RESUMEN
Macrophages are key cellular contributors to the pathogenesis of COVID-19, the disease caused by the virus SARS-CoV-2. The SARS-CoV-2 entry receptor ACE2 is present only on a subset of macrophages at sites of SARS-CoV-2 infection in humans. Here, we investigated whether SARS-CoV-2 can enter macrophages, replicate, and release new viral progeny; whether macrophages need to sense a replicating virus to drive cytokine release; and, if so, whether ACE2 is involved in these mechanisms. We found that SARS-CoV-2 could enter, but did not replicate within, ACE2-deficient human primary macrophages and did not induce proinflammatory cytokine expression. By contrast, ACE2 overexpression in human THP-1-derived macrophages permitted SARS-CoV-2 entry, processing and replication, and virion release. ACE2-overexpressing THP-1 macrophages sensed active viral replication and triggered proinflammatory, antiviral programs mediated by the kinase TBK-1 that limited prolonged viral replication and release. These findings help elucidate the role of ACE2 and its absence in macrophage responses to SARS-CoV-2 infection.
Asunto(s)
COVID-19 , SARS-CoV-2 , Humanos , SARS-CoV-2/fisiología , Enzima Convertidora de Angiotensina 2/genética , Citocinas , Peptidil-Dipeptidasa A/genética , Peptidil-Dipeptidasa A/metabolismo , Macrófagos/metabolismo , Virión/metabolismoRESUMEN
High-throughput single-cell RNA-seq (scRNA-seq) is a powerful tool for studying gene expression in single cells. Most current scRNA-seq bioinformatics tools focus on analysing overall expression levels, largely ignoring alternative mRNA isoform expression. We present a computational pipeline, Sierra, that readily detects differential transcript usage from data generated by commonly used polyA-captured scRNA-seq technology. We validate Sierra by comparing cardiac scRNA-seq cell types to bulk RNA-seq of matched populations, finding significant overlap in differential transcripts. Sierra detects differential transcript usage across human peripheral blood mononuclear cells and the Tabula Muris, and 3 'UTR shortening in cardiac fibroblasts. Sierra is available at https://github.com/VCCRI/Sierra .