SARS-CoV-2 genomes from Saudi Arabia implicate nucleocapsid mutations in host response and increased viral load.
Tobias MourierMuhammad ShuaibSharif HalaSara MfarrejFadwa AlofiRaeece NaeemAfrah AlsomaliDavid JorgensenAmit Kumar SubudhiFathia Ben RachedQingtian GuanRahul P SalunkeAmanda OoiLuke EsauOlga DouvropoulouRaushan NugmanovaSadhasivam PerumalHuoming ZhangIssaac RajanAwad Al-OmariSamer SalihAbbas ShamsanAbbas Al MutairJumana TahaAbdulaziz AlahmadiNashwa KhotaniAbdelrahman AlhamssAhmad Bakur MahmoudKhaled AlquthamiAbdullah DageegAsim KhogeerAnwar M HashemPaula MoragaErik M VolzNaif AlmontashiriArnab PainPublished in: Nature communications (2022)
Monitoring SARS-CoV-2 spread and evolution through genome sequencing is essential in handling the COVID-19 pandemic. Here, we sequenced 892 SARS-CoV-2 genomes collected from patients in Saudi Arabia from March to August 2020. We show that two consecutive mutations (R203K/G204R) in the nucleocapsid (N) protein are associated with higher viral loads in COVID-19 patients. Our comparative biochemical analysis reveals that the mutant N protein displays enhanced viral RNA binding and differential interaction with key host proteins. We found increased interaction of GSK3A kinase simultaneously with hyper-phosphorylation of the adjacent serine site (S206) in the mutant N protein. Furthermore, the host cell transcriptome analysis suggests that the mutant N protein produces dysregulated interferon response genes. Here, we provide crucial information in linking the R203K/G204R mutations in the N protein to modulations of host-virus interactions and underline the potential of the nucleocapsid protein as a drug target during infection.
Keyphrases
- sars cov
- respiratory syndrome coronavirus
- protein protein
- amino acid
- binding protein
- saudi arabia
- stem cells
- single cell
- ejection fraction
- newly diagnosed
- emergency department
- protein kinase
- risk assessment
- dendritic cells
- transcription factor
- prognostic factors
- dna binding
- electronic health record
- human health
- genome wide identification