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. 2013 Jan 2;27(1):29-37.
doi: 10.1097/QAD.0b013e32835b3e26.

Suberoylanilide Hydroxamic Acid Induces Limited Changes in the Transcriptome of Primary CD4(+) T Cells

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Free PMC article

Suberoylanilide Hydroxamic Acid Induces Limited Changes in the Transcriptome of Primary CD4(+) T Cells

Nadejda Beliakova-Bethell et al. AIDS. .
Free PMC article

Abstract

Objective: To assess the off-target effects of the histone deacetylase inhibitor (HDACi) suberoylanilide hydroxamic acid (SAHA) in human primary CD4 T cells.

Design: A pharmacologically relevant concentration (340 nmol/l) of SAHA was shown to significantly increase histone hyperacetylation by 24 h and this length of treatment was selected to determine its impact on gene expression in primary CD4 T cells.

Methods: Illumina Beadchips for microarray gene expression analysis were used to analyze differential gene expression between cells treated or not with SAHA with a paired analysis using multivariate permutation tests. Gene ontology, biological pathway and protein interaction network analyses were used to identify the higher order biological processes affected by SAHA treatment.

Results: Modest modulation by SAHA was observed for 1847 genes with 80% confidence level of no more than 10% false positives. A thousand genes were upregulated by SAHA and 847 downregulated. Pathways and gene ontologies overrepresented in the list of differentially expressed genes included Glycolysis/Gluconeogenesis, tRNA Modification, and the Histone Acetyltransferase Complex. Protein interaction network analysis revealed that transcription factor c-Myc, which was downregulated by SAHA treatment at the mRNA level, interacts with a number of SAHA-responsive genes.

Conclusions: The effects on transcription by SAHA were sufficiently modest to support trials to activate HIV replication as part of an eradication strategy. SAHA did not appear to modulate proliferative or apoptotic processes to a great extent, which might impact the ability of patients to eradicate the virus reservoir following activation by HDACi treatment.

Conflict of interest statement

For the remaining authors, no conflicts of interest were declared.

Conflicts of interest

D.D.R. is a consultant for Merck and Co. Inc., Theraclone, Myriad, Bristol-Myers Squibb, Anadys Pharmaceuticals, Inc., Gilead Sciences, Hoffman-La Roche Inc., Monogram Biosciences, Biota, Chimerx, Idenix, and Gen-Probe, but these roles are not in conflict with the data presented in this manuscript.

C.A.S. has previously received research support from Merck Research Laboratories for an unrelated project.

Figures

Fig. 1
Fig. 1. Suberoylanilide hydroxamic acid but not valproic acid treatment leads to a significant increase in histone acetylation
Primary CD4+ T cells from three donors were treated for 6, 24, or 48 h with suberoylanilide hydroxamic acid (SAHA) (340 nmol/l), valproic acid (VPA) (40 μmol/l), or left untreated (i.e., DMSO only, which was the solvent used to dissolve SAHA). Total protein was extracted and 5 μg used for immunoblot analysis with antiacetylated histone H3 (Ac-H3) and antitotal histone H3 (H3) antibodies. The bands were quantified using ImageJ software version 1.45. The fold changes were obtained by dividing the SAHA or VPA band intensities by the band intensities for the untreated control after normalization of the acetylated to total histone H3. The error bars represent standard error of the mean. Significant changes (P <0.05) as assessed by 2-way ANOVA with a Tukey post-hoc test are denoted by an asterisk (*).
Fig. 2
Fig. 2. Validation of gene expression by real-time quantitative PCR
Fold changes of gene expression between the SAHA-treated and untreated control groups are shown for real-time quantitative PCR (RT-qPCR) (black bars) and microarrays (grey bars). All the genes were found to be significantly modulated by SAHA treatment by microarray analysis. Genes marked with a double asterisk (**) were confirmed by RT-qPCR to be significantly modulated by SAHA (P <0.05, one-tailed paired t-test), and genes marked with a single asterisk (*) approached significance (i.e., 0.05 <P <0.1). The association of genes with functional categories indicating the criteria by which they were selected for RT-qPCR validation is shown on the left of the figure. HLA-DMB had the highest fold change and is a marker of immune activation.
Fig. 3
Fig. 3. Direct protein interaction network constructed from the products of suberoylanilide hydroxamic acid-modulated genes
MetaCore was used to identify protein-protein and protein-DNA interactions between the protein products of SAHA modulated genes. For visualization purposes, only genes with a fold change <+1.4 or >−1.4 were used for constructing the protein interaction network. Each node represents a gene and nodes with multiple connections form hubs. The largest hubs are c-Myc, AP-1, c-Jun, ZNF42 (MZF1), Bcl-6, EZH2, CDK2, and NOTCH1 and correspond to transcription factors. Green and red lines refer to positive and negative regulation, respectively, whereas grey lines depict unspecified effects. Upregulated genes are depicted in red and downregulated genes in blue as indicated by the scale bar. The types of interactions are indicated with a letter code on top of the lines and can be visualized by zooming using the on-line version of the article: B, binding; C, cleavage; CM, covalent modifications; +p, phosphorylation; –p, dephosphorylation; T, transformation; TR, transcription regulation; GR, group relation; CS, complex subunit.

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