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

This work was supported by:

National Centre for the Replacement, Refinement and Reduction of Animals in Research, United Kingdom

Newton Fund, International

Medical Research Council, United Kingdom

Department of Health, United Kingdom

GrantID: PB-PG-1215-20037

NHLBI NIH HHS, United States

NHLBI NIH HHS, United States

British Heart Foundation, United Kingdom

Wellcome Trust, United Kingdom

NIAID NIH HHS, United States

Medical Research Council, United Kingdom

Medical Research Council, United Kingdom

NIA NIH HHS, United States

NHLBI NIH HHS, United States

Medical Research Council, United Kingdom

Medical Research Council, United Kingdom

NHLBI NIH HHS, United States

British Heart Foundation, United Kingdom

Medical Research Council, United Kingdom

Medical Research Council, United Kingdom

NICHD NIH HHS, United States

Rosetrees Trust, International

Medical Research Council, United Kingdom

NIAID NIH HHS, United States

NHLBI NIH HHS, United States

National Centre for the Replacement, Refinement and Reduction of Animals in Research, United Kingdom

NHLBI NIH HHS, United States

Medical Research Council, United Kingdom

NIDDK NIH HHS, United States

NHLBI NIH HHS, United States

NHLBI NIH HHS, United States

Medical Research Council, United Kingdom

Medical Research Council, United Kingdom

Multi-tissue genetic analysis suggests SARS-CoV-2 may infect specific nose cells Genes associated with how the virus SARS-CoV-2 enters a host were found to be expressed in specific healthy human respiratory, corneal and intestinal epithelial cells, according to a paper published this week in Nature Medicine. Expression of these genes was observed in nasal cells alongside that of genes involved in the innate immune system, which suggests a potential role for nasal tissue in initial viral infection, transmission and clearance.

Previous research had shown that nasal swabs from patients with symptomatic or asymptomatic COVID-19 respiratory disease (the disease caused by SARS-CoV-2) exhibit higher viral concentrations than those in throat swabs. This has implicated the nasal passage as a potential gateway for initial infection and transmission.

ACE2 and TMPRSS2 are two molecules involved in SARS-CoV-2 viral entry. To clarify the expression patterns of the genes encoding ACE2 and TMPRSS2, Waradon Sungnak and colleagues from the Lung Biological Network examined various human tissue samples obtained from healthy donors. The authors analysed data for tissues from various parts of the respiratory system, the retina, skeletal muscle, prostate, brain and skin, among other locations. They confirmed the expression of ACE2 in multiple tissues implicated in prior research. They also detected ACE2 expression in tissues not previously analysed, along with its co-expression with TMPRSS2.

The authors found high expression of ACE2 and TMPRSS2 in nasal goblet and ciliated cells, which produce mucus. This suggests that these cells are the location of original viral infection and are possibly the source of dissemination within and between people.

The authors conclude that their results could potentially have implications for future treatment and prevention of COVID-19.

doi:10.1038/s41591-020-0868-6

The coronavirus disease 2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)1. Detection of the virus was first reported in Wuhan2, China and has since spread worldwide, emerging as a global pandemic3.

In symptomatic patients, nasal swabs have yielded higher viral loads than throat swabs4. The same distribution was observed in an asymptomatic patient4, implicating the nasal epithelium as a portal for initial infection and transmission. Cellular entry of coronaviruses depends on the binding of the spike (S) protein to a specific cellular receptor and subsequent S protein priming by cellular proteases. Similar to SARS-CoV5,6, SARS-CoV-2 employs ACE2 as a receptor for cellular entry. The binding affinity of the S protein and ACE2 was found to be a major determinant of SARS-CoV replication rates and disease severity4,7. Viral entry also depends on TMPRSS2 protease activity, and cathepsin B/L activity may be able to substitute for TMPRSS27.

ACE2 and TMPRSS2 have been detected in both nasal and bronchial epithelium by immunohistochemistry8. Gene expression of ACE2 and TMPRSS2 has been reported to occur largely in alveolar epithelial type II (AT-2) cells9–11, which are central to SARS-CoV pathogenesis, while a different study reported the absence of ACE2 in the upper airway12. To clarify the expression patterns of ACE2 and TMPRSS2, we analyzed their expression and the expression of other genes potentially associated with SARS-CoV-2 pathogenesis at cellular resolution, using scRNA-seq datasets from healthy donors generated by the Human Cell Atlas consortium and other resources to inform and prioritize the use of precious, limited clinical material that is becoming available from COVID-19 patients.

