In the NCBI database, as on June 6, 2020, total number of available complete genome sequences of SARS-CoV2 across the world is 3617. The envelope protein of SARS-CoV2 possesses several non-synonymous mutations over the transmembrane domain and (C)-terminus in 0.414\% of these 3617 genomes. The C-terminus motif DLLV has been changed to DFLV and YLLV in the proteins QJR88103 (Australia: Victoria) and QKI36831 (China: Guangzhou) respectively, which might affect the binding of this motif with the host protein PALS1.
Hyper-transmissibility with decreased disease severity is a typical characteristic of the SARS-CoV-2 Omicron variant. To understand this phenomenon, we used various bioinformatics approaches to analyze randomly selected genome sequences (one each) of the Gamma, Delta, and Omicron variants submitted to NCBI from December 15 to 31, 2021. We report that the pathogenicity of SARS-CoV-2 variants decreases in the order of Wuhan > Gamma > Delta > Omicron; however, the antigenic property follows the order of Omicron > Gamma > Wuhan > Delta. The Omicron spike RBD shows lower pathogenicity but higher antigenicity than other variants. The reported decreased disease severity by the Omicron variant may be due to its decreased pro-inflammatory and IL-6 stimulation and increased IFN-γ and IL-4 induction efficacy. The mutations in the N protein are probably associated with this decreased IL-6 induction and human DDX21-mediated increased IL-4 production for Omicron. Due to the mutations, the stability of S, M, N, and E proteins decreases in the order of Omicron > Gamma > Delta > Wuhan. Although a stronger spike RBD-
h
ACE2 binding of Omicron increases its transmissibility, the lowest stability of its spike protein makes spike RBD-
h
ACE2 interaction weak for systemic infection and for causing severe disease. Finally, the highest instability of the Omicron E protein may also be associated with decreased viral maturation and low viral load, leading to less severe disease and faster recovery. Our findings will contribute to the understanding of the dynamics of SARS-CoV-2 variants and the management of emerging variants. This minimal genome-based method may be used for other similar viruses avoiding robust analysis.
Supplementary Information
The online version contains supplementary material available at 10.1007/s10753-022-01734-w.
Hyper-transmissibility with decreased disease severity are typical characteristics of Omicron variant. To understand this phenomenon, we used various bioinformatics approaches to analyze randomly selected genome sequences (one each) of the Gamma, Delta, and Omicron variants submitted to NCBI from 15 to 31 December 2021. We show that: (i) Pathogenicity of SARS-CoV-2 variants decreases in the order: Wuhan > Gamma > Delta > Omicron; however, the antigenic property follows the order: Omicron > Gamma > Wuhan > Delta. (ii) Omicron Spike RBD has lower pathogenicity but higher antigenicity than that of other variants. (iii) Decreased disease severity by Omicron variant may be due to its decreased pro-inflammatory and IL-6 stimulation and increased IFN-γ and IL-4 induction efficacy. (iv) Mutations in N protein are associated with decreased IL-6 induction and human DDX21-mediated increased IL-4 production in Omicron. (v) Due to mutations, the stability of S, M, N, and E proteins decrease in the order: Omicron > Gamma > Delta > Wuhan. (vi) Stronger Spike-hACE2 binding in Omicron is associated with its increased transmissibility. However, the lowest stability of the Omicron Spike protein makes Spike-hACE2 interaction unstable for systemic infection and for causing severe disease. Finally (vii), the highest instability of Omicron E protein may also be associated with decreased viral maturation and low viral load leading to less severe disease and faster recovery. Our method may be used for other similar viruses, and these findings will contribute to the understanding of the dynamics of SARS-CoV-2 variants and the management of emerging variants.
Essential genes are considered to be the genes required to sustain life of different organisms. These genes encode proteins that maintain central metabolism, DNA replications, translation of genes, and basic cellular structure, and mediate the transport process within and out of the cell. The identification of essential genes is one of the essential problems in computational genomics. In this present study, to discriminate essential genes from other genes from a non-biologists perspective, the purine and pyrimidine distribution over the essential genes of four exemplary species, namely
Homo sapiens
,
Arabidopsis thaliana
,
Drosophila melanogaster
, and
Danio rerio
are thoroughly experimented using some quantitative methods. Moreover, the Indigent classification method has also been deployed for classification on the essential genes of the said species. Based on Shannon entropy, fractal dimension, Hurst exponent, and purine and pyrimidine bases distribution, 10 different clusters have been generated for the essential genes of the four species. Some proximity results are also reported herewith for the clusters of the essential genes.
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