Europe PMC
Nothing Special   »   [go: up one dir, main page]

Europe PMC requires Javascript to function effectively.

Either your web browser doesn't support Javascript or it is currently turned off. In the latter case, please turn on Javascript support in your web browser and reload this page.

This website requires cookies, and the limited processing of your personal data in order to function. By using the site you are agreeing to this as outlined in our privacy notice and cookie policy.

Abstract 


It has been known that, the novel coronavirus, 2019-nCoV, which is considered similar to SARS-CoV, invades human cells via the receptor angiotensin converting enzyme II (ACE2). Moreover, lung cells that have ACE2 expression may be the main target cells during 2019-nCoV infection. However, some patients also exhibit non-respiratory symptoms, such as kidney failure, implying that 2019-nCoV could also invade other organs. To construct a risk map of different human organs, we analyzed the single-cell RNA sequencing (scRNA-seq) datasets derived from major human physiological systems, including the respiratory, cardiovascular, digestive, and urinary systems. Through scRNA-seq data analyses, we identified the organs at risk, such as lung, heart, esophagus, kidney, bladder, and ileum, and located specific cell types (i.e., type II alveolar cells (AT2), myocardial cells, proximal tubule cells of the kidney, ileum and esophagus epithelial cells, and bladder urothelial cells), which are vulnerable to 2019-nCoV infection. Based on the findings, we constructed a risk map indicating the vulnerability of different organs to 2019-nCoV infection. This study may provide potential clues for further investigation of the pathogenesis and route of 2019-nCoV infection.

Free full text 


Logo of phenaturepgLink to Publisher's site
Front Med. 2020; 14(2): 185–192.
Published online 2020 Mar 12. https://doi.org/10.1007/s11684-020-0754-0
PMCID: PMC7088738
PMID: 32170560

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

Associated Data

Supplementary Materials

Abstract

It has been known that, the novel coronavirus, 2019-nCoV, which is considered similar to SARS-CoV, invades human cells via the receptor angiotensin converting enzyme II (ACE2). Moreover, lung cells that have ACE2 expression may be the main target cells during 2019-nCoV infection. However, some patients also exhibit non-respiratory symptoms, such as kidney failure, implying that 2019-nCoV could also invade other organs. To construct a risk map of different human organs, we analyzed the single-cell RNA sequencing (scRNA-seq) datasets derived from major human physiological systems, including the respiratory, cardiovascular, digestive, and urinary systems. Through scRNA-seq data analyses, we identified the organs at risk, such as lung, heart, esophagus, kidney, bladder, and ileum, and located specific cell types (i.e., type II alveolar cells (AT2), myocardial cells, proximal tubule cells of the kidney, ileum and esophagus epithelial cells, and bladder urothelial cells), which are vulnerable to 2019-nCoV infection. Based on the findings, we constructed a risk map indicating the vulnerability of different organs to 2019-nCoV infection. This study may provide potential clues for further investigation of the pathogenesis and route of 2019-nCoV infection.

Electronic Supplementary Material

Supplementary material is available for this article at 10.1007/s11684-020-0754-0 and is accessible for authorized users.

Keywords: 2019-nCoV, ACE2, single-cell RNA-seq

Electronic Supplementary Material

Acknowledgements

This work was supported in part by the China National Science and Technology Major Project for Prevention and Treatment of Infectious Diseases (No. 2017ZX10203207 to Z.-G. H.), National Natural Science Foundation of China (No. 81672772 to Z.-G. H., No. 31601070 to J. H., No. 31800253 to K. C.), Interdisciplinary Program of Shanghai Jiao Tong University (Nos. 2019TPA09 and ZH2018ZDA33 to Z.-G. H., J. H., and X. Z.), Shanghai Sailing Program (No. 17YF1410400 to K. C.) and Innovative Research Team of High-Level Local Universities in Shanghai.

Compliance with ethics guidelines

Xin Zou, Ke Chen, Jiawei Zou, Peiyi Han, Jie Hao, and Zeguang Han declare that they have no conflict of interest. This manuscript does not involve a research protocol requiring approval by the relevant institutional review board or ethics committee.

Footnotes

The authors wish it to be known that, in their opinion, the first three authors should be regarded as Joint First Authors.

Contributor Information

Jie Hao, nc.ude.utjs@oah.j.

Zeguang Han, nc.ude.utjs@gznah.