We investigated the gene expression of ACE2 in multiple scRNA-seq datasets from different tissues, including those of the respiratory tree, cornea, retina, esophagus, ileum, colon, heart, skeletal muscle, spleen, liver, placenta/decidua, kidney, testis, pancreas, prostate gland, brain, skin, and fetal tissues. We note that studies may lack specific cell types due to their sparsity, the challenges associated with isolation, or analysis methodology. Moreover, expression may be under-detected due to technical dropout effects. Thus, while positive (presence) results are highly reliable, absence should be interpreted with care.

ACE2 expression was generally low in all analyzed datasets. Consistent with independent studies10,11, ACE2 was expressed in cells from multiple tissues, including airways, cornea, esophagus, ileum, colon, liver, gallbladder, heart, kidney, and testis (Fig. 1a; first column). TMPRSS2 was highly expressed with a broader distribution (Fig. 1a; second column), suggesting that ACE2, rather than TMPRSS2, may be a limiting factor for viral entry at the initial infection stage. Cells from the respiratory tree, cornea, esophagus, ileum, colon, gallbladder, and common bile duct expressed both genes in the same cell (Fig. 1a; third column). We also assessed ACE2 and TMPRSS2 expression in developmental datasets from fetal tissues, including liver, thymus, skin, bone marrow, yolk sac, and lung, and found little to no expression of ACE2 in all but fetal liver and thymus (Fig. 1a) where there was no co-expression with TMPRSS2 (data not shown) except for a cluster of medullary thymic epithelial cells (Fig. 1a). ACE2 expression is noticeable in certain cell types in placenta/decidua without TMPRSS2 (Fig. 1a). Additional fetal data across relevant tissues and stages are needed to determine the generality of these findings.

Expression of ACE2 and TMPRSS2 across different tissues and its enrichment in nasal epithelial cells.

a, RNA expression of SARS-CoV-2 entry receptor ACE2 (first column), entry-associated protease TMPRSS2 (second column), and their co-expression (third column) from multiple scRNA-seq datasets across different tissues. Raw expression values were normalized, log transformed and summarized by published cell clustering where available, or reproduced clustering annotated using marker genes and cell type nomenclature from the respective studies. The size of the dots indicates the proportion of cells in the respective cell type having greater-than-zero expression of ACE2 (first column), TMPRSS2 (second column) or both (third column), while the colour indicates the mean expression of ACE2 (first and third columns) or TMPRSS2 (second column). b, Schematic illustration depicts the major anatomical regions in the human respiratory tree demonstrated in this study: nasal, lower airway, and lung parenchyma (left panel). Expression of ACE2 is from airway epithelial cell datasets: Vieira Braga, Kar et al. 2019 (middle panel) and Deprez et al. 2019 (right panel). The datasets were retrieved from existing sources, and the cell clustering and nomenclature were retained based on the respective studies. For gene expression results in the dot plots: the dot size represents the proportion of cells within the respective cell type expressing the gene and the dot color represents the average gene expression level within the particular cell type.

To further characterize specific epithelial cell types expressing ACE2, we evaluated the ACE2 expression within the lung and airway epithelium. We found that, despite a low level of expression overall, ACE2 was expressed in multiple epithelial cell types across the airway, as well as in AT-2 cells in the parenchyma, consistent with previous studies9–11. Importantly, nasal epithelial cells, including two previously described clusters of goblet cells and one cluster of ciliated cells, show the highest expression among all investigated cells in the respiratory tree (Fig. 1b; left panel). We confirmed enriched ACE2 expression in nasal epithelial cells in an independent scRNA-seq study that includes nasal brushings and biopsies. The results were consistent: we found the highest expression of ACE2 in nasal secretory cells (equivalent to the two goblet cell clusters in the previous dataset) and ciliated cells (Fig. 1b; right panel).

In addition, scRNA-seq data from an in vitro epithelial regeneration system from nasal epithelial cells corroborated the expression of ACE2 in goblet/secretory cells and ciliated cells in these air-liquid interface (ALI) cultures (Extended Data Fig. 1). Notably, the differentiating cells in ALI acquire progressively more ACE2 (Extended Data Fig. 1). The results also suggest that this in vitro culture system may be biologically relevant for the study of SARS-CoV-2 pathogenesis.

