Next-Generation Sequencing Analysis Reveals Differential Expression Profiles of MiRNA-mRNA Target Pairs in KSHV-Infected Cells

Abstract

Kaposi's sarcoma associated herpesvirus (KSHV) causes several tumors, including primary effusion lymphoma (PEL) and Kaposi's sarcoma (KS). Cellular and viral microRNAs (miRNAs) have been shown to play important roles in regulating gene expression. A better knowledge of the miRNA-mediated pathways affected by KSHV infection is therefore important for understanding viral infection and tumor pathogenesis. In this study, we used deep sequencing to analyze miRNA and cellular mRNA expression in a cell line with latent KSHV infection (SLKK) as compared to the uninfected SLK line. This approach revealed 153 differentially expressed human miRNAs, eight of which were independently confirmed by qRT-PCR. KSHV infection led to the dysregulation of ~15% of the human miRNA pool and most of these cellular miRNAs were down-regulated, including nearly all members of the 14q32 miRNA cluster, a genomic locus linked to cancer and that is deleted in a number of PEL cell lines. Furthermore, we identified 48 miRNAs that were associated with a total of 1,117 predicted or experimentally validated target mRNAs; of these mRNAs, a majority (73%) were inversely correlated to expression changes of their respective miRNAs, suggesting miRNA-mediated silencing mechanisms were involved in a number of these alterations. Several dysregulated miRNA-mRNA pairs may facilitate KSHV infection or tumor formation, such as up-regulated miR-708-5p, associated with a decrease in pro-apoptotic caspase-2 and leukemia inhibitory factor LIF, or down-regulated miR-409-5p, associated with an increase in the p53-inhibitor MDM2. Transfection of miRNA mimics provided further evidence that changes in miRNAs are driving some observed mRNA changes. Using filtered datasets, we also identified several canonical pathways that were significantly enriched in differentially expressed miRNA-mRNA pairs, such as the epithelial-to-mesenchymal transition and the interleukin-8 signaling pathways. Overall, our data provide a more detailed understanding of KSHV latency and guide further studies of the biological significance of these changes.

Fig 1. Relative abundance of human and KSHV-encoded miRNAs in KSHV-positive SLKK cells.

The expression levels of KSHV miRNAs are shown as the percentage of the total of viral miRNA reads. Data are the mean of sequenced samples from three independent experiments, each with two technical replicates with opposite sequencing directions. Percentages have been rounded to the closest digit. For a detailed presentation, see S2 and S3 Tables.

Fig 2. Expression of miRNAs and mRNAs in the analyzed libraries.

A. Volcano plot of differentially expressed human mature miRNAs in KSHV-infected versus uninfected cells. Vertical red lines indicate the threshold for a relative expression fold change (FC) of 2 or -2 fold compared to uninfected controls. The horizontal red line represents the threshold of a 0.05 P-value. Thus, the blue points lying in the top right and top left sectors are significantly up-regulated and down-regulated, respectively, in KSHV-positive versus KSHV-negative cells (P <0.05, FC ≥2 or ≤-2). Selected miRNAs that have been validated by qRT-PCR are labeled. B. Volcano plot of differentially expressed mRNAs in KSHV-infected versus uninfected cells. The plot is depicted as in Fig 2A, with vertical and horizontal red lines similarly representing the thresholds of a fold-change of 2 or -2 fold, and of a false-discovery rate (FDR) of 0.05 respectively. C. Top 15 repressed and induced miRNAs in KSHV-positive vs. uninfected SLK cells with P <0.05 and medium to high miRNA expression (threshold of a mean miR count of 10 or more across all replicates).

Fig 3. Analysis of miRNA expression in latent and de novo KSHV-infected cells.

A. Data represent the average log₂-transformed fold change of expression between latently infected SLKK cells and uninfected SLK cells, measured either by small RNA sequencing (black bars) or Taqman assay (grey bars). All the changes are significant (P≤0.05) except that of miR-210 as detected by miRNA-Seq. B. Effects of de novo KSHV infection on miRNAs seen down-regulated in the SLK/SLKK model. SLK cells were exposed to KSHV and after 5 days, changes in specific miRNAs were assessed by Taqman assay. The dotted line indicates the normalized level of these miRNAs in uninfected SLK cells. P-values were calculated using Student t-test. ** indicates P <0.01. ns: not significant. Expression levels of mature miRNAs were evaluated using the comparative CT method (2-deltaCT). Transcript levels of RNU43 were used for sample normalization. Bars depict the mean of 3 independent experiments; error bars reflect the standard deviation.

Fig 4. Differential expression of miRNAs and their known or predicted mRNA targets.

A. miRNA expression in latently infected SLKK cells compared to uninfected SLK cells and the mRNA expression of their corresponding targets (Taqman and qRT-PCR assays). miRNAs and mRNAs are shown in light and dark grey, respectively. miR-409-3p targets fibrinogen beta (FGB) and radixin (RDX). miR-409-5p is predicted to target MDM2. miR-708-5p targets caspase-2 (CASP2) and is predicted to target leukemia inhibitor factor (LIF). P-values were calculated using Student t-test. *, ** and *** indicate P <0.05, 0.01 and 0.001, respectively. B. Effect of miRNA transfection on target regulation. Scramble control (miR-scramble) and miRNA mimics for miR-409-3p, miR-409-5p and miR-708-5p were transfected in either SLK or SLKK cells. Quantitative real-time polymerase chain reaction revealed the target expression for these miRNAs and the relative value is presented as the mean ± standard deviation based on 3 independent experiments. Statistical analysis and its representation are as in Fig 4A.

Fig 5. Workflow of integrated miRNA-mRNA association analysis using IPA.

This experimental workflow shows the various filters used to associate miRNA-Seq and mRNA-Seq data. Numbers are presented as Total differentially expressed miRNAs or mRNAs (Up-regulated/Down-regulated).

Fig 6. Implications of miRNA-mRNA pairs in Pathogen-Influenced Signaling.

A total of 17 miRNAs and 28 mRNA targets are involved in the super pathway entitled ‘Pathogen-Influenced Signaling’. Only experimentally validated and highly predicted targets are presented here. The top part shows the up-regulated miRNAs and respective down-regulated targets. The bottom part shows the down-regulated miRNAs and respective up-regulated targets. The intensity of colors represents the extent of the up-regulation or down-regulation, in red and green respectively.