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/). 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) 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.
Keywords: COVID-19; SARS-CoV-2; antiviral host defense; autoimmune disorder; bronchoalveolar lavage; host-pathogen cell atlas; inflammatory thrombosis; interactive datamining; platelets; single-cell RNA-seq; systems biology.