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Mutational signature dynamics indicate SARS-CoV-2's evolutionary capacity is driven by host antiviral molecules.
Lamb, Kieran D; Luka, Martha M; Saathoff, Megan; Orton, Richard J; Phan, My V T; Cotten, Matthew; Yuan, Ke; Robertson, David L.
Afiliación
  • Lamb KD; Medical Research Council - University of Glasgow Centre for Virus Research, School of Infection and Immunity, Glasgow, Scotland, United Kingdom.
  • Luka MM; School of Computing Science, University of Glasgow, Glasgow, Scotland, United Kingdom.
  • Saathoff M; Medical Research Council - University of Glasgow Centre for Virus Research, School of Infection and Immunity, Glasgow, Scotland, United Kingdom.
  • Orton RJ; School of Computing Science, University of Glasgow, Glasgow, Scotland, United Kingdom.
  • Phan MVT; Medical Research Council - University of Glasgow Centre for Virus Research, School of Infection and Immunity, Glasgow, Scotland, United Kingdom.
  • Cotten M; Medical Research Council - University of Glasgow Centre for Virus Research, School of Infection and Immunity, Glasgow, Scotland, United Kingdom.
  • Yuan K; Medical Research Council/Uganda Virus Research Institute and London School of Hygiene & Tropical Medicine Uganda Research Unit, Entebbe, Uganda.
  • Robertson DL; College of Health Solutions, Arizona State University, Phoenix, Arizona, United States of America.
PLoS Comput Biol ; 20(1): e1011795, 2024 Jan.
Article en En | MEDLINE | ID: mdl-38271457
ABSTRACT
The COVID-19 pandemic has been characterised by sequential variant-specific waves shaped by viral, individual human and population factors. SARS-CoV-2 variants are defined by their unique combinations of mutations and there has been a clear adaptation to more efficient human infection since the emergence of this new human coronavirus in late 2019. Here, we use machine learning models to identify shared signatures, i.e., common underlying mutational processes and link these to the subset of mutations that define the variants of concern (VOCs). First, we examined the global SARS-CoV-2 genomes and associated metadata to determine how viral properties and public health measures have influenced the magnitude of waves, as measured by the number of infection cases, in different geographic locations using regression models. This analysis showed that, as expected, both public health measures and virus properties were associated with the waves of regional SARS-CoV-2 reported infection numbers and this impact varies geographically. We attribute this to intrinsic differences such as vaccine coverage, testing and sequencing capacity and the effectiveness of government stringency. To assess underlying evolutionary change, we used non-negative matrix factorisation and observed three distinct mutational signatures, unique in their substitution patterns and exposures from the SARS-CoV-2 genomes. Signatures 1, 2 and 3 were biased to C→T, T→C/A→G and G→T point mutations. We hypothesise assignments of these mutational signatures to the host antiviral molecules APOBEC, ADAR and ROS respectively. We observe a shift amidst the pandemic in relative mutational signature activity from predominantly Signature 1 changes to an increasingly high proportion of changes consistent with Signature 2. This could represent changes in how the virus and the host immune response interact and indicates how SARS-CoV-2 may continue to generate variation in the future. Linkage of the detected mutational signatures to the VOC-defining amino acids substitutions indicates the majority of SARS-CoV-2's evolutionary capacity is likely to be associated with the action of host antiviral molecules rather than virus replication errors.
Asunto(s)

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: SARS-CoV-2 / COVID-19 Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: PLoS Comput Biol Asunto de la revista: BIOLOGIA / INFORMATICA MEDICA Año: 2024 Tipo del documento: Article País de afiliación: Reino Unido

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: SARS-CoV-2 / COVID-19 Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: PLoS Comput Biol Asunto de la revista: BIOLOGIA / INFORMATICA MEDICA Año: 2024 Tipo del documento: Article País de afiliación: Reino Unido