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Bellevue College Biology Club Presents "Mutational and phylogenetic analysis of SARS CoV-2 strains"

Authors: Ahmed N., Louie A., Jones O., Hamilton J., Song A., Young A., Alvares S.M., Bilge A.;

Bellevue College Biology Club Presents "Mutational and phylogenetic analysis of SARS CoV-2 strains"

Abstract

Contact information for joining the Bellevue College Biology Club can be found below. Abstract Mutations in the genetic sequences of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) have been instrumental in shaping the ongoing pandemic. The emergence of distinct strains highlights the significance of these mutations. In order to understand implications and potential impact on virulence, we investigated prevalent SARS-CoV-2 strains from the GISAID database and used a custom python script to identify the location of mutations and their potential effects on protein amino acid sequences. Our comprehensive analysis revealed mutations accumulated throughout the pandemic, particularly in the spike protein gene (S gene), which exhibited high mutational diversity and reduced conservation. Notably, mutations such as N439K, T478K, and D614G were found to potentially impact viral infectivity, antibody resistance, and binding affinity to the ACE2 receptor. Additionally, the phylogenetic tree analysis indicated that the original strain, NC_045512.2, may not be the original strain, but rather a strain that researchers first discovered, suggesting the existence of predated strains. These findings enhance our understanding of SARS-CoV-2 virology and provide valuable insights into the factors influencing strain prevalence and their potential implications for transmission and disease severity.

Bellevue College Biology Club: biologyclub@bellevuec.onmicrosoft.com, Advisor Contact: stacy.alvares@bellevuecollege.edu

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mutational analysis of SARS CoV-2 strains, phylogenetic analysis, biology club

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This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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