Santiago Vilar1, Daniel G Isom1,2,3. 1. Department of Molecular and Cellular Pharmacology, University of Miami Miller School of Medicine, Miami, FL 33136, USA. 2. Sylvester Comprehensive Cancer Center, University of Miami, Miami, FL 33136, USA. 3. Institute for Data Science and Computing, University of Miami, Coral Gables, FL 33146, USA.
Abstract
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a worldwide crisis with profound effects on both public health and the economy. In order to combat the COVID-19 pandemic, research groups have shared viral genome sequence data through the Global Initiative on Sharing All Influenza Data (GISAID). Over the past year, ≈290,000 full SARS-CoV-2 proteome sequences have been deposited in the GISAID. Here, we used these sequences to assess the rate of nonsynonymous mutants over the entire viral proteome. Our analysis shows that SARS-CoV-2 proteins are mutating at substantially different rates, with most of the viral proteins exhibiting little mutational variability. As anticipated, our calculations capture previously reported mutations that arose in the first months of the pandemic, such as D614G (Spike), P323L (NSP12), and R203K/G204R (Nucleocapsid), but they also identify more recent mutations, such as A222V and L18F (Spike) and A220V (Nucleocapsid), among others. Our comprehensive temporal and geographical analyses show two distinct periods with different proteome mutation rates: December 2019 to July 2020 and August to December 2020. Notably, some mutation rates differ by geography, primarily during the latter half of 2020 in Europe. Furthermore, our structure-based molecular analysis provides an exhaustive assessment of SARS-CoV-2 mutation rates in the context of the current set of 3D structures available for SARS-CoV-2 proteins. This emerging sequence-to-structure insight is beginning to illuminate the site-specific mutational (in)tolerance of SARS-CoV-2 proteins as the virus continues to spread around the globe.
Severe acute respiratory syndrome coronavirus 2 (n class="Species">SARS-CoV-2) has caused a worldwide crisis with profound effects on both public health and the economy. In order to combat the COVID-19 pandemic, research groups have shared viral genome sequence data through the Global Initiative on Sharing All Influenza Data (GISAID). Over the past year, ≈290,000 full SARS-CoV-2 proteome sequences have been deposited in the GISAID. Here, we used these sequences to assess the rate of nonsynonymous mutants over the entire viral proteome. Our analysis shows that SARS-CoV-2 proteins are mutating at substantially different rates, with most of the viral proteins exhibiting little mutational variability. As anticipated, our calculations capture previously reported mutations that arose in the first months of the pandemic, such asD614G (Spike), P323L (NSP12), and R203K/G204R (Nucleocapsid), but they also identify more recent mutations, such asA222V and L18F (Spike) and A220V (Nucleocapsid), among others. Our comprehensive temporal and geographical analyses show two distinct periods with different proteome mutation rates: December 2019 to July 2020 and August to December 2020. Notably, some mutation rates differ by geography, primarily during the latter half of 2020 in Europe. Furthermore, our structure-based molecular analysis provides an exhaustive assessment of SARS-CoV-2 mutation rates in the context of the current set of 3D structures available for SARS-CoV-2 proteins. This emerging sequence-to-structure insight is beginning to illuminate the site-specific mutational (in)tolerance of SARS-CoV-2 proteins as the virus continues to spread around the globe.
Entities:
Keywords:
3D proteins; COVID-19; SARS-CoV-2; mutations; proteome; sequence
Authors: Sindy Burgold-Voigt; Elke Müller; David Zopf; Stefan Monecke; Sascha D Braun; Katrin Frankenfeld; Michael Kiehntopf; Sebastian Weis; Thomas Schumacher; Mathias W Pletz; Ralf Ehricht Journal: Sci Rep Date: 2022-05-16 Impact factor: 4.996