Validation of a new strategy for the identification of SARS-CoV-2 variants by sequencing the spike gene by Sanger

Introduction: The emergence of multiple variants of SARS-CoV-2 during the COVID-19 pandemic is of great world concern. Until now, their analysis has mainly focused on next-generation sequencing. However, this technique is expensive and requires sophisticated equipment, long processing times, and highly qualified technical personnel with experience in bioinformatics. To contribute to the analysis of variants of interest and variants of concern, increase the diagnostic capacity, and process samples to carry out genomic surveillance, we propose a quick and easy methodology to apply, based on Sanger sequencing of 3 gene fragments that code for protein spike. Methods: Fifteen positive samples for SARS-CoV-2 with a cycle threshold below 25 were sequenced by Sanger and next-generation sequencing methodologies. The data obtained were analyzed on the Nextstrain and PANGO Lineages platforms. Results: Both methodologies allowed the identification of the variants of interest reported by the WHO. Two samples were identified as Alpha, 3 Gamma, one Delta, 3 Mu, one Omicron, and 5 strains were close to the initial Wuhan-Hu-1 virus isolate. According to in silico analysis, key mutations can also be detected to identify and classify other variants not evaluated in the study. Conclusion: The different SARS-CoV-2 lineages of interest and concern are classified quickly, agilely, and reliably with the Sanger sequencing methodology. (c) 2022 The Authors. Published by Elsevier Espan similar to a, S.L.U. on behalf of Sociedad Espan similar to ola de Enfermedades Infecciosas y Microbiologi ' a Cli ' nica. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Automated summary

The emergence of multiple variants of SARS-CoV-2 during the COVID-19 pandemic has raised great global concern. In this study, a quick and easy method based on Sanger sequencing of protein spike gene fragments was proposed to analyze and classify the variants of interest and concern. The results demonstrated that this method allows for rapid and reliable classification and identification of different SARS-CoV-2 lineages.