Mutational signature dynamics indicate SARS-CoV-2’s evolutionary capacity is driven by host antiviral molecules

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.

Potential Role of APOBEC3 Family Proteins in SARS-CoV-2 Replication

“…These mutation counts were organized in a data matric of (38,830 by 192) and used as input for analysis using the Non-negative Matrix Factorization (NMF) method. NMF is a matrix decomposition method used routinely to deconstruct mutational signatures in cancer and viral genomes [94][95][96][97]. Here, NMF was used to investigate if deconstruction of all SARS-CoV-2 sequences provides evidence for the existence of an APOBEC mutational signature similar to the known SBS2 and SBS13 signatures [94].…”

APOBEC3-related mutations in the spike protein-encoding region facilitate SARS-CoV-2 evolution

“…Apolipoprotein B mRNA editing catalytic subunit-like proteins (APOBECs), the zinc-dependent deaminase family, have an important impact on viral suppression and evolution [ 11 ]. They edit viral genome by recognizing specific nucleotides, compared to random genetic mutations [ 12 , 13 ]. APOBECs comprise 11 genes, namely APOBEC1 ( A1 ), APOBEC2 ( A2 ), APOBEC3A ( A3A ), APOBEC3B ( A3B ) , APOBEC3C ( A3C) , APOBEC3D ( A3D ), APOBEC3F ( A3F ), APOBEC3G ( A3G ) and APOBEC3H ( A3H ), APOBEC4 ( A4 ) and activation-induced cytidine deaminase ( AICDA ) (reviewed in) [ 14 ].…”