RESUMO
SARS-CoV-2 pandemic resulted in 92 million cases in a span of one year. The study focuses on understanding population specific variations attributing its high rate of infections in specific geographical regions particularly in USA. Rigorous phylogenomic network analysis of complete SARS-CoV-2 genomes (245) inferred five central clades named a (ancestral), b, c, d and e (subtype e1 & e2). The clade d & e2 were found exclusively comprising of USA. Clades were distinguished by 10 co-mutational combinations in Nsp3, ORF8, Nsp13, S, Nsp12, Nsp2 and Nsp6. Our analysis revealed that only 67.46% of SNP mutations were at amino acid level. T1103P mutation in Nsp3 was predicted to increase protein stability in 238 strains except 6 strains which were marked as ancestral type; whereas co-mutation (P409L & Y446C) in Nsp13 were found in 64 genomes from USA highlighting its 100% co-occurrence. Docking highlighted mutation (D614G) caused reduction in binding of Spike proteins with ACE2, but it also showed better interaction with TMPRSS2 receptor contributing to high transmissibility among USA strains. We also found host proteins, MYO5A, MYO5B, MYO5C had maximum interaction with viral proteins (N, S, M). Thus, blocking the internalization pathway by inhibiting MYO5 proteins which could be an effective target for COVID-19 treatment. The functional annotations of the HPI network were found to be closely associated with hypoxia and thrombotic conditions confirming the vulnerability and severity of infection. We also screened CpG islands in Nsp1 & N conferring ability of SARS-CoV-2 to enter and trigger ZAP activity inside host cell. ImportanceIn the current study we presented a global view of mutational pattern observed in SARS-CoV-2 virus transmission. This provided a who-infect-whom geographical model since the early pandemic. This is hitherto the most comprehensive comparative genomics analysis of full-length genomes for co-mutations at different geographical regions specially in USA strains. Compositional structural biology results suggested that mutations have balance of contrary forces effect on pathogenicity suggesting only few mutations to effective at translation level but not all. Novel HPI analysis and CpG predictions elucidates the proof of concept of hypoxia and thrombotic conditions in several patients. Thus, the current study focuses the understanding of population specific variations attributing high rate of SARS-CoV-2 infections in specific geographical regions which may eventually be vital for the most severely affected countries and regions for sharp development of custom-made vindication strategies.
RESUMO
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a positive single-stranded RNA virus that causes a highly contagious Corona Virus Disease (COVID19). Entry of SARS-CoV-2 in human cells depends on binding of the viral spike (S) proteins to cellular receptor Angiotensin-converting enzyme 2 (ACE2) and on S-protein priming by host cell serine protease TMPRSS2. Recently, COVID19 has been declared pandemic by World Health Organization (WHO) yet high differences in disease outcomes across countries have been seen. We provide evidences to explain these population-level differences. One of the key factors of entry of the virus in host cells presumably is because of differential interaction of viral proteins with host cell proteins due to different genetic backgrounds. Based on our findings, we conclude that a higher expression of ACE2 is facilitated by natural variations, acting as Expression quantitative trait loci (eQTLs), with different frequencies in different populations. We suggest that high expression of ACE2 results in homo-dimerization, proving disadvantageous for TMPRSS2 mediated cleavage of ACE2; whereas, the monomeric ACE2 has higher preferential binding with SARS-CoV-2 S-Protein vis-a-vis its dimerized counterpart. Further, eQTLs in TMPRSS2 and natural structural variations in the gene may also result in differential outcomes towards priming of viral S-protein, a critical step for entry of the Virus in host cells. In addition, we suggest that several key host genes, like SLC6A19, ADAM17, RPS6, HNRNPA1, SUMO1, NACA, BTF3 and some other proteases as Cathepsins, might have a critical role. To conclude, understanding population specific differences in these genes may help in developing appropriate management strategies for COVID19 with better therapeutic interventions.
