SARS-CoV-2 genome underwent mutations since it started circulating within the human population. The aim of this study was to understand the fluctuation of the spike clusters concomitant to the population immunity either due to natural infection and/or vaccination in a state of Brazil that had both high rate of natural infection and vaccination coverage. A total of 1725 SARS-CoV-2 sequences from the state of Rio Grande do Norte, Brazil, were retrieved from GISAID and subjected to cluster analysis. Immunoinformatics were used to predict T- and B-cell epitopes, followed by simulation to estimate either pro- or anti-inflammatory responses and to correlate with circulating variants. From March 2020 to June 2022, the state of Rio Grande do Norte reported 579,931 COVID-19 cases with a 1.4% fatality rate across the three major waves: May-Sept 2020, Feb-Aug 2021, and Jan-Mar 2022. Cluster 0 variants (wild type strain, Zeta) were prevalent in the first wave and Delta (AY.*), which circulated in Brazil in the latter half of 2021, featuring fewer unique epitopes. Cluster 1 (Gamma (P.1 + P.1.*)) dominated the first half of 2021. Late 2021 had two new clusters, Cluster 2 (Omicron, (B.1.1.529 + BA.*)), and Cluster 3 (BA.*) with the most unique epitopes, in addition to Cluster 4 (Delta sub lineages) which emerged in the second half of 2021 with fewer unique epitopes. Cluster 1 epitopes showed a high pro-inflammatory propensity, while others exhibited a balanced cytokine induction. The clustering method effectively identified Spike groups that may contribute to immune evasion and clinical presentation, and explain in part the clinical outcome.
Keywords: COVID-19; Cytokine induction; Epitope prediction; Immunoinformatics; SARS-CoV-2 variants; Spike glycoprotein.
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