References

1. WHO. Statement on the second meeting of the International Health Regulations (2005) Emergency Committee regarding the outbreak of novel coronavirus (2019-nCoV). 2020. https://www.who.int/news-room/detail/30-01-2020-statement-on-the-second-meeting-of-the-international-health-regulations-(2005)-emergency-committee-regarding-the-outbreak-of-novel-coronavirus-(2019-ncov) (accessed Janaury 30, 2020)
2. Xu X, Chen P, Wang J, Feng J, Zhou H, Li X, Zhong W, Hao P. Evolution of the novel coronavirus from the ongoing Wuhan outbreak and modeling of its spike protein for risk of human transmission. Science China Life Sciences. 2020;63(3):457–460. 10.1007/s11427-020-1637-5. [Europe PMC free article] [Abstract] [CrossRef] [Google Scholar]
3. Zhou P, Yang X-L, Wang X-G, Hu B, Zhang L, Zhang W, Si H-R, Zhu Y, Li B, Huang C-L, Chen H-D, Chen J, Luo Y, Guo H, Jiang R-D, Liu M-Q, Chen Y, Shen X-R, Wang X, Zheng X-S, Zhao K, Chen Q-J, Deng F, Liu L-L, Yan B, Zhan F-X, Wang Y-Y, Xiao G-F, Shi Z-L. A pneumonia outbreak associated with a new coronavirus of probable bat origin. Nature. 2020;579(7798):270–273. 10.1038/s41586-020-2012-7. [Europe PMC free article] [Abstract] [CrossRef] [Google Scholar]
4. Reyfman PA, Walter JM, Joshi N, Anekalla KR, McQuattie-Pimentel AC, Chiu S, Fernandez R, Akbarpour M, Chen CI, Ren Z, Verma R, Abdala-Valencia H, Nam K, Chi M, Han S, Gonzalez-Gonzalez FJ, Soberanes S, Watanabe S, Williams KJN, Flozak AS, Nicholson TT, Morgan VK, Winter DR, Hinchcliff M, Hrusch CL, Guzy RD, Bonham CA, Sperling AI, Bag R, Hamanaka RB, Mutlu GM, Yeldandi AV, Marshall SA, Shilatifard A, Amaral LAN, Perlman H, Sznajder JI, Argento AC, Gillespie CT, Dematte J, Jain M, Singer BD, Ridge KM, Lam AP, Bharat A, Bhorade SM, Gottardi CJ, Budinger GRS, Misharin AV. Single-cell transcriptomic analysis of human lung provides insights into the pathobiology of pulmonary fibrosis. Am J Respir Crit Care Med. 2019;199(12):1517–1536. 10.1164/rccm.201712-2410OC. [Europe PMC free article] [Abstract] [CrossRef] [Google Scholar]
5. Ruiz García S, Deprez M, Lebrigand K, Cavard A, Paquet A, Arguel MJ, Magnone V, Truchi M, Caballero I, Leroy S, Marquette CH, Marcet B, Barbry P, Zaragosi LE. Novel dynamics of human mucociliary differentiation revealed by single-cell RNA sequencing of nasal epithelial cultures. Development. 2019;146(20):146. 10.1242/dev.177428. [Europe PMC free article] [Abstract] [CrossRef] [Google Scholar]
6. Cui Y, Zheng Y, Liu X, Yan L, Fan X, Yong J, Hu Y, Dong J, Li Q, Wu X, Gao S, Li J, Wen L, Qiao J, Tang F. Single-cell transcriptome analysis maps the developmental track of the human heart. Cell Rep. 2019;26(7):1934–1950. 10.1016/j.celrep.2019.01.079. [Abstract] [CrossRef] [Google Scholar]
7. Madissoon E, Wilbrey-Clark A, Miragaia RJ, Saeb-Parsy K, Mahbubani KT, Georgakopoulos N, Harding P, Polanski K, Huang N, Nowicki-Osuch K, Fitzgerald RC, Loudon KW, Ferdinand JR, Clatworthy MR, Tsingene A, van Dongen S, Dabrowska M, Patel M, Stubbington MJT, Teichmann SA, Stegle O, Meyer KB. scRNA-seq assessment of the human lung, spleen, and esophagus tissue stability after cold preservation. Genome Biol. 2020;21(1):1. 10.1186/s13059-019-1906-x. [Europe PMC free article] [Abstract] [CrossRef] [Google Scholar]
8. Zhang P, Yang M, Zhang Y, Xiao S, Lai X, Tan A, Du S, Li S. Dissecting the single-cell transcriptome network underlying gastric premalignant lesions and early gastric cancer. Cell Rep. 2019;27(6):1934–1947. 10.1016/j.celrep.2019.04.052. [Abstract] [CrossRef] [Google Scholar]
9. MacParland SA, Liu JC, Ma XZ, Innes BT, Bartczak AM, Gage BK, Manuel J, Khuu N, Echeverri J, Linares I, Gupta R, Cheng ML, Liu LY, Camat D, Chung SW, Seliga RK, Shao Z, Lee E, Ogawa S, Ogawa M, Wilson MD, Fish JE, Selzner M, Ghanekar A, Grant D, Greig P, Sapisochin G, Selzner N, Winegarden N, Adeyi O, Keller G, Bader GD, McGilvray ID. Single cell RNA sequencing of human liver reveals distinct intrahepatic macrophage populations. Nat Commun. 2018;9(1):4383. 10.1038/s41467-018-06318-7. [Europe PMC free article] [Abstract] [CrossRef] [Google Scholar]
