 Infections in Engineered Human Tissues Using Clinical-Grade Soluble Human ACE2

Pericyte loss and microaneurysm formation in PDGF-B-deficient mice

Pericytes control key neurovascular functions and neuronal phenotype in the adult brain and during brain aging

COVID-19 cytokine storm: the interplay between inflammation and coagulation

Running title: COVID-19-pericyte hypothesis

Classification of the cutaneous manifestations of COVID-19: a rapid prospective nationwide consensus study in Spain with 375 cases

Full-length RNA-seq from single cells using Smart-seq2

We thank Cecilia Olsson, Pia Peterson, Jana Chmielniakova, Helene Leksell, Sonja Gustafsson, Byambajav Buyandelger and Elisabeth Raschperger for technical help.