It is worth noting that TMPRSS2 was only expressed in a subset of ACE2+ cells (Extended Data Fig. 2), suggesting that the virus might use alternative pathways. It was previously shown that SARS-CoV-2 could enter TMPRSS2− cells using cathepsin B/L7. Indeed, other proteases were more promiscuously expressed than TMPRSS2, especially cathepsin B, which was expressed in more than 70%-90% of ACE2+ cells (Extended Data Fig. 2). However, while TMPRSS2 activity is documented to be important for viral transmission13,14, the potential of cathepsin B/L or other proteases to functionally replace TMPRSS2 has not been determined.

We next asked whether the enriched expression of viral receptors and entry-associated molecules in the nasal region/upper airway might be relevant for viral transmissibility. Here, we assessed the expression of viral receptor genes that are used by other coronaviruses and influenza viruses in our datasets. We looked for ANPEP (used by HCoV-2294415) and DPP4 (used by MERS-CoV4516), as well as the enzymes ST6GAL1 and ST3GAL4, which are important for the synthesis of α(2,6)-linked and α(2,3)-linked sialic acids recognized by influenza viruses17. Notably, their expression distribution coincided with viral transmissibility patterns based on a comparison to the basic reproduction number (R0), which estimates the number of people who can become infected from a single infected person. The skewed distribution of the receptors/enzymes towards the upper airway is observed in viruses with higher R0/infectivity, including those of SARS-CoV/SARS-CoV-2 (R0 ~ 1.4-5.018–20), influenza (mean R0 ~1.34721) and HCoV-229E (unidentified R0; associated with common cold). This distribution is in distinct contrast with that of DPP4, the receptor for MERS-CoV (R0 ~0.3-0.822), a coronavirus with limited human-to-human transmission23, in which expression skews towards lower airway/lung parenchyma (Fig. 2a). Therefore, our data highlight the possibility that viral transmissibility is dependent on the spatial distribution of receptor accessibility along the respiratory tract.

Respiratory expression of viral receptor/entry-associated genes and implications for viral transmissibility and genes associated with ACE2 expression.

a, Expression of ACE2 (an entry receptor for SARS-CoV and SARS-CoV-2), ANPEP (an entry receptor for HCoV-229E), ST6GAL1/ST3GAL4 (enzymes important for synthesis of influenza entry receptors), and DPP4 (an entry receptor for MERS-CoV) from the airway epithelial datasets: Vieira Braga, Kar et al. 2019 (left panel) and Deprez et al. 2019 (right panel). The basic reproductive number (R0) for respective viruses, if available, are shown. b, Respiratory epithelial expression of the top 50 genes correlated with ACE2 expression based on Spearman’s correlation analysis (with Benjamini-Hochberg-adjusted p-values) performed on all cells within the Vieira Braga, Kar et al. airway epithelial dataset. The colored gene names represent genes that are immune-associated (GO:0002376: immune system process or GO:0002526: acute inflammatory response). For gene expression results in the dot plots: the dot size represents the proportion of cells within the respective cell type expressing the gene and the color represents the average gene expression level within the particular cell type.

To gain more insight into the expression patterns of genes associated with ACE2, we performed Spearman’s correlation analysis with Benjamini-Hochberg-adjusted p-values to identify genes associated with ACE2 across all cells within the lung epithelial cell datasets. While the correlation coefficients are relatively low (< 0.12), likely due to low expression of ACE2 and technical noise and dropout effects, the expression pattern of the top 50 ACE2-correlated genes across the respiratory tree is consistent with that of ACE2, with a skewed expression towards upper airway cells (Fig. 2b and Extended Data Fig. 3a,​b). Interestingly, while some of the genes are associated with carbohydrate metabolism, possibly due to their role in goblet cell mucin synthesis, a number of genes associated with immune functions including innate and antiviral immune functions, are over-represented in the rank list, including IDO1, IRAK3, NOS2, TNFSF10, OAS1, and MX1 (Fig. 2b and Supplementary Table 1). Expression of these genes is highest in nasal goblet 2 cells (Fig. 2b), consistent with the phenotype previously described. Nonetheless, nasal goblet 1 and nasal ciliated 2 cells also significantly express these genes (Fig. 2b). Given their environmental exposure and high expression of receptor/receptor-associated enzymes (Fig. 2a), it is plausible that nasal epithelial cells are conditioned to express these immune-associated genes to reduce viral susceptibility.

