Suberoylanilide hydroxamic acid (SAHA) induces limited changes in the transcriptome of primary CD4+ T cells
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE41504 | GEO | 2012/10/12
SECONDARY ACCESSION(S): PRJNA177331
REPOSITORIES: GEO
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Project description:This study evaluated primary CD4+ T cell gene expression treated with pharmacologically achievable concentration (340 nM) of SAHA for 24 hours in order to evaluate potential side effects of this compound in cells relevant to HIV infection. Analysis of human primary CD4+ T cells taken from 9 healthy donors treated with 340 nM of SAHA for 24 hours. Results identify genes modulated by SAHA treatment in human primary CD4+ T cells.
2012-10-12 | E-GEOD-41504 | biostudies-arrayexpress
Project description:Design: Persistent latently infected CD4+ T cells represent a major obstacle to HIV eradication. Histone deacetylase inhibitors (HDACis) are a promising activation therapy in a “shock and kill” strategy. However, off-target effects of HDACis on host gene expression are poorly understood in primary cells of the immune system. We hypothesized that HDACi-modulated genes would be best identified with a dose response analysis. Methods: Resting primary CD4+ T cells were treated with increasing concentrations (0.34, 1, 3, or 10 μM) of the HDACi, suberoylanilide hydroxamic acid (SAHA), for 24 hours and then subjected to microarray gene expression analysis. Genes with dose-correlated expression were identified with a likelihood ratio test using Isogene GX and a subset of these genes with a consistent trend of up or downregulation at each dose of SAHA were identified as dose-responsive. Histone modifications were characterized in promoter regions of the top 6 SAHA dose-responsive genes by RT-qPCR analysis of immunopreciptated chromatin (ChIP). Results: A large number of genes were shown to be up (N=657) or down (N=725) regulated by SAHA in a dose-responsive manner (FDR p-value < 0.05 and fold change ≥ |2|). Several of these genes (CTNNAL1, DPEP2, H1F0, IRGM, PHF15, and SELL) are potential in vivo biomarkers of SAHA activity. SAHA dose-responsive gene categories included transcription factors, HIV restriction factors, histone methyltransferases, and host proteins that interact with HIV proteins or the HIV LTR. Pathway analysis suggested net downregulation of T cell activation with increasing SAHA dose. Histone acetylation was not correlated with host expression, but plausible alternative mechanisms for SAHA-modulated expression were identified. Conclusions: Numerous host genes in CD4+ T cells are modulated by SAHA in a dose-responsive manner, including genes that may negatively influence HIV activation from latency. Our study suggests that SAHA influences gene expression through a confluence of several mechanisms, including histone acetylation, histone methylation, and altered expression and activity of transcription factors.
2015-08-13 | GSE66994 | GEO
Project description:Suberoylanilide hydroxamic acid (SAHA) has been assessed in clinical trials as part of a “shock and kill” strategy to cure HIV-infected patients. While it was effective at inducing expression of HIV RNA "shock" , treatment with SAHA did not result in the reduction of reservoir size "kill". We therefore utilized a systems biology approach to dissect the mechanisms of action of SAHA that may explain its limited success in “shock and kill” strategies. CD4+ T cells from HIV seronegative donors were treated with 1 uM SAHA or its solvent dimethyl sulfoxide for 24 hours. Differential protein expression and post-translational modification was measured with two-dimensional liquid chromatography - tandem mass spectrometry iTRAQ proteomics. Gene expression changes were assessed by Illumina microarrays. Using limma package in the R computing environment, we identified 185 proteins, 18 phosphorylated forms, 4 acetylated forms and 2,982 genes, whose expression was modulated by SAHA. A protein interaction network integrating these 4 data types identified the transcriptional regulator HMGA1 to be upregulated by SAHA at the transcript, protein and acetylated protein levels. HMGA1 has been shown to repress HIV transcription, which is not optimal with respect to a shock and kill strategy. Further functional category assessment of proteins and genes modulated by SAHA identified gene ontology terms related to NFB signaling, protein folding and autophagy, which are all relevant to HIV reactivation. In summary, this study identified a number of host factors that may be therapeutically targeted to achieve more potent HIV reactivation in the “shock and kill” treatment, when using SAHA, either through modification of SAHA itself or through combination with other latency reversing agents. Finally, proteome profiling highlighted a number of potential adverse effects of SAHA, which transcriptome profiling alone would not have identified.