10. Martin JC, Chang C, Boschetti G, Ungaro R, Giri M, Grout JA, Gettler K, Chuang LS, Nayar S, Greenstein AJ, Dubinsky M, Walker L, Leader A, Fine JS, Whitehurst CE, Mbow ML, Kugathasan S, Denson LA, Hyams JS, Friedman JR, Desai PT, Ko HM, Laface I, Akturk G, Schadt EE, Salmon H, Gnjatic S, Rahman AH, Merad M, Cho JH, Kenigsberg E. Single-cell analysis of Crohn’s disease lesions identifies a pathogenic cellular module associated with resistance to anti-TNF therapy. Cell. 2019;178(6):1493–1508. 10.1016/j.cell.2019.08.008. [Europe PMC free article] [Abstract] [CrossRef] [Google Scholar]
11. Wu H, Malone AF, Donnelly EL, Kirita Y, Uchimura K, Ramakrishnan SM, Gaut JP, Humphreys BD. Single-cell transcriptomics of a human kidney allograft biopsy specimen defines a diverse inflammatory response. J Am Soc Nephrol. 2018;29(8):2069–2080. 10.1681/ASN.2018020125. [Europe PMC free article] [Abstract] [CrossRef] [Google Scholar]
12. Yu Z, Liao J, Chen Y, Zou C, Zhang H, Cheng J, Liu D, Li T, Zhang Q, Li J, Yang X, Ye Y, Huang Z, Long X, Yang R, Mo Z. Single-cell transcriptomic map of the human and mouse bladders. J Am Soc Nephrol. 2019;30(11):2159–2176. 10.1681/ASN.2019040335. [Europe PMC free article] [Abstract] [CrossRef] [Google Scholar]
13. Becht E, McInnes L, Healy J, Dutertre CA, Kwok IWH, Ng LG, Ginhoux F, Newell EW. Dimensionality reduction for visualizing single-cell data using UMAP. Nat Biotechnol. 2019;37:38–44. 10.1038/nbt.4314. [Abstract] [CrossRef] [Google Scholar]
14. Hamming I, Timens W, Bulthuis MLC, Lely AT, Navis G, van Goor H. Tissue distribution of ACE2 protein, the functional receptor for SARS coronavirus. A first step in understanding SARS pathogenesis. J Pathol. 2004;203(2):631–637. 10.1002/path.1570. [Europe PMC free article] [Abstract] [CrossRef] [Google Scholar]
15. Crackower MA, Sarao R, Oudit GY, Yagil C, Kozieradzki I, Scanga SE, Oliveira-dos-Santos AJ, da Costa J, Zhang L, Pei Y, Scholey J, Ferrario CM, Manoukian AS, Chappell MC, Backx PH, Yagil Y, Penninger JM. Angiotensin-converting enzyme 2 is an essential regulator of heart function. Nature. 2002;417(6891):822–828. 10.1038/nature00786. [Abstract] [CrossRef] [Google Scholar]
16. Kowalczuk S, Bröer A, Tietze N, Vanslambrouck JM, Rasko JEJ, Bröer S. A protein complex in the brush-border membrane explains a Hartnup disorder allele. FASEB J. 2008;22(8):2880–2887. 10.1096/fj.08-107300. [Abstract] [CrossRef] [Google Scholar]
17. Donoghue M, Hsieh F, Baronas E, Godbout K, Gosselin M, Stagliano N, Donovan M, Woolf B, Robison K, Jeyaseelan R, Breitbart RE, Acton S. A novel angiotensin-converting enzyme-related carboxypeptidase (ACE2) converts angiotensin I to angiotensin 1–9. Circ Res. 2000;87(5):E1–E9. 10.1161/01.RES.87.5.e1. [Abstract] [CrossRef] [Google Scholar]
18. Harmer D, Gilbert M, Borman R, Clark KL. Quantitative mRNA expression profiling of ACE 2, a novel homologue of angiotensin converting enzyme. FEBS Lett. 2002;532(1–2):107–110. 10.1016/S0014-5793(02)03640-2. [Abstract] [CrossRef] [Google Scholar]
19. Burrell LM, Risvanis J, Kubota E, Dean RG, MacDonald PS, Lu S, Tikellis C, Grant SL, Lew RA, Smith AI, Cooper ME, Johnston CI. Myocardial infarction increases ACE2 expression in rat and humans. Eur Heart J. 2005;26(4):369–375. 10.1093/eurheartj/ehi114. [Abstract] [CrossRef] [Google Scholar]

Citations & impact 


Impact metrics

Jump to Citations
Jump to Data

Citations of article over time

Alternative metrics

Altmetric item for https://www.altmetric.com/details/77538095
Altmetric
Discover the attention surrounding your research
https://www.altmetric.com/details/77538095

Smart citations by scite.ai
Smart citations by scite.ai include citation statements extracted from the full text of the citing article. The number of the statements may be higher than the number of citations provided by EuropePMC if one paper cites another multiple times or lower if scite has not yet processed some of the citing articles.
Explore citation contexts and check if this article has been supported or disputed.
https://scite.ai/reports/10.1007/s11684-020-0754-0

Supporting
Mentioning
Contrasting
68
1940
3

Article citations


Go to all (1,297) article citations

Data 


Data behind the article

This data has been text mined from the article, or deposited into data resources.

Similar Articles 


To arrive at the top five similar articles we use a word-weighted algorithm to compare words from the Title and Abstract of each citation.