Single-cell landscape of bronchoalveolar immune cells in patients with COVID-19.
Mingfeng Liao, Yang Liu, Jing Yuan, Yanling Wen, Gang Xu, Juanjuan Zhao, Lin Cheng, Jinxiu Li, Xin Wang, Fuxiang Wang, Lei Liu, Ido Amit, Shuye Zhang, Zheng Zhang
Author Information
Mingfeng Liao: Institute for Hepatology, National Clinical Research Center for Infectious Disease, Shenzhen Third People's Hospital, Shenzhen, China.
Yang Liu: Institute for Hepatology, National Clinical Research Center for Infectious Disease, Shenzhen Third People's Hospital, Shenzhen, China.
Jing Yuan: Department for Infectious Diseases, Shenzhen Third People's Hospital, Shenzhen, China.
Yanling Wen: Institute for Hepatology, National Clinical Research Center for Infectious Disease, Shenzhen Third People's Hospital, Shenzhen, China.
Gang Xu: Institute for Hepatology, National Clinical Research Center for Infectious Disease, Shenzhen Third People's Hospital, Shenzhen, China.
Juanjuan Zhao: Institute for Hepatology, National Clinical Research Center for Infectious Disease, Shenzhen Third People's Hospital, Shenzhen, China.
Lin Cheng: Institute for Hepatology, National Clinical Research Center for Infectious Disease, Shenzhen Third People's Hospital, Shenzhen, China.
Jinxiu Li: Department for Infectious Diseases, Shenzhen Third People's Hospital, Shenzhen, China.
Xin Wang: Institute for Hepatology, National Clinical Research Center for Infectious Disease, Shenzhen Third People's Hospital, Shenzhen, China.
Fuxiang Wang: Department for Infectious Diseases, Shenzhen Third People's Hospital, Shenzhen, China.
Lei Liu: Institute for Hepatology, National Clinical Research Center for Infectious Disease, Shenzhen Third People's Hospital, Shenzhen, China. liulei3322@aliyun.com.
Ido Amit: Department of Immunology, Weizmann Institute of Science, Rehovot, Israel. ido.amit@weizmann.ac.il. ORCID
Shuye Zhang: Shanghai Public Health Clinical Center, Fudan University, Shanghai, China. zhangshuye@shphc.org.cn. ORCID
Zheng Zhang: Institute for Hepatology, National Clinical Research Center for Infectious Disease, Shenzhen Third People's Hospital, Shenzhen, China. zhangzheng1975@aliyun.com. ORCID
Respiratory immune characteristics associated with Coronavirus Disease 2019 (COVID-19) severity are currently unclear. We characterized bronchoalveolar lavage fluid immune cells from patients with varying severity of COVID-19 and from healthy people by using single-cell RNA sequencing. Proinflammatory monocyte-derived macrophages were abundant in the bronchoalveolar lavage fluid from patients with severe COVID-9. Moderate cases were characterized by the presence of highly clonally expanded CD8 T cells. This atlas of the bronchoalveolar immune microenvironment suggests potential mechanisms underlying pathogenesis and recovery in COVID-19.
References
Channappanavar, R. et al. Dysregulated type I interferon and inflammatory monocyte-macrophage responses cause lethal pneumonia in SARS-CoV-Infected mice. Cell Host Microbe 19, 181–193 (2016).
[DOI: 10.1016/j.chom.2016.01.007]
Liu, L. et al. Anti–spike IgG causes severe acute lung injury by skewing macrophage responses during acute SARS-CoV infection. JCI Insight 4, e123158 (2019).
[DOI: 10.1172/jci.insight.123158]
Cao, X. COVID-19: immunopathology and its implications for therapy. Nat. Rev. Immunol. 20, 269–270 (2020).
[DOI: 10.1038/s41577-020-0308-3]
Morse, C. et al. Proliferating SPP1/MERTK-expressing macrophages in idiopathic pulmonary fibrosis. Eur. Respir. J. 54, 1802441 (2019).
