Role of microRNA modulation in the interferon-α/ribavirin suppression of HIV-1 in vivo

Abstract

Background: Interferon-α (IFN-α) treatment suppresses HIV-1 viremia and reduces the size of the HIV-1 latent reservoir. Therefore, investigation of the molecular and immunologic effects of IFN-α may provide insights that contribute to the development of novel prophylactic, therapeutic and curative strategies for HIV-1 infection. In this study, we hypothesized that microRNAs (miRNAs) contribute to the IFN-α-mediated suppression of HIV-1. To inform the development of novel miRNA-based antiretroviral strategies, we investigated the effects of exogenous IFN-α treatment on global miRNA expression profile, HIV-1 viremia, and potential regulatory networks between miRNAs and cell-intrinsic anti-HIV-1 host factors in vivo.

Methods: Global miRNA expression was examined in longitudinal PBMC samples obtained from seven HIV/HCV-coinfected, antiretroviral therapy-naïve individuals before, during, and after pegylated interferon-α/ribavirin therapy (IFN-α/RBV). We implemented novel hybrid computational-empirical approaches to characterize regulatory networks between miRNAs and anti-HIV-1 host restriction factors.

Results: miR-422a was the only miRNA significantly modulated by IFN-α/RBV in vivo (p<0.0001, paired t test; FDR<0.037). Our interactome mapping revealed extensive regulatory involvement of miR-422a in p53-dependent apoptotic and pyroptotic pathways. Based on sequence homology and inverse expression relationships, 29 unique miRNAs may regulate anti-HIV-1 restriction factor expression in vivo.

Conclusions: The specific reduction of miR-422a is associated with exogenous IFN-α treatment, and likely contributes to the IFN-α suppression of HIV-1 through the enhancement of anti-HIV-1 restriction factor expression and regulation of genes involved in programmed cell death. Moreover, our regulatory network analysis presents additional candidate miRNAs that may be targeted to enhance anti-HIV-1 restriction factor expression in vivo.

Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.

Figures

Figure 1. Heat map representing effects of IFN-α/RBV treatment on the expression of individual miRNAs.

45 miRNAs were significantly modulated by IFN-α/RBV in vivo, based on a paired t test and an uncorrected significance cutoff of p<0.05. Relative copy numbers of each miRNA are reported. Blue color indicates ≤−3 SD from the mean, red indicates ≥3 SD from the mean, and white represents the mean. Asterisks indicate previously established association with HIV-1.

Figure 2. miR-422a is modulated by IFN-α treatment.

(A) Expression of miR-422a in PBMC in vivo before, during and after IFN-α/RBV treatment (labeled as “Rx”). Error bars represent SEM. P-value was obtained using a paired t-test and FDR is reported. (B) Effects of IFN-α on the expression of miR-422a in CD4+ T cells in vitro; cells were plated at a million cells per well and treated with either 5 U/ml of IFN-α or media as a negative control. (C) Expression of MLH1 in PBMC in vivo before, during, and after IFN-α/RBV treatment. (D) Expression of TP53 in PBMC in vivo before, during, and after IFN-α/RBV treatment. Error bars represent SEM. P-values were obtained using paired Wilcoxon tests. (E) Correlation between TP53 fold induction and MLH1 fold induction in PBMC in vivo during IFN-α/RBV treatment. P-value was obtained using Spearman’s rank test.

Figure 3. Visualization of miRNA and mRNA regulatory networks.

(A) Plot of global miRNA and anti-HIV-1 restriction factor responses to IFN-α/RBV treatment. Numbers in blue and red represent tallies of microRNAs and restriction factor mRNAs in each quadrant, respectively. P-values were obtained using Fisher’s exact tests. (B) Integrative bioinformatic analyses of our miRNA data, restriction factor, MLH1 and TP53 mRNA profiles within the context of gene regulatory networks. Ingenuity Pathway Analysis (IPA) software was implemented to create the network map.

Figure 4. Global network of putative regulatory interactions between miRNAs and anti-HIV-1 restriction factor mRNAs.

miRNA and mRNA expression data were measured in longitudinal PBMC samples from IFN-α/RBV-treated patients enrolled in the SHCS. Two variables were used to generate the network: 1) inverse expression relationships between a given miRNA-mRNA pair (represented as a dashed line drawn between a miRNA – mRNA pair), and 2) Significant sequence homology between a given miRNA seed region and a restriction factor 3′ UTR (word size 4, alignment length > = 5, e-value