| Autor: |
Kang Jin, Eric E. Bardes, Alexis Mitelpunkt, Jake Y. Wang, Surbhi Bhatnagar, Soma Sengupta, Daniel Pomeranz Krummel, Marc E. Rothenberg, Bruce J. Aronow |
| Jazyk: |
angličtina |
| Rok vydání: |
2021 |
| Předmět: |
|
| Zdroj: |
iScience, Vol 24, Iss 10, Pp 103115- (2021) |
| Druh dokumentu: |
article |
| ISSN: |
2589-0042 |
| DOI: |
10.1016/j.isci.2021.103115 |
| Popis: |
Summary: Numerous 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. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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