作者
Boyi Cong,Xuan Dong,Zongheng Yang,Pin Yü,Yangyang Chai,Jiaqi Liu,Meihan Zhang,Yupeng Zang,Jingmin Kang,Yu Feng,Yi Liu,Weimin Feng,Dehe Wang,Wei Deng,Fengdi Li,Zhiqi Song,Ziqiao Wang,Xiaosu Chen,Hua Qin,Qinyi Yu,Zhiqing Li,Shuxun Liu,Xun Xu,Nanshan Zhong,Xianwen Ren,Chuan Qin,Longqi Liu,Jian Wang,Xuetao Cao
摘要
Abstract How immune cells are spatiotemporally coordinated in the lung to effectively monitor, respond to, and resolve infection and inflammation in primed form needs to be fully illustrated. Here we apply immunocartography, a high-resolution technique that integrates spatial and single-cell RNA sequencing (scRNA-seq) through deconvolution and co-localization analyses, to the SARS-CoV-2-infected Syrian hamster model. We generate a comprehensive transcriptome map of the whole process of pulmonary infection from physiological condition, infection initiation, severe pneumonia to natural recovery at organ scale and single-cell resolution, with 142,965 cells and 45 lung lobes from 25 hamsters at 5 time points. Integrative analysis identifies that alveolar dendritic cell–T cell immunity hubs, where Ccr7 + Ido1 + dendritic cells, Cd160 + Cd8 + T cells, and Tnfrsf4 + Cd4 + T cells physiologically co-localize, rapidly expand during SARS-CoV-2 infection, eliminate SARS-CoV-2 with the aid of Slamf9 + macrophages, and then restore to physiological levels after viral clearance. We verify the presence of these cell subpopulations in the immunity hubs in normal and SARS-CoV-2-infected hACE2 mouse models, as well as in publicly available human scRNA-seq datasets, demonstrating the potential broad relevance of our findings in lung immunity.