In this study, we explored multiple scRNA-seq datasets generated within the HCA consortium and other resources, and found that the SARS-CoV-2 entry receptor ACE2 and viral entry-associated protease TMPRSS2 are highly expressed in nasal goblet and ciliated cells. This finding implicates these cells as loci of original infection and possible reservoirs for dissemination within and between individuals. Co-expression in other barrier surface tissues could also suggest further investigation into alternative transmission routes. For example, the co-expression in esophagus, ileum, and colon could explain viral fecal shedding observed clinically24, with implications for potential fecal-oral transmission, whereas the co-expression in superficial conjunctival cells could explain an ocular phenotype observed in a small portion of COVID-19 patients25 with the potential of spread through the nasolacrimal duct.

The results confirmed the expression of ACE2 in multiple tissues shown in prior studies10,11 with added information on tissues not previously investigated, including nasal epithelium and cornea, and its co-expression with TMPRSS2. We clearly detected nasal ACE2 mRNA expression, for which protein confirmation is needed to resolve conflicting results in literature8,12. Our findings may have significant implications for understanding viral transmissibility, considering that the primary viral transmission is through infectious droplets. Moreover, as SARS-CoV-2 is an enveloped virus, its release does not require cell lysis. Thus, the virus might exploit existing secretory pathways in nasal goblet cells sustained at a pre-symptomatic stage. These discoveries could have translational implications. For example, given that nasal carriage is likely to be a key feature of transmission, drugs/vaccines administered intranasally could be highly effective in limiting spread.

This is the first collaborative effort by a Human Cell Atlas Biological Network (the Lung), and illustrates the opportunities from integrative analyses of Human Cell Atlas data, with future examples of consortium work expected soon.

The datasets were retrieved from published and unpublished datasets in multiple human tissues, including airways26,27, cornea (personal communication; Lako lab, Newcastle), skeletal muscle (personal communication, Teichmann lab, Wellcome Sanger Insitute and Zhang lab, Sun-Yat-Sen University, Guangzhou, China), ileum28, colon29, pancreas30, liver31, gallbladder (personal communication; Vallier lab, University of Cambridge), heart (Teichmann lab, Hubner lab/Berlin, Seidmanns/Harvard, and Noseda lab/Imperial College London), kidney32, placenta/decidua33, testis34, prostate gland35, brain36, skin37, retina38, spleen39, esophagus39, and fetal tissues40,41. Raw expression values were normalized and log transformed. We retained the cell clustering based on the original studies when available.

For each dataset where per-cell annotation is not available, we re-processed the data from raw or normalized (whichever was deposited alongside the original publication) quantification matrix. The standard scanpy (version 1.4.3) clustering procedure was followed. When batch information is available, harmony package was used to correct batch effects in the PC space and the corrected PCs were used for computing nearest neighbour graphs. To re-annotate the cells, multiple clusterings of different resolutions were generated among which the one best matching the published clustering was picked and manual annotation was undertaken using marker genes described in the original publication. Full details can be found in analysis notebooks available at github.com/Teichlab/covid19_MS1.

Illustration of the results was generated using scanpy and Seurat (version 3.1). For correlation analysis with ACE2, we performed the Spearman’s correlation with statistical tests using the R Hmisc package (version 4.3-1) and the p values were adjusted with Benjamini-Hochberg method with the R stats package (version 3.6.1) on the Vieira Braga, Kar et al. airway epithelial dataset and the Deprez et al. airway dataset. We also tested multiple additional approaches, including Kendall’s correlation, data transformation by sctransform function in the Seurat package, and data imputation by the Markov Affinity-based Graph Imputation of Cells (MAGIC) algorithm, to compare correlation results. While the imputation significantly improved the correlations, the top genes correlated with ACE2 are largely the same as the analysis done on un-imputed data. With the uncertainty of the extent imputation artificially distorted the data, we reported the results with no imputation even though the correlations are low. The correlation coefficients for all genes are included as Supplementary Data 1. The top 50 genes in each dataset were characterized based on Gene Ontology classes from the Gene Ontology (GO) database and associated pathways in PathCards from the Pathway Unification database.

