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    The HIV transcriptome under the eye of the MinION

    Team Clarisse Berlioz-Torrent and Stéphane Emiliani

    Dynamic analysis of HIV-1 transcriptome by long-read sequencing

     

    During the infection of T lymphocytes with the human immunodeficiency virus (HIV), more than 50 different viral RNA are generated. A controlled production of these different RNAs is crucial for the efficient replication of the virus. The "host-virus interaction" team, in collaboration with the IBENS Genomics core facility, used the third generation of long-read sequencing (MinION from Oxford Nanopore Technologies) to dynamically analyse the entire HIV transcriptome expressed in primary CD4+ T cells during the early stages of infection. This study was recently published in Retrovirology. 

     

    Alternative splicing (AS) is a cellular process mediated by a large ribonucleoprotein complex, the spliceosome, which can generate from a pre-messenger RNA a range of different mRNA isoforms. It is a means for the majority of cellular genes to extend and regulate their expression.

    During infection, the HIV uses this AS process to generate from a single unspliced pre-messenger RNA more than 50 spliced viral transcripts. These different RNAs are needed to produce both the viral genome that will be incorporated into new viruses and the mRNAs for the translation of all the viral proteins necessary for the production of new viral particles. An imbalance in this process can have dramatic consequences on viral replication. HIV AS is therefore tightly regulated both spatially and temporally during infection. 

    Due to the number and diversity of RNA isoforms generated, the viral transcriptome has proved to be particularly challenging to study. 

    In a work led by Sarah Gallois-Montbrun within the “host-virus interaction” team, and in collaboration with the IBENS Genomic core facility, Nam Nguyen Quang et al. used the new generation of long-read sequencing MinION from Oxford Nanopore Technologies to dynamically analyse the entire viral transcriptome produced during HIV-1 infection of primary CD4+ T cells.  

     

     

    Long-read sequencing of HIV transcriptome expressed in infected primary CD4+ T cells. Primary CD4+ T cells were infected with HIV-1, cell lysates were collected between 12 and 24 h post-infection, RNAs were extracted, reverse transcribed and libraries were prepared. MinION (ONT) sequencing was performed in collaboration with the genomic core facility at IBENS. Read analysis allowed to identify and quantify viral RNA isoform levels during infection.

     

     

     

     

     

    The reads obtained, of several thousand nucleotides, were long enough to cover all possible splice junctions, and to identify over 150 different combinations of exons generated during infection. Fifty-three viral RNA isoforms, including 14 new ones, were further considered for quantitative analysis.  The quantifications of the usage of splice sites and of the expression levels of each transcript enabled building "splice trees", an original quantitative representation of the cascade of splicing events leading to the production of the different viral isoforms. Through this approach, the authors produced for the first time a dynamic map of the regulation of the viral transcriptome generated between 12 and 24 hours of infection. In particular, these data highlighted the importance of non-coding exons in viral RNA transcriptome regulation. 

     

    Altogether, this study demonstrated that long-read sequencing is a convenient and reliable strategy to grasp the dynamic of splicing event modulating the HIV RNA landscape in infected cells. It is a promising tool to gain new insights into the regulation of this highly dynamic step of HIV-1 replication cycle.

     

    References

    Nguyen Quang N, Goudey S, Ségéral E, Mohammad A, Lemoine S, Blugeon C, Versapuech M, Paillart JC, Berlioz-Torrent C, Emiliani S, Gallois-Montbrun S. Dynamic nanopore long-read sequencing analysis of HIV-1 splicing events during the early steps of infection. Retrovirology. 2020 Aug 17;17(1):25. doi: 10.1186/s12977-020-00533-1. PMID: 32807178; PMCID: PMC7433067.

     

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