Genomic and immunoinformatic characterization of severe acute respiratory syndrome Coronavirus 2 variants in North-Rift Kenya and their overlap with endemic Human Coronaviruses

Abstract

Background: Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), the virus responsible for COVID-19, continuously mutates, posing new challenges in pandemic management. It is necessary to study these mutations across all geographical regions, including North Rift Kenya, as they are influenced by environmental and host factors among other factors. Such mutations can undermine vaccine efficacy and diagnostic accuracy by altering epitopes. Therefore, identifying conserved epitopes is crucial for developing long-term immunity strategies. Additionally, understanding cross-immunity with less harmful coronaviruses could help use endemic strains in combating the pandemic. Objectives: To investigate the genetic diversity and immunogenicity of SARS-CoV-2 and their overlap with endemic human coronaviruses in North Rift Kenya Methods: A cross-sectional study was conducted to identify the various SARS-CoV-2 mutations circulating in North Rift, Kenya. Purposive sampling method was used to select 44 samples from COVID-19 patients tested at Moi Teaching and Referral Hospital. Samples these patients, which had a cycle threshold (Ct) value of <30 as determined by Polymerase Chain Reaction (PCR), were sequenced using the Illumina MiSeq platform. Bioinformatic tools were employed to process sequences, identify clades and annotate mutations in the sequences. Basic Local Alignment Search Tool (BLAST) was used to identify conserved epitopes by aligning the annotated proteins with epitopes from the initial Wuhan strain deposited in the Immune Epitope Database (IEDB). The study also examined the immune cross-reactivity of SARS-CoV-2 with endemic coronaviruses by aligning its annotated proteins with epitopes from hCoV-OC43, hCoV-HKU1, hCoV-NL63, and hCoV-229E, also found in the IEDB. Results: Out of the analyzed samples, 2 (5%) samples were Delta of clade AY.46 and 42 samples were Omicron which represents clades BA.1 (2%), BA.1.1(86%), BA.1.1.1(5%), and BA.1.14(2%). There were 65 overlapping mutations of which 38 of them occurred in 88% of the patients, 2 occurred in 63% of the patients 18 in 38% of the patients and 7 mutations in 13% of the patients. Two new mutations (S:R214R and NSP12:A555A) were discovered in the region. Other notable mutations included S:D614G; S:D796Y; S:E484A; and S:N501Y. A total of 5154 (358 T-Cell MHC Class1; 661 T-Cell MHC Class2; and 4135 B-Cell) conserved epitopes were described from a pool of 12285 Wuhan genome epitopes. Various endemic coronaviruses showed cross-reactivity with SARS-CoV-2: hCoV-OC43 having 11 cross-reacting epitopes; hCoV-HKU1 had 13; hCoV-NL63 had 1; and hCoV-229E had 3. Collectively, these cross-reacting epitopes had similarities with 7 immunodominant epitopes. Conclusion: The study identified Delta and Omicron variants, with Omicron being predominant. Among the 65 mutations, most notable ones included S:D614G; S:D796Y; S:E484A; and S:N501Y, with two new mutations, S:R214R and NSP12: A555A. Conserved epitopes from the Wuhan genome were described, and cross-reactivity with endemic coronaviruses was observed, identifying 28 cross-reacting epitopes that shared similarities with 7 immunodominant epitopes. Recommendations: The study recommend continuous monitoring of new SARS-CoV-2 mutations and investigation of the benefits of endemic coronaviruses for insight cross-immunity. An in-depth analysis of endemic coronaviruses is also recommend and its data documented for future researches. Further investigations should focus on mechanisms of cross-reactivity, the diagnostic and therapeutic potential of specific epitopes, and immune responses to coronaviruses to enhance outbreak management.