{"database":"iProX","file_versions":[],"scores":null,"additional":{"omics_type":["Proteomics"],"submitter":["Guanghui Liu"],"species":["Homo Sapiens"],"full_dataset_link":["http://www.iprox.org/page/project.html?id=IPX0003571000"],"submitter_email":["ghliu@ioz.ac.cn"],"submitter_affiliation":["Institute of Zoology, Chinese Academy of Science"],"sample_protocol":[""],"repository":["iProX"],"data_protocol":[""],"pubmed_abstract":["The lung is the primary organ targeted by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), making respiratory failure a leading coronavirus disease 2019 (COVID-19)-related mortality. However, our cellular and molecular understanding of how SARS-CoV-2 infection drives lung pathology is limited. Here we constructed multi-omics and single-nucleus transcriptomic atlases of the lungs of patients with COVID-19, which integrate histological, transcriptomic and proteomic analyses. Our work reveals the molecular basis of pathological hallmarks associated with SARS-CoV-2 infection in different lung and infiltrating immune cell populations. We report molecular fingerprints of hyperinflammation, alveolar epithelial cell exhaustion, vascular changes and fibrosis, and identify parenchymal lung senescence as a molecular state of COVID-19 pathology. Moreover, our data suggest that FOXO3A suppression is a potential mechanism underlying the fibroblast-to-myofibroblast transition associated with COVID-19 pulmonary fibrosis. Our work depicts a comprehensive cellular and molecular atlas of the lungs of patients with COVID-19 and provides insights into SARS-CoV-2-related pulmonary injury, facilitating the identification of biomarkers and development of symptomatic treatments."],"pubmed_title":["A single-cell transcriptomic landscape of the lungs of patients with COVID-19."],"pubmed_authors":["Wang Si S, Yao Xiaohong X, Ma Shuai S, Ping Yifang Y, Fan Yanling Y, Sun Shuhui S, He Zhicheng Z, Shi Yu Y, Sun Liang L, Xiao Shiqi S, Song Moshi M, Cai Jun J, Li Jiaming J, Tang Rui R, Zhao Liyun L, Wang Chaofu C, Wang Qiaoran Q, Zhao Lei L, Hu Huifang H, Liu Xindong X, Sun Guoqiang G, Chen Lu L, Pan Guoqing G, Chen Huaiyong H, Li Qingrui Q, Zhang Peipei P, Xu Yuanyuan Y, Feng Huyi H, Zhao Guo-Guang GG, Wen Tianzi T, Yang Yungui Y, Huang Xuequan X, Li Wei W, Liu Zhenhua Z, Wang Hongmei H, Wu Haibo H, Hu Baoyang B, Ren Yong Y, Zhou Qi Q, Qu Jing J, Zhang Weiqi W, Liu Guang-Hui GH, Bian Xiu-Wu XW"],"additional_accession":[]},"is_claimable":false,"name":"Proteomics dataset of COVID-19 and control patients","description":"Proteomics dataset of COVID-19 and control patients","dates":{"publication":"Thu Oct 14 00:00:00 BST 2021"},"accession":"PXD029023","cross_references":{"TAXONOMY":["9606"],"pubmed":["34876692"]}}