HIV modifies the m6A and m5C epitranscriptomic landscape of the host cell

Abstract

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 compare it to mock-treated cells. Cells were collected at 12, 24 and 36h 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, both m6A and m5C methylations 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.