We are grateful to Cori Bargmann, Jeremy Farrar, and Sarah Aldridge for stimulating discussions. We thank Jana Eliasova (scientific illustrator) for support with the design of figures, Sarah Sansum for support in document processing, and Martin Prete, Vlad Kiselev and the Wellcome Sanger Cellular Genetics IT Team, as well as Paul Bevan, for support with setting up the website portal. The human embryonic and fetal material was provided by the Joint MRC/Wellcome (MR/R006237/1) Human Developmental Biology Resource (www.hdbr.org).

This publication is part of the Human Cell Atlas - www.humancellatlas.org/publications.

This work was supported by the Wellcome Sanger Institute core funding (WT206194) and the Wellcome Strategic Scientific Support award “Pilot projects for the Human Cell Atlas” (WT211276/Z/18/Z), a Seed Network grant from the Chan Zuckerberg Initiative to P.B., T.D., T.E.D., O.E., P.H., N.H., N.K., M.K., K.B.M., A.M., M.C.N., M.N., D.P., J.R., P.R.T., S.Q., A.R., O.R., M.S., J.S., J.G.S., C.E.S., H.B.S., D.S., A.T., J.W. and K.Z. and by the European Union’s H2020 research and innovation program under grant agreement No 874656 (discovAIR) to P.B., A.B., M.K., S.L., J.L., K.B.M., M.C.N., K.S.P., C.S., H.B.S., J.S., F.J.T. and M.vd.B. W.S. acknowledges funding from the Newton Fund, Medical Research Council (MRC), The Thailand Research Fund (TRF), and Thailand’s National Science and Technology Development Agency (NSTDA). M.C.N acknowledges funding from GSK Ltd, Netherlands Lung Foundation project no. 5.1.14.020 and 4.1.18.226. T.D. acknowledges funding from HubMap consortium and Stanford Child Health Research Institute- Woods Family Faculty Scholarship. T.E.D. acknowledges funding from HubMap. P.H. acknowledges funding from LENDULET-BIOMAG Grant (2018-342) and the European Regional Development Funds (GINOP-2.3.2-15-2016-00006, GINOP-2.3.2-15-2016-00026, GINOP-2.3.2-15-2016-00037). J.L.B. acknowledges funding from Medical Research Council (MRC), and the UK Regenerative Medicine Platform (MR/ 5005579/1). P.B. acknowledges funding from Fondation pour la Recherche Médicale (DEQ20180339158), Agence Nationale de la Recherche (UCAJEDI, ANR-15-IDEX-01; SAHARRA, ANR-19-CE14-0027; France Génomique, ANR-10-INBS-09-03), and Conseil Départemental des Alpes Maritimes (2016-294DGADSH-CV; 2019-390DGADSH-CV). N.E.B. and J.K. acknowledge funding from NIH grant R01HL145372 and DOD grant W81XWH1910416. I.G. acknowledges funding from NIH (5R24HD000836) and the Eunice Kennedy Shriver National Institute of Child Health and Human. N.H., J.G.S. and C.E.S. acknowledge funding by the Leducq foundation. N.H. is recipient of an ERC Advanced Grant. J.K. acknowledges funding from NIH grant K08HL130595 and the Doris Duke Charitable Foundation. N.K. acknowledges funding from NIH grants R01HL127349, U01HL145567 and an unrestricted grant from Three Lakes Foundation. M.K. acknowledges HHMI and Wall Center for Pulmonary Vascular Disease. H.L. acknowledges funding from National Research Foundation of Korea. K.M. acknowledges funding from Wellcome Trust. A.M. acknowledges funding from NIH grants HL135124, AG049665 and AI135964. M.Z.N. acknowledges funding from Rutherford Fund Fellowship allocated by the Medical Research Council and the UK Regenerative Medicine Platform (MR/ 5005579/1 to M.Z.N.). M.Z.N. and M.Y. have been funded by the Rosetrees Grant (Grant number M899). M.N. acknowledges funding from a BHF/DZHK grant and British Heart Foundation (PG/16/47/32156). J.O.-M. acknowledges funding from Richard and Susan Smith Family Foundation. D.P. acknowledges funding from Alan and Sandra Gerry Metastasis and Tumor Ecosystems Center. J.P. acknowledges funding from National Health and Medical Research Council. P.R.T. acknowledges funding from R01HL146557 from NHLBI/NIH. E.L.R. acknowledges funding from MRC MR/P009581/1 and MR/SO35907/1. A.R. and O. R. acknowledge HHMI, the Klarman Cell Observatory, and the Manton Foundation. K.S.-P. acknowledges NIHR Cambridge Biomedical Research Centre. C.S. acknowledges Swedish research Council, Swedish Cancer Society, and CPI. H.B.S. acknowledges German Center for Lung Research and Helmholtz Association. J.S. acknowledges Boehringer Ingelheim, by the German Research Foundation (DFG; EXC2151/1, ImmunoSensation2 - the immune sensory system, project number 390873048), project numbers 329123747, 347286815) and by the HGF grant sparse2big. A.K.S. acknowledges the Beckman Young Investigator Program, a Sloan Fellowship in Chemistry, the NIH (5U24AI118672), and the Bill and Melinda Gates Foundation. F.J.T. acknowledges the German Center for Lung Research. M.vd.B. acknowledges from Ministry of Economic Affairs and Climate Policy by means of the PPP. K.B.W. is funded by the University College London-Birkbeck MRC Doctoral Training Programme. J.W. and Y.Y. acknowledge NIH, U01 HL148856 LungMap Phase II. R.X. acknowledges the NIH (DK043351). H.Z. is supported by the National Key R&D Program (no. 2019YFA0801703) and National Natural Science Foundation of China (no. 31871370)

