Jin Kang, Bardes Eric E, Mitelpunkt Alexis, Wang Jake Y, Bhatnagar Surbhi, Sengupta Soma, Krummel Daniel Pomeranz, Rothenberg Marc E, Aronow Bruce J
Division of Biomedical Informatics, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, 45229, USA.
Department of Biomedical Informatics, University of Cincinnati, Cincinnati, OH, 45229, USA.
bioRxiv. 2021 Jun 16:2021.06.07.447287. doi: 10.1101/2021.06.07.447287.
Numerous studies have provided single-cell transcriptome profiles of host responses to SARS-CoV-2 infection. Critically lacking however is a datamine that allows users to compare and explore cell profiles to gain insights and develop new hypotheses. To accomplish this, we harmonized datasets from COVID-19 and other control condition blood, bronchoalveolar lavage, and tissue samples, and derived a compendium of gene signature modules per cell type, subtype, clinical condition, and compartment. We demonstrate approaches to probe these via a new interactive web portal (http://toppcell.cchmc.org/COVID-19). As examples, we develop three hypotheses: (1) a multicellular signaling cascade among alternatively differentiated monocyte-derived macrophages whose tasks include T cell recruitment and activation; (2) novel platelet subtypes with drastically modulated expression of genes responsible for adhesion, coagulation and thrombosis; and (3) a multilineage cell activator network able to drive extrafollicular B maturation via an ensemble of genes strongly associated with risk for developing post-viral autoimmunity.
许多研究已经提供了宿主对SARS-CoV-2感染反应的单细胞转录组图谱。然而,至关重要的是缺乏一个数据库,该数据库能让用户比较和探索细胞图谱,以获得见解并提出新的假设。为了实现这一点,我们整合了来自COVID-19和其他对照条件下的血液、支气管肺泡灌洗和组织样本的数据集,并针对每种细胞类型、亚型、临床状况和区室得出了基因特征模块的汇总。我们展示了通过一个新的交互式门户网站(http://toppcell.cchmc.org/COVID-19)来探究这些数据的方法。例如,我们提出了三个假设:(1)交替分化的单核细胞衍生巨噬细胞之间的多细胞信号级联反应,其任务包括T细胞招募和激活;(2)具有负责黏附、凝血和血栓形成的基因表达大幅调节的新型血小板亚型;(3)一个多谱系细胞激活网络,能够通过一组与病毒后自身免疫风险密切相关的基因驱动滤泡外B细胞成熟。