2015-09-10 | PXD002150 | Pride
Project description:miRNA expression profiling of K562 ctrl vs K562 treated Saha 5 µM 6h
2017-05-22 | GSE69958 | GEO
Project description:miRNA expression profiling of U937 ctrl vs U937 treated Saha 5 µM 6h
2017-05-22 | GSE69957 | GEO
Project description:Purpose: The goal of this study is to identify host genes whose expression is perturbed in primary CD4+ T cells by histone deacetylase (HDAC) inhibitors (HDACi) SAHA and RMD, which have different potencies and specificities for various HDACs. The study aims to evaluate the effects of SAHA and RMD that may promote or inhibit reactivation of HIV provirus out of latency. Methods: Peripheral blood mononuclear cells were collected from 4 HIV-seronegative donors. CD4+ T cells were isolated and utilized to generate an in vitro model of latent HIV infection (model developed in the Spina laboratory and previously described in Spina et al., 2013). Mock-infected cells were cultured in parallel to evaluate effects of SAHA and RMD that may be dependent on the exposure of cells to virus. Following generation of the model, cells were treated with SAHA, RMD or their solvent dimethyl sulfoxide (DMSO) for 24 hours. Mock-infected cells were treated in parallel. The experiment had 4 biological replicates, 6 conditions for each, for a total of 24 samples. ERCC spikes (Thermo Fisher Scientific, Inc.) were added to cell lysates based on cell number in each sample (10 ul of 1:800 dilution per million cells). Mix 1 was used for DMSO- and mix 2 for SAHA- and RMD-treated cells. After all samples were collected, RNA was extracted and subjected to deep sequencing by Expression Analysis, Inc. Sequence reads that passed quality filters were mapped using Tophat (human genome) or Bowtie (ERCC spikes and HIV) and counted using HTSeq. ERCC spikes with the same concentration in mixes 1 and 2 were utilized to remove unwanted technical variation. Any human gene which did not achieve at least 1 count per million reads in at least 4 samples or any ERCC that did not achieve at least 5 reads in at least 4 samples was discarded. Differential gene expression analysis was performed using library EdgeR in Bioconductor R. National Center for Biotechnology Information (NCBI) HIV-1 Human Interaction Database was then searched for genes that have been implicated in controlling HIV latency. EdgeR output was used to extract expression information of the genes of interest from the NCBI database to identify genes implicated in HIV latency that were modulated by SAHA and RMD. The resulting lists were manually curated to verify relevance to HIV latency, using the Description column of the NCBI database, as well as available PubMed references. Results: Using a custom built data analysis pipeline, ~100 million reads per sample were mapped to the human genome (build hg38). After applying filtering criteria, 16058 human transcripts, 19 ERCC spikes transcripts, and HIV NL4-3 transcripts were identified with the Tophat/Bowtie and HTSeq workflow. Differential expression analysis was performed between SAHA or RMD-treated and DMSO-treated cells. In addition, differential modulation of gene expression by SAHA and RMD in the model of HIV latency and mock-infected cells was assessed using EdgeR. In mock-infected cells, SAHA upregulated 3,971 genes and downregulated 2,940 genes; RMD upregulated 5,068 genes and downregulated 4,050 genes. In the model of HIV latency, SAHA upregulated 3,498 genes and downregulated 2,904 genes; RMD upregulated 5,116 genes and downregulated 4,053 genes (FDR < 0.05). SAHA modulated 6, and RMD 11 genes differentially between mock-infected cells and the model of HIV latency. Following search of the NCBI HIV-1 Human Interaction Database, 27 genes upregulated and 29 downregulated in common between SAHA and RMD were found to be relevant to regulation of HIV latency; 31 were up- and 32 downregulated by RMD only; and 6 were up- and 2 were downregulated by SAHA only. Conclusions: This study demonstrates that SAHA and RMD, which have different potencies and specificities for HDACs, modulate a set of overlapping genes implicated in regulation of HIV latency. Some of these genes may be explored as additional host targets for improving the outcomes of “shock and kill” strategies.
2019-02-08 | GSE114883 | GEO
Project description:miRNA expression profiling of KASUMI-1 ctrl vs KASUMI-1 treated Saha 5 µM 6h
2017-05-22 | GSE69956 | GEO
Project description:Transcriptional profiling of U937 scramble vs shHDAC2 before and after SAHA treatment at 5µM concentration for 6 and 24 hours.
2015-02-18 | GSE37529 | GEO
Project description:Transcriptional profiling of U937 scramble vs shHDAC2 before and after SAHA treatment at 5µM concentration for 6 and 24 hours. Different Experimental Conditions: U937 scramble (U937 trasfected with empty vector) vs shHDAC2 (U937 trasfected with shHDAC2 vector), untreated and treated with SAHA at 5 µM concentration for 6h and 24h. Biological replicates: 2 for each sample, independently grown and harvested at 6 and 24 hours. One replicate per array.
2015-02-18 | E-GEOD-37529 | biostudies-arrayexpress
Project description:To elucidate the molecular mechanism involved in increased tolerance to high-salinity stress by the application of HDAC inhibitor named SAHA
2016-12-01 | GSE84715 | GEO