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1.
Viruses ; 14(3)2022 03 15.
Article in English | MEDLINE | ID: covidwho-1742732

ABSTRACT

The novel coronavirus SARS-CoV-2 is responsible for the ongoing COVID-19 pandemic and has caused a major health and economic burden worldwide. Understanding how SARS-CoV-2 viral proteins behave in host cells can reveal underlying mechanisms of pathogenesis and assist in development of antiviral therapies. Here, the cellular impact of expressing SARS-CoV-2 viral proteins was studied by global proteomic analysis, and proximity biotinylation (BioID) was used to map the SARS-CoV-2 virus-host interactome in human lung cancer-derived cells. Functional enrichment analyses revealed previously reported and unreported cellular pathways that are associated with SARS-CoV-2 proteins. We have established a website to host the proteomic data to allow for public access and continued analysis of host-viral protein associations and whole-cell proteomes of cells expressing the viral-BioID fusion proteins. Furthermore, we identified 66 high-confidence interactions by comparing this study with previous reports, providing a strong foundation for future follow-up studies. Finally, we cross-referenced candidate interactors with the CLUE drug library to identify potential therapeutics for drug-repurposing efforts. Collectively, these studies provide a valuable resource to uncover novel SARS-CoV-2 biology and inform development of antivirals.


Subject(s)
COVID-19 , SARS-CoV-2 , Biotinylation , Humans , Pandemics , Proteomics
2.
Mol Cell ; 81(12): 2656-2668.e8, 2021 06 17.
Article in English | MEDLINE | ID: covidwho-1179919

ABSTRACT

A deficient interferon (IFN) response to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has been implicated as a determinant of severe coronavirus disease 2019 (COVID-19). To identify the molecular effectors that govern IFN control of SARS-CoV-2 infection, we conducted a large-scale gain-of-function analysis that evaluated the impact of human IFN-stimulated genes (ISGs) on viral replication. A limited subset of ISGs were found to control viral infection, including endosomal factors inhibiting viral entry, RNA binding proteins suppressing viral RNA synthesis, and a highly enriched cluster of endoplasmic reticulum (ER)/Golgi-resident ISGs inhibiting viral assembly/egress. These included broad-acting antiviral ISGs and eight ISGs that specifically inhibited SARS-CoV-2 and SARS-CoV-1 replication. Among the broad-acting ISGs was BST2/tetherin, which impeded viral release and is antagonized by SARS-CoV-2 Orf7a protein. Overall, these data illuminate a set of ISGs that underlie innate immune control of SARS-CoV-2/SARS-CoV-1 infection, which will facilitate the understanding of host determinants that impact disease severity and offer potential therapeutic strategies for COVID-19.


Subject(s)
Antigens, CD/genetics , Host-Pathogen Interactions/genetics , Interferon Regulatory Factors/genetics , Interferon Type I/genetics , SARS-CoV-2/genetics , Viral Proteins/genetics , Animals , Antigens, CD/chemistry , Antigens, CD/immunology , Binding Sites , Cell Line, Tumor , Chlorocebus aethiops , Endoplasmic Reticulum/genetics , Endoplasmic Reticulum/immunology , Endoplasmic Reticulum/virology , GPI-Linked Proteins/chemistry , GPI-Linked Proteins/genetics , GPI-Linked Proteins/immunology , Gene Expression Regulation , Golgi Apparatus/genetics , Golgi Apparatus/immunology , Golgi Apparatus/virology , HEK293 Cells , Host-Pathogen Interactions/immunology , Humans , Immunity, Innate , Interferon Regulatory Factors/classification , Interferon Regulatory Factors/immunology , Interferon Type I/immunology , Molecular Docking Simulation , Protein Binding , Protein Conformation, alpha-Helical , Protein Conformation, beta-Strand , Protein Interaction Domains and Motifs , SARS-CoV-2/immunology , Signal Transduction , Vero Cells , Viral Proteins/chemistry , Viral Proteins/immunology , Virus Internalization , Virus Release/genetics , Virus Release/immunology , Virus Replication/genetics , Virus Replication/immunology
3.
Genome Biol ; 22(1): 21, 2021 01 07.
Article in English | MEDLINE | ID: covidwho-1015895

ABSTRACT

In any 'omics study, the scale of analysis can dramatically affect the outcome. For instance, when clustering single-cell transcriptomes, is the analysis tuned to discover broad or specific cell types? Likewise, protein communities revealed from protein networks can vary widely in sizes depending on the method. Here, we use the concept of persistent homology, drawn from mathematical topology, to identify robust structures in data at all scales simultaneously. Application to mouse single-cell transcriptomes significantly expands the catalog of identified cell types, while analysis of SARS-COV-2 protein interactions suggests hijacking of WNT. The method, HiDeF, is available via Python and Cytoscape.


Subject(s)
Computational Biology/methods , SARS-CoV-2/metabolism , Algorithms , Animals , Humans , Mice , Viral Proteins/metabolism
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