SARS-CoV-2 NSP3, NSP4 and NSP6 mutations and Epistasis during the pandemic in the world: Evolutionary Trends and Natural Selections in Six Continents

Abstract

Background: The Coronavirus 2019 (COVID-19) was named by the World Health Organization (WHO) due to its rapid transmittable potential and high mortality rate. Based on the critical role of None Structural Proteins (NSP), NSP3, NSP4, and NSP6 in COVID-19, this study attempts to investigate the superior natural selection mutations and Epistasis among these none structural proteins. Methods: Approximately 6.5 million SARS-CoV-2 protein sequences of each NSP3, NSP4, and NSP6 nonstructural protein were analyzed from January 2020 to January 2022. Python programming language was utilized to preprocess and apply inclusion criteria on the FASTA file to prepare a list of suitable samples. NSP3, NSP4, and NSP6 were aligned to the reference sequence to compare and identify mutation patterns categorized based on frequency, geographical zone distribution, and date. To discover epistasis situations, linear regression between mutation frequency and date among candidate genes was performed to determine correlations. Results: The rate of NSP3, NSP4, and NSP6 mutations in divided geographical areas was different. Based on continental studies, P1228L (54.48%), P1469S (54.41%), and A488S (53.86%) mutations in NSP3, T492I (54.84%), and V167L (52.81%) in NSP4 and T77A (69.85%) mutation in NSP6 increased over time, especially in recent months. For NSP3, Europe had the highest P1228L, P1469S, and A488S mutations. For NSP4, Oceania had the highest T492I and V167L mutations, and for NSP6, Europe had the highest T77A mutation. Hot spot regions for NSP3, NSP4, and NSP6 were 1358 to 1552 AA, 150 to 200 AA, and 58 to 87 AA, respectively. Our results showed a significant correlation and co-occurrence between NSP3, NSP4, and NSP6 mutations. Conclusion: We conclude that the effect of mutations on virus stability and replication can be predicted by examining the amino acid changes of P1228L, P1469S, A488S, T492I, V167L and T77A mutations. Also, these mutations can possibly be effective on the function of proteins and their targets in the host cell. Keywords: NSP4, NSP3, NSP6, Epistasis, SARS-CoV-2, Epidemiology

Analysis of Whole-Genome Sequencing of SARS-CoV-2 Reveals Recurrent Mutations among Iranian Patients

“…NSP3 with NSP4 rearrange host-derived membranes and plays a role in the replication of SARS-CoV [41]. A total of 32.8% of NSP4 was conserved and presented 40 mutations, including T492I (6%), L264F (1.3%), and T327I (1.2%) that were reported in previous studies [35, 42, 43].…”

“…The transcriptome analysis of Sun et al demonstrated that the L37F mutant failed to trigger pyroptosis and the downstream inflammasome pathway [51]. In our recent study, we showed that the T77A mutation is one of the top mutations globally, with a frequency of 69.8% [43].…”

Global landscape of SARS-CoV-2 mutations and conserved regions

“…However, The PLpro central catalytic residues were highly conserved [ 82 ]. Based on fooladinezhad, results, in North America NSP3 data, 41.47% of aa showed more than four mutations in their sequence [ 22 ]. The region corresponding to the C-terminal domain of SARS-CoV NSP3 was found to be significantly less mutated likely due to its vital role in inducing the formation of [ 2 ] double-membrane vesicles [ 6 ].…”

Rapid assembly of SARS-CoV-2 genomes reveals attenuation of the Omicron BA.1 variant through NSP6

“…Several studies have suggested that Omicron could have emerged due to epistatic interactions that may allow for the emergence of mutations not seen in other variants or that are very rare [57][58][59] . The low intra-host evolution for SARS-CoV-2 and relatively limited transmission bottleneck 60,61 suggest that Omicron may have evolved in chronically infected patients where the virus can cross through fitness valleys that may not be possible in an acute infection 57 .…”