alexa Host genes associated with HIV-1 replication in lymphatic tissue.
Bioinformatics & Systems Biology

Bioinformatics & Systems Biology

Journal of Proteomics & Bioinformatics

Author(s): Smith AJ, Li Q, Wietgrefe SW, Schacker TW, Reilly CS,

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Abstract Much effort has been spent recently in identifying host factors required for HIV-1 to effectively replicate in cultured human cells. However, much less is known about the genetic factors in vivo that impact viral replication in lymphatic tissue, the primary anatomical site of virus-host interactions where the bulk of viral replication and pathogenesis occurs. To identify genetic determinants in lymphatic tissue that critically affect HIV-1 replication, we used microarrays to transcriptionally profile and identify host genes expressed in inguinal lymph nodes that were associated determinants of viral load. Strikingly, ∼95\% of the transcripts (558) in this data set (592 transcripts total) were negatively associated with HIV-1 replication. Genes in this subset 1) inhibit cellular activation/proliferation (e.g., TCFL5, SOCS5 and SCOS7, KLF10), 2) promote heterochromatin formation (e.g., HIC2, CREBZF, ZNF148/ZBP-89), 3) increase collagen synthesis (e.g., PLOD2, POSTN, CRTAP), and 4) reduce cellular transcription and translation. Potential anti-HIV-1 restriction factors were also identified (e.g., NR3C1, HNRNPU, PACT). Only ∼5\% of the transcripts (34) were positively associated with HIV-1 replication. Paradoxically, nearly all of these genes function in innate and adaptive immunity, particularly highlighting heightened gene expression in the IFN system. We conclude that this conventional host response cannot contain HIV-1 replication and, in fact, could well contribute to increased replication through immune activation. More importantly, genes that have a negative association with virus replication point to target cell availability and potentially new viral restriction factors as principal determinants of viral load.
This article was published in J Immunol and referenced in Journal of Proteomics & Bioinformatics

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