摘要：SummaryNumerous studies have provided single-cell transcriptome profiles of host responses to SARS-CoV-2 infection. Critically lacking however is a data mine 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 interacting with, exploring, and functional evaluating these modules via a new interactive web portal ToppCell (http://toppcell.cchmc.org/). As examples, we develop three hypotheses: (1) alternatively-differentiated monocyte-derived macrophages form a multicelllar signaling cascade that drives T cell recruitment and activation; (2) COVID-19-generated platelet subtypes exhibit dramatically altered potential to adhere, coagulate, and thrombose; and (3) extrafollicular B maturation is driven by a multilineage cell activation network that expresses an ensemble of genes strongly associated with risk for developing post-viral autoimmunity.Graphical abstractDisplay OmittedHighlights•Topp-toolkit creates the first COVID-19 immune signature atlas•Monocytic cell subtypes form a signaling cascade capable of creating the cytokine storm of severe COVID-19•Activated platelets display dysregulated expression of adhesion, activation, and coagulation genes with upregulated heparanase•Autoantibody generation outside of germinal centers is promoted by multilineage multicellular activator network of autoimmunity-associated genesVirology; Systems Immunobiology; Omics; Transcriptomics, AI/ML Bionetworks
