Transcriptomics,Genomics

Dataset Information

128

Single-Cell RNA-Seq Reveals Transcriptional Heterogeneity in Latent and Reactivated HIV-infected Cells


ABSTRACT: Despite effective treatment, HIV can persist in latent reservoirs, which represent a major obstacle towards HIV eradication. Targeting and reactivating latent cells is challenging due to the heterogeneous nature of HIV infected cells. Here, we used a primary model of HIV latency and single-cell RNA sequencing to characterize transcriptional heterogeneity during HIV latency and reactivation. Our analysis identified transcriptional programs leading to successful reactivation of HIV expression. We further validated our results using primary CD4+ T cells isolated from HIV+ individuals. Overall design: Human primary CD4+ T-cells were infected, cultured, and maintained in a resting, latent phenotype in order to generate a primary model of HIV latency. Latently infected cells were either left untreated, or exposed to SAHA or TCR stimulation, followed by single-cell isolation and single-cell RNA-seq (scRNA-Seq) analysis. Bulk RNA-Seq experiments were also performed as control. To validate the observed cellular heterogeneity in the primary model of HIV latency, we used primary CD4+ T cells isolated from HIV+ individuals. As for the primary HIV latency model, resting cells from HIV+ individuals were either not treated or TCR-treated before single cell isolation and single-cell RNA-Seq.

INSTRUMENT(S): Illumina HiSeq 2500 (Homo sapiens)

SUBMITTER: Monica Golumbeanu  

PROVIDER: GSE111727 | GEO | 2018-03-13

REPOSITORIES: GEO

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Publications

Single-Cell RNA-Seq Reveals Transcriptional Heterogeneity in Latent and Reactivated HIV-Infected Cells.

Golumbeanu Monica M   Cristinelli Sara S   Rato Sylvie S   Munoz Miguel M   Cavassini Matthias M   Beerenwinkel Niko N   Ciuffi Angela A  

Cell reports 20180401 4


Despite effective treatment, HIV can persist in latent reservoirs, which represent a major obstacle toward HIV eradication. Targeting and reactivating latent cells is challenging due to the heterogeneous nature of HIV-infected cells. Here, we used a primary model of HIV latency and single-cell RNA sequencing to characterize transcriptional heterogeneity during HIV latency and reactivation. Our analysis identified transcriptional programs leading to successful reactivation of HIV expression. ...[more]

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