iScienceMolecular BiologyPeer-reviewed journal article
SARS-CoV-2 Nucleocapsid protein attenuates stress granule formation and alters gene expression via direct interaction with host mRNAs
Syed Nabeel‐ShahiD, Hyunmin LeeiD, Nujhat Ahmed, Giovanni L. BurkeiD, Shaghayegh Farhangmehr, Kanwal Ashraf, Shuye PuiD, Ulrich BraunschweigiD, Guoqing Zhong, Hong WeiiD, Hua Tang, Jianyi YangiD, Edyta Marcon, Benjamin J. BlencoweiD, Zhaolei ZhangiD, Jack F. GreenblattiD
Abstract
The COVID-19 pandemic has caused over one million deaths thus far. There is an urgent need for the development of specific viral therapeutics and a vaccine. SARS-CoV-2 nucleocapsid (N) protein is highly expressed upon infection and is essential for viral replication, making it a promising target for both antiviral drug and vaccine development. Here, starting from a functional proteomics workflow, we initially catalogued the protein-protein interactions of 21 SARS-CoV-2 proteins in HEK293 cells, finding that the stress granule resident proteins G3BP1 and G3BP2 copurify with N with high specificity. We demonstrate that N protein expression in human cells sequesters G3BP1 and G3BP2 through its physical interaction with these proteins, attenuating stress granule (SG) formation. The ectopic expression of G3BP1 in N-expressing cells was sufficient to reverse this phenotype. Since N is an RNA-binding protein, we performed iCLIP-sequencing experiments in cells, with or without exposure to oxidative stress, to identify the host RNAs targeted by N. Our results indicate that SARS-CoV-2 N protein binds directly to thousands of mRNAs under both conditions. Like the G3BPs stress granule proteins, N was found to predominantly bind its target mRNAs in their 3UTRs. RNA sequencing experiments indicated that expression of N results in wide-spread gene expression changes in both unstressed and oxidatively stressed cells. We suggest that N regulates host gene expression by both attenuating stress granules and binding directly to target mRNAs.
- organism: human
- assay: bulk RNA-seq
- research focus: differential expression
- approach: statistical model
- Citations
- 139
- FWCI
- 8.01
- Field percentile
- top 2%
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