[DOI: 10.1183/13993003.02441-2018]
Reyfman, P. A. et al. Single-cell transcriptomic analysis of human lung provides insights into the pathobiology of pulmonary fibrosis. Am. J. Respir. Crit. Care Med. 199, 1517–1536 (2019).
[DOI: 10.1164/rccm.201712-2410OC]
Evren, E., Ringqvist, E. & Willinger, T. Origin and ontogeny of lung macrophages: from mice to humans. Immunology https://doi.org/10.1111/imm.13154 (2019).
Bonnardel, J. & Guilliams, M. Developmental control of macrophage function. Curr. Opin. Immunol. 50, 64–74 (2018).
[DOI: 10.1016/j.coi.2017.12.001]
Liu, W. J. et al. T cell immunity of SARS-CoV: implications for vaccine development against MERS-CoV. Antiviral Res. 137, 82–92 (2017).
[DOI: 10.1016/j.antiviral.2016.11.006]
Channappanavar, R., Fett, C., Zhao, J., Meyerholz, D. K. & Perlman, S. Virus-specific memory CD8 T cells provide substantial protection from lethal severe acute respiratory syndrome coronavirus infection. J. Virol. 88, 11034–11044 (2014).
[DOI: 10.1128/JVI.01505-14]
Zhao, J., Zhao, J. & Perlman, S. T cell responses are required for protection from clinical disease and for virus clearance in severe acute respiratory syndrome coronavirus-infected mice. J. Virol. 84, 9318–9325 (2010).
[DOI: 10.1128/JVI.01049-10]
Kumar, B. V. et al. Human tissue-resident memory T cells are defined by core transcriptional and functional signatures in lymphoid and mucosal sites. Cell Rep. 20, 2921–2934 (2017).
[DOI: 10.1016/j.celrep.2017.08.078]
Huang, C. et al. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. Lancet 395, 497–506 (2020).
[DOI: 10.1016/S0140-6736(20)30183-5]
Zhou, F. et al. COVID-19 with spontaneous pneumomediastinum. Lancet 20, 384–510 (2020).
[DOI: 10.1016/S1473-3099(20)30134-1]
Chen, G. et al. Hepatitis C virus-specific CD4 T cell phenotype and function in different infection outcomes. J. Clin. Invest. 130, 768–773 (2020).
[DOI: 10.1172/JCI126277]
Dobin, A. et al. STAR: ultrafast universal RNA-seq aligner. Bioinformatics 29, 15–21 (2013).
[DOI: 10.1093/bioinformatics/bts635]
Stuart, T. et al. Comprehensive Integration of single-cell data. Cell 177, 1888–1902 (2019).
[DOI: 10.1016/j.cell.2019.05.031]
Finak, G. et al. MAST: a flexible statistical framework for assessing transcriptional changes and characterizing heterogeneity in single-cell RNA sequencing data. Genome Biol. 16, 278 (2015).
[DOI: 10.1186/s13059-015-0844-5]
Aibar, S. et al. SCENIC: single-cell regulatory network inference and clustering. Nat. Methods 14, 1083–1086 (2017).
[DOI: 10.1038/nmeth.4463]
Subramanian, A. et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc. Natl Acad. Sci. USA 102, 15545–15550 (2005).
[DOI: 10.1073/pnas.0506580102]
Yu, G., Wang, L. G., Han, Y. & He, Q. Y. clusterProfiler: an R package for comparing biological themes among gene clusters. OMICS 16, 284–287 (2012).
[DOI: 10.1089/omi.2011.0118]
Liberzon, A. et al. The molecular signatures database hallmark gene set collection. Cell Syst. 1, 417–425 (2015).
[DOI: 10.1016/j.cels.2015.12.004]
Pont, F., Tosolini, M. & Fournie, J. J. Single-cell signature explorer for comprehensive visualization of single cell signatures across scRNA-seq datasets. Nucleic Acids Res. 47, e133–e133 (2019).
[DOI: 10.1093/nar/gkz601]
Grants
202002073000002/Shenzhen Science and Technology Innovation Commission
