  The human genome encodes a family of editing enzymes known as APOBEC3
(apolipoprotein B mRNA editing enzyme, catalytic polypeptide-like 3). Several
family members, such as APO-BEC3G, APOBEC3F, and APOBEC3H haplotype II, exhibit
activity against viruses such as HIV. These enzymes induce C-to-U mutations in
the negative strand of viral genomes, resulting in multiple G-to-A changes,
commonly referred to as 'hypermutation.' Mutations catalyzed by these enzymes
are sequence context-dependent in the HIV genome; for instance, APOBEC3G
preferen-tially mutates G within GG, TGG, and TGGG contexts, while other
members mutate G within GA, TGA, and TGAA contexts. However, the same sequence
context has not been explored in relation to these enzymes and HBV. In this
study, our objective is to identify the mutational footprint of APOBEC3 enzymes
in the HBV genome. To achieve this, we employ a multivariable data analytics
technique to investigate motif preferences and potential sequence hierarchies
of mutation by APOBEC3 enzymes using full genome HBV sequences from a diverse
range of naturally infected patients. This approach allows us to distinguish
between normal and hypermutated sequences based on the representation of mono-
to tetra-nucleotide motifs. Additionally, we aim to identify motifs associated
with hypermutation induced by different APOBEC3 enzymes in HBV genomes. Our
analyses reveal that either APOBEC3 enzymes are not active against HBV, or the
induction of G-to-A mutations by these enzymes is not sequence
context-dependent in the HBV genome.
