Evolutionary ecology theory offers avenues to anticipate the future behavior of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pathogen. The repeated emergence of more infectious and possibly more virulent variants of SARS-CoV-2 shows that the virus is adapting under selective pressure.
Although there has been a lot of discussion on how biodiversity-related events facilitate zoonosis, the role of the globally connected human population in driving the rapid evolution of the virus has not been sufficiently acknowledged.
*Important notice: bioRxiv publishes preliminary scientific reports that are not peer-reviewed and, therefore, should not be regarded as conclusive, guide clinical practice/health-related behavior, or treated as established information.
Analyzing the rapid evolution of SARS-CoV-2 by tracking the mutations of the virus worldwide
A team of researchers from Saudi Arabia and Spain recently quantified the rapid evolution of SARS-CoV-2 by tracking the mutations of the virus globally, focusing on the receptor-binding domain (RBD) of the virus’s spike protein, which determines its infectivity.
In this study, the researchers used macroscopic considerations of evolutionary ecology theory to offer insights into SARS-CoV-2’s current and future evolution. They first analyzed the rise of new variants of SARS-CoV-2 and their relationship to infection in humans. They also provided evidence of the rates and ways of selection driving SARS-CoV-2 evolution and, based on this evidence, discussed the expected outcomes and the best defense tactics.
The researchers focused the analysis on mutations at the 194 amino-acid receptor-binding domain (RBD) of SARS-CoV-2 based on raw sequenced genomes from GISAID identifying mutations and Mutation Fingerprints (MF), available through their in-house platform COVID-19 virus Mutation Tracker. They defined each set of SARS-CoV-2 genomes generating the same amino acid sequence in the RBD region of the spike protein as a unique RBD variant. The study is published on the preprint server, bioRxiv*.
Results show three new RBD variants produced every day and doubling of RBD variants every 71.67 days
The study estimated that by March 1, 2021, a total of 384 million people were infected by SARS-CoV-2, producing up to 1021 copies of the organism, with one new RBD variant emerging for every 600,000 infections. This results in about three new effective RBD variants produced every day, which means doubling of RBD variants every 71.67 days and selection of the most infective viral variants that challenge human defenses. This demands a shift to proactive rather than reactive measures, suggest the researchers.
Our analysis provides evidence for extraordinarily rapid evolution and selection of SARS-CoV-2, with the number of unique RBD variants currently doubling every 71.67 days, which has clearly reached a full speed in the Red Queen race, risking outpacing that of human defenses.”
The rapid development of COVID-19 vaccines, thanks to the unprecedented collaboration between scientists worldwide, has been hailed as the beginning of the end of the COVID-19 pandemic. It surely is the beginning of a new phase of continuous development of new and universal vaccines, which calls for sustained global collaboration. Novel and diverse vaccines will be the best tools to prevent the rapid evolution of SARS-CoV-2 from outpacing human defenses in this race to end the COVID-19 pandemic.
Analyzing global genomic data about the COVID-19 pandemic using supercomputers may help gain a better understanding of viral evolutionary processes
The study provides evidence for the extraordinarily rapid evolution of SARS-CoV-2, with the number of unique RBD variants doubling every 71.67 days outpacing human defenses. In silico analyses of the efficacy of currently available vaccines against potential RBD variants are yet to be carried out.
The development of new and more effective vaccines against such variants will help overtake SARS-CoV-2 in this evolutionary race, as the current reactive and catch-up tactics to vaccines are risky.
Artificial Intelligence may further help analyze the immunogenicity of all the nonsynonymous variations across described and predicted SARS-CoV-2 sequences to generate a blueprint for effective vaccine development.”
We also have a massive amount of global genomic data available about the COVID-19 pandemic at a level unprecedented in human pandemic history. Analyzing them using supercomputers will help gain a better understanding of viral evolutionary processes needed to predict potential future evolutionary pathways for the SARS-CoV-2 virus.
*Important notice: bioRxiv publishes preliminary scientific reports that are not peer-reviewed and, therefore, should not be regarded as conclusive, guide clinical practice/health-related behavior, or treated as established information.
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