Mutational dynamics across VOCs in International travellers and Community transmission underscores importance of Spike-ACE2 interaction

Abstract

Background: Emergence of SARS-CoV-2 VOCs at different time points through COVID-19 pandemic raised concern for increased transmissibility, infectivity and vaccination breakthroughs.

Methods: 1567 international travellers plus community transmission COVID-19 cases were analysed for mutational profile of VOCS, that led to notable waves in India, namely Alpha, Delta, and Omicron. Spike mutations in Linkage Disequilibrium were investigated for potential impact on structural and functional changes of Spike-ACE2.

Results: ORF1ab and spike harboured diverse mutational signatures for each lineage. B.1.617.2 and AY. * demonstrated comparable profile, yet non-clade defining mutations were majorly unique between international vs community samples. Contrarily, Omicron lineages showed substantial overlap in non-clade defining mutations, signifying early phase of transmission and evolution within Indian community. Mutations in LD for Alpha [N501Y, A570D, D1118H, S982A], Delta [P681R, L452R, EFR:156-158 G, D950N, G142D] and Omicron [P681H, D796Y, N764K, N969K, N501Y, S375F] resulted in decreased binding affinity of Spike-ACE2 for Alpha and BA.1 whereas Delta, Omicron and BA.2 demonstrated strong binding.

Conclusion: Genomic surveillance tracked spread of VOCs in international travellers' vs community transmission. Behavioural transmission patterns of variants, based on selective advantage incurred by spike mutations, led us to predict sudden takeover of Delta over Alpha and BA.2 over BA.1 in India.

Keywords: Genomic surveillance; Mutation analysis; SARS-CoV-2; Structural analysis; Variants of concern.

Graphical abstract

Fig. 1

Demographics and phylogenetic evolution of the prominent SARS-CoV-2 variants in India. (a) The matrix plot demonstrates a comparative frequency distribution of SARS-CoV-2 variants between Dec 2020-Jan 2022 in the study cohort from our Lab and pan-India based on the genomic surveillance data from GISAID. (b) The age demographics of SARS-CoV-2 positive patients across India, Dec 2020-Jan 2022. (c) Phylogenetic distribution of various SARS-CoV-2 positive patients, Dec 2020-Jan 2022 in our study cohort.

Fig. 2

Mutational landscape of SARS-CoV-2 dominant variants across different time points. (a) A comparative pan view of the entire SARS-CoV-2 genome showing regions with high and low concentration of mutations across different VOCs. (b) Circular bar plot representing SARS-CoV-2 genes arranged in descending order of the mutation rates across Alpha, Delta and Omicron VOCs. (c) Lollipop plot of B.1.1.7 (Alpha) variant mutations from international travellers. (d) Lollipop plot of B.1.617.2 (Delta) variant mutations from community cases. (e) Lollipop plot of AY. * (Delta-sub lineages) mutations from community cases and international travellers. (f) Lollipop plot of B.1.1.529 (Omicron) variant mutations from community cases and international travellers. (g) Lollipop plot of BA.1 (Omicron) variant mutations from community cases and international travellers. (h) Lollipop plot of BA.2 (Omicron) variant mutations from community cases and international travellers. The nodes of clade-defining mutations are coloured in red for (c-h), pink nodes belong to mutations which became clade-defining in successive lineages and black nodes are for non-clade defining mutations.

Fig. 3

Linkage Disequilibrium analysis of Spike mutations in different variants over time in India. The LD plot represents spike mutations that are in strong LD with each other, with r2 > =0.8 and D′ > = 0.9. (a) In pre-omicron variants, (b) in community samples, and (c) in the international travellers’ groups. The colour of the plot represents r² values as percentage.

Fig. 4

Docking representation of the Wild type and different variant mutation complexes. Illustrates the binding interfaces with key hydrogen interactions (a) wild-type complex, (b) Alpha variant complex, (c) Delta variant complex, and (d) Omicron variant complex.

Fig. 5

Docking model with binding interfaces and key hydrogen interactions from PDBsum. This includes for, (a) BA.1, and (b) BA.2 sub-lineages with ACE2 receptor. (c) 2D interaction representation of salt-bridges, hydrogen bonds and non-bonded interactions in BA.1 and BA.2 with ACE2 receptor.