N.K. was a consultant to Biogen Idec, Boehringer Ingelheim, Third Rock, Pliant, Samumed, NuMedii, Indaloo, Theravance, LifeMax, Three Lake Partners, Optikira in the last three years and received non-financial support from MiRagen. J.L. is a scientific consultant for 10X Genomics Inc. J.K. reports advisory board fees from Boehringer Ingelheim, nonfinancial study support from Genentech, and grant funding from Boehringer Ingelheim. A.R. is a co-founder and equity holder of Celsius Therapeutics, an equity holder in Immunitas, and an SAB member of ThermoFisher Scientific, Syros Pharmaceuticals, Asimov, and Neogene Therapeutics. O.R. is a co-inventor on patent applications filed by the Broad Institute to inventions relating to single cell genomics applications, such as in PCT/US2018/060860 and US Provisional Application No. 62/745,259. A.K.S. reports compensation for consulting and/or SAB membership from Merck, Honeycomb Biotechnologies, Cellarity, Cogen Therapeutics, Orche Bio, and Dahlia Biosciences. F.J.T. reports receiving consulting fees from Roche Diagnostics GmbH, and ownership interest in Cellarity Inc. S.A.T. was a consultant at Genentech, Biogen and Roche in the last three years. L.V. is a founder of Definigen and Bilitech, two biotech companies using hPSCs and organoid for disease modelling and cell-based therapy. F.S. is a founder of Bilitech, a biotechnology company using organoids for cell-based therapy.

*The HCA Lung Biological Network are: Nicholas E. Banovich1, Pascal Barbry2, Alvis Brazma3, Joseph Collin4, Tushar J. Desai5, Thu Elizabeth Duong6,7, Oliver Eickelberg8, Christine Falk9,10, Michael Farzan11, Ian Glass12, Ravindra K. Gupta13, Muzlifah Haniffa4,14,15, Peter Horvath16,17, Norbert Hubner18, Deborah Hung20,21,22, Naftali Kaminski23, Mark Krasnow24, Jonathan A. Kropski25, Malte Kuhnemund26, Majlinda Lako4, Haeock Lee27, Sylvie Leroy2,28, Sten Linnarson29, Joakim Lundeberg30, Kerstin B. Meyer14, Chichau Miao14, Alexander J. Misharin31, Martijn C. Nawijn32, Marko Z. Nikolic33, Michela Noseda34,35, Jose OrdovasMontanes36,37,38,39, Gavin Oudit40, Dana Pe’er41, Joseph Powell42,43, Steve Quake44, Jay Rajagopal39,45, Purushothama Rao Tata46, Emma L. Rawlins47, Aviv Regev38,48,49,50, Paul A. Reyfman51, Orit Rozenblatt-Rosen38,48, Kourosh Saeb-Parsy52, Christos Samakovlis30,53, Herbert B. Schiller54, Joachim L. Schultze55,56, Max Seibold57, Christine E. Seidman20,49,58, Jonathan G. Seidman20, Alex K. Shalek38,59,60, Douglas Shepherd61, Jason Spence62, Avi Spira63,64, Xin Sun65, Sarah A. Teichmann14,66, Fabian J. Theis67, Alexander Tsankov68, Ludovic Vallier69, Maarten van den Berge70, Jeffrey Whitsett71, Ramnik Xavier21,38, Yan Xu72, Laure-Emmanuelle Zaragosi2, Darin Zerti4,73, Hongbo Zhang74, and Kun Zhang75.

