Abstract
ABSTRACTSARS-CoV-2 genome underwent mutations since it started circulating intensively within the human populations. The aim of this study was to understand the fluctuation of the spike clusters concomitant to high rate of population immunity either due to natural infection and/or vaccination in a state of Brazil that had high rate of infection and vaccination coverage. A total of 1715 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 correlate with circulating variants. From March 2020 to June 2022, Rio Grande do Norte reported 579,931 COVID-19 cases with a 1.4% fatality rate across 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 in the latter half of 2021, featuring fewer unique epitopes. Cluster 1 (Gamma [P1]) dominated the first half of 2021. Late 2021 had Clusters 2 (Omicron) and 3 (Omicron sublineages) with the most unique epitopes, while Cluster 4 (Delta sublineages) 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.IMPORTANCEIdentification of epitopes of emerging or endemic pathogens is of importance to estimate population responses and predict clinical outcomes and contribute to vaccine improvement. In the case of SARS-CoV-2, the virus within 6 months of circulation transitioned from the wild-type to novel variants leading to distinct clinical outcomes. Immunoinformatics analysis of viral epitopes of isolates from the Brazilian state of Rio Grande do Norte was performed using a clustering method. This analysis aimed to clarify how the introduction of novel variants in a population characterized by high infection and/or vaccination rates resulted in immune evasion and distinct clinical disease. Our analysis showed that the epitope profiles of each variant explained the respective potential for cytokine production, including the variants that were more likely to cause cytokine storms. Finally, it serves as a mean to explain the multi-wave patterns observed during SARS-CoV-2 pandemics.
Publisher
Cold Spring Harbor Laboratory