The study of RNA modifications, today known as epitranscriptomics, is of growing
interest. The N6-methyladenosine (m6A) and 5-methylcytosine (m5C) RNA modifications
are abundantly present on mRNA molecules, and impact RNA interactions with other
proteins or molecules, thereby affecting cellular processes, such as RNA splicing,
export, stability, and translation. Recently m6A and m5C marks were found to be
present on human immunodeficiency (HIV) transcripts as well and affect viral replication.
Therefore, the discovery of RNA methylation provides a new layer of regulation of
HIV expression and replication, and thus offers novel array of opportunities to inhibit
replication. However, no study has been performed to date to investigate the impact
of HIV replication on the transcript methylation level in the infected cell. We used
a productive HIV infection model, consisting of the CD4+ SupT1 T cell line infected
with a VSV-G pseudotyped HIVeGFP-based vector, to explore the temporal landscape
of m6A and m5C epitranscriptomic marks upon HIV infection, and to compare it to
mock-treated cells. Cells were collected at 12, 24, and 36 h post-infection for mRNA
extraction and FACS analysis. M6A RNA modifications were investigated by methylated
RNA immunoprecipitation followed by high-throughput sequencing (MeRIP-Seq). M5C
RNA modifications were investigated using a bisulfite conversion approach followed by
high-throughput sequencing (BS-Seq). Our data suggest that HIV infection impacted
the methylation landscape of HIV-infected cells, inducing mostly increased methylation
of cellular transcripts upon infection. Indeed, differential methylation (DM) analysis
identified 59 m6A hypermethylated and only 2 hypomethylated transcripts and 14 m5C
hypermethylated transcripts and 7 hypomethylated ones. All data and analyses are also
freely accessible on an interactive web resource (http://sib-pc17.unil.ch/HIVmain.html).
Furthermore, bothm6A andm5Cmethylations were detected on viral transcripts and viral
particle RNA genomes, as previously described, but additional patterns were identified.
This work used differential epitranscriptomic analysis to identify novel players involved in
HIV life cycle, thereby providing innovative opportunities for HIV regulation.