1Translational Genomics Research Institute, Phoenix, AZ

2Université Côte d’Azur, CNRS, IPMC, Sophia-Antipolis 06560, France

3European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK

4Biosciences Institute, Faculty of Medical Sciences, Newcastle University, International Centre for Life, Newcastle upon Tyne, UK

5Department of Medicine and Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA

6Department of Pediatrics Division of Respiratory Medicine, University of California San Diego 7Rady Children’s Hospital San Diego, San Diego, CA 92123, USA

8Division of Pulmonary Sciences and Critical Care Medicine, Department of Medicine, University of Colorado, Anschutz Medical Campus, Aurora, CO, US

9Institute of Transplant Immunology, Hannover Medical School, MHH, Carl-Neuberg Str. 1, 30625 Hannover, Germany,

10German Center for Infectious Diseases DZIF, TTU-IICH 07.801

11Department of Immunology and Microbiology, The Scripps Research Institute, Jupiter, Florida, USA (33458)

12Department of Pediatrics, Genetic Medicine, University of Washington, Seattle, Washington

13Cambridge Institute for Therapeutic Immunology and Infectious Diseases, Jeffrey Cheah Biomedical Centre, University of Cambridge, Cambridge CB2 0AW, UK

14Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK

15Department of Dermatology and NIHR Newcastle Biomedical Research Centre, Newcastle Hospitals NHS Foundation Trust, Newcastle upon Tyne NE2 4LP, UK

16Synthetic and Systems Biology Unit, Biological Research Centre (BRC), Szeged, Hungary

17Institute for Molecular Medicine Finland, University of Helsinki

18Cardiovascular and Metabolic Sciences, Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), 13125 Berlin, Germany

19DZHK (German Centre for Cardiovascular Research), Partner Site Berlin, 13347 Berlin, Germany

20Department of Genetics,Harvard Medical School, Boston, MA 02115, USA

21Department of Molecular Biology at Massachusetts General Hospital, Boston, MA 02114, USA

21Infectious Disease and Microbiome Program, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA

23Pulmonary, Critical Care and Sleep Medicine, Yale University School of Medicine, New Haven, CT 06520, USA

24Department of Biochemistry and Wall Center for Pulmonary Vascular Disease, Howard Hughes Medical Institute, Stanford University School of Medicine, Stanford, CA 94305, USA

25Division of Allergy, Pulmonary and Critical Care Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, Department of Veterans Affairs Medical Center, Nashville, TN; Department of Cell and Developmental Biology, Vanderbilt University, Nashville, TN

26Cartana AB, Nobels vag 16, 17165 Stockholm, Sweden

27Department of Biomedicine and Health Sciences, The Catholic University of Korea, Seoul, Korea

28Institut de Pharmacologie Moléculaire et Cellulaire, Sophia Antipolis, France

29Division of Molecular Neurobiology, Department of Medical Biochemistry and Biophysics, Karolinska Institute

30SciLifeLab, Stockholm University, 17121, Solna, Sweden

31Division of Pulmonary and Critical Care Medicine, Northwestern University, Chicago, Illinois 60611, USA

32Department of Pathology and Medical Biology, University of Groningen, GRIAC Research Institute, University Medical Center Groningen, 9713 AV Groningen, Netherlands

33UCL Respiratory, Division of Medicine, University College London, WC1E 6JF, London, UK

34National Heart and Lung Institute, Imperial College London, UK

35British Heart Foundation Centre for Research Excellence and Centre for Regenerative Medicine, Imperial College London, UK

36Division of Gastroenterology Boston Children’s Hospital, Boston, MA 02115, USA

37Program in Immunology, Harvard Medical School, Boston, MA 02115, USA

38Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA

39Harvard Stem Cell Institute, Cambridge, MA 02138, USA

40Canada Research Chair in Heart Failure, Division of Cardiology, 2C2 Walter Mackenzie Health Sciences Centre, Edmonton, Alberta, T6G 2B7, Canada

41Computational and Systems Biology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, New York 10065, USA

42Garvan-Weizmann Centre for Cellular Genomics, Garvan Institute of Medical Research, Sydney, NSW, Australia

