An in silico analysis of early SARS-CoV-2 variant B.1.1.529 (Omicron) genomic sequences and their epidemiological correlates

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Abstract

Background

A newly emerged SARS-CoV-2 variant B.1.1.529 has worried the health policy makers worldwide due to the presence of a large number of mutations in its genomic sequence, especially in the spike protein region. World Health Organization (WHO) has designated it as a global variant of concern (VOC) and has named as ‘Omicron’. A surge in new COVID-19 cases have been reported from certain geographical locations, primarily in South Africa (SA) following the emergence of Omicron.

Materials and methods

We performed an in silico analysis of the complete genomic sequences of Omicron available on GISAID (until 2021-12-10) to predict the functional impact of the mutations present in this variant on virus-host interactions in terms of viral transmissibility, virulence/lethality, and immune escape. The mutations present at the receptor binding domain (RBD) of the variants were assessed using an open analysis pipeline which integrates a yeast-display platform with deep mutational scanning. Further, we performed a correlation analysis of the relative proportion of the genomic sequences of specific SARS-CoV-2 variants (in the period of 01 Oct-10 th Dec, 2021) with the current epidemiological data (new COVID-19 cases and deaths) from SA to understand whether the Omicron has an epidemiological advantage over existing variants.

Results

Compared to the current list of global VOCs/VOIs (as per WHO) Omicron bears more sequence variation, specifically in the spike protein and host receptor-binding motif (RBM). Omicron showed the closest nucleotide and protein sequence homology with Alpha variant for the complete sequence as well as for RBM. The mutations were found primarily condensed in spike region (28-48) of the virus. Further, the mutational analysis showed enrichment for the mutations decreasing ACE2-binding affinity and RBD protein expression, in contrast, increasing the propensity of immune escape. An inverse correlation of Omicron with Delta variant was noted (r=-0.99, p< .001, 95% CI: -0.99 to - 0.97) in the sequences reported from SA post-emergence of the new variant, later showing a decrease. There has been a steep rise in the new COVID-19 cases in parallel with increase in the proportion of Omicron since the first case (74-100%), on the contrary, the incidences of new deaths have not been increased (r=-0.04, p>0.05, 95% CI =-0.52 to 0.58).

Conclusions

Omicron may have greater immune escape ability than the existing VOCs/VOIs. However, there are no clear indications coming out from the predictive mutational analysis that the Omicron may have higher virulence/lethality than other variants, including Delta. The higher ability for immune escape may be a likely reason for the recent surge in Omicron cases in SA.

Highlights

  • Higher immune escape ability than the existing VOCs/VOIs

  • No clear indications of increased affinity for ACE2 binding

  • Driving a new COVID-19 wave in South Africa

  • Outcompeting Delta variant

  • Currently, no clear evidence for increased virulence/lethality

Article activity feed

  1. SciScore for 10.1101/2021.12.18.21267908: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Ethicsnot detected.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Data analysis: The mutational analysis on the genomic sequences was performed and 3D structure of spike with amino acid changes in Omicron was generated using CoVsurver app by GISAID (https://www.gisaid.org/) employing hCoV-19/Wuhan/WIV04/2019 as a reference strain.
    CoVsurver
    suggested: None
    A comparative assessment of the Omicron nucleotide and protein sequences with existing global VOCs/VOIs were made using NCBI Blast tool (https://blast.ncbi.nlm.nih.gov/Blast.cgi?).
    NCBI Blast tool
    suggested: None
    https://blast.ncbi.nlm.nih.gov/Blast.cgi
    suggested: (TBLASTX, RRID:SCR_011823)
    For the analysis of epidemiological data the statistical tests were performed to evaluate inter-group differences between the SARS-CoV-2 Variants with the help of MS Excel 2019 and XLSTAT package.
    XLSTAT
    suggested: (XLSTAT, RRID:SCR_016299)

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).


    Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    Results from TrialIdentifier: No clinical trial numbers were referenced.


    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.


    Results from JetFighter: We did not find any issues relating to colormaps.


    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    Results from scite Reference Check: We found no unreliable references.


    About SciScore

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