43UNSW Cellular Genomics Futures Institute, University of New South Wales, Sydney, NSW, Australia

44Depts of Bioengineering and Applied Physics, Stanford University, and the Chan Zuckerberg Biohub, Stanford University, Stanford, CA 94305, USA

45Center for Regenerative Medicine, Massachusetts General Hospital, Boston, MA 02114, Boston

46Department of Cell Biology, Regeneration Next Initiative, Duke University School of Medicine, Durham, NC 27710, USA

47Wellcome Trust/CRUK Gurdon Institute and Department Physiology, Development and Neuroscience, University of Cambridge, Cambridge, CB2 1QN, UK

48Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA

49Howard Hughes Medical Institute, Chevy Chase, MD 20815, USA

50Department of Biology, Massachusetts Institute of Technology, Cambridge, MA 02142, USA

51Northwestern University Feinberg School of Medicine, Division of Pulmonary and Critical Care Medicine

52Department of Surgery, University of Cambridge and NIHR Cambridge Biomedical Research Centre, CB2 0QQ, UK

53Cardiopulmonary Institute, Justus Liebig University; Giessen Germany

54Comprehensive Pneumology Center (CPC) / Institute of Lung Biology and Disease (ILBD), Helmholtz Zentrum München, Member of the German Center for Lung Research (DZL), Munich, Germany

55Department for Genomics & Immunoregulation, LIMES-Institute, University of Bonn, 53115 Bonn, Germany Department of Pediatrics; Center for Genes, Environment, and Health

56PRECISE Platform for Single Cell Genomics & Epigenomics, German Center for Neurodegenerative Diseases and University of Bonn, Bonn, Germany

57Department of Pediatrics, Center for Genes, Environment, and Health, National Jewish Health; Denver, CO 80206

58Cardiovascular Division, Brigham & Women’s Hospital, Boston, MA 02115, USA

59Ragon Institute of MGH, MIT, and Harvard, Cambridge, MA, USA

60Institute for Medical Engineering and Science (IMES), Koch Institute for Integrative Cancer Research, and Department of Chemistry, Massachusetts Institute of Technology, Cambridge, MA, USA;

61Center for Biological Physics and Department of Physics, Arizona State University, Tempe, AZ 85287, USA

62Department of Internal Medicine, Gastroenterology, University of Michigan Medical School, Ann Arbor, MI 48109, USA; Department of Cell and Developmental Biology, University of Michigan Medical School, Ann Arbor, MI 48109, USA; Department of Biomedical Engineering, University of Michigan College of Engineering, Ann Arbor, MI 48109, USA.

63Department of Medicine, Boston University School of Medicine, Boston, MA, USA

64Johnson & Johnson Innovation, Cambridge, MA, USA.

65Department of Pediatrics, Department of Biological Sciences, University of California SD, 9500 Gilman Dr. MC0766, San Diego, CA 92093, USA

66Theory of Condensed Matter Group, Cavendish Laboratory/Department of Physics, University of Cambridge, Cambridge CB3 0HE, UK

67Institute of Computational Biology, Helmholtz Zentrum München and Departments of Mathematics and Life Sciences, Technical University Munich, Germany

68Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA

69Wellcome and MRC Cambridge Stem Cell Institute, Jeffrey Cheah Biomedical Centre, Biomedical Campus, Puddicombe Way, Cambridge CB2 0AW, UK; Department of Surgery, Cambridge Biomedical Campus, Hills Rd, Cambridge, CB2 0QQ, UK

70Department of Pulmonary diseases and tuberculosis, University of Groningen, GRIAC Research Institute, University Medical Center Groningen, 9713 AV Groningen, Netherlands

71Cincinnati Children’s Hospital Medical Center, Cincinnati, OHIO

72Divisions of Pulmonary Biology and Biomedical Informatics; Perinatal Institute, Cincinnati Children’s Hospital Medical Center; University of Cincinnati College of Medicine

73Microscopy Centre and Department of Applied Clinical Sciences and Biotechnology, University of L’Aquila, via Vetoio, 67100 Coppito, L’Aquila, Italy

74Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education and Department of Histology and Embryology of Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou 510080, China

75UCSD Department of Bioengineering, 9500 Gilman Drive, MC0412, PFBH402, La Jolla, CA 92093, USA

Pascal Barbry, Alexander Misharin, Martijn Nawijn and Jay Rajagopal serve as the coordinators for the HCA Lung Biological Network.

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