Regulation of the hepatitis C virus RNA replicase by endogenous lipid peroxidation

Although oxidative tissue injury often accompanies viral infection, there is little understanding of how it influences virus replication. We show that multiple hepatitis C virus (HCV) genotypes are exquisitely sensitive to oxidative membrane damage, a property distinguishing them from other pathogenic RNA viruses. Lipid peroxidation, regulated in part through sphingosine kinase 2, severely restricts HCV replication in Huh-7 cells and primary human hepatoblasts. Endogenous oxidative membrane damage lowers the 50% effective concentration of direct-acting antivirals, suggesting critical regulation of the conformation of the NS3/4A protease and NS5B polymerase, membrane-bound HCV replicase components. Resistance to lipid peroxidation maps genetically to trans-membrane and membrane-proximal residues within these proteins, and is essential for robust replication in cell culture, as exemplified by the atypical JFH1 strain. Thus, the typical, wild-type HCV replicase is uniquely regulated by lipid peroxidation, providing a novel mechanism for attenuating replication in stressed tissue and possibly facilitating long-term viral persistence

Pre-Micro RNA Signatures Delineate Stages of Endothelial Cell Transformation in Kaposi Sarcoma

MicroRNAs (miRNA) have emerged as key regulators of cell lineage differentiation and cancer. We used precursor miRNA profiling by a novel real-time QPCR method (i) to define progressive stages of endothelial cell transformation cumulating in Kaposi sarcoma (KS) and (ii) to identify specific miRNAs that serve as biomarkers for tumor progression. We were able to compare primary patient biopsies to well-established culture and mouse tumor models. Loss of mir-221 and gain of mir-15 expression demarked the transition from merely immortalized to fully tumorigenic endothelial cells. Mir-140 and Kaposi sarcoma–associated herpesvirus viral miRNAs increased linearly with the degree of transformation. Mir-24 emerged as a biomarker specific for KS

Toll-Like Receptor-3 Is Dispensable for the Innate MicroRNA Response to West Nile Virus (WNV)

<div><p>The innate immune response to West Nile virus (WNV) infection involves recognition through toll-like receptors (TLRs) and RIG-I-like receptors (RLRs), leading to establishment of an antiviral state. MiRNAs (miRNAs) have been shown to be reliable biomarkers of TLR activation. Here, we sought to evaluate the contribution of TLR3 and miRNAs to the host response to WNV infection. We first analyzed HEK293-NULL and HEK293-TLR3 cells for changes in the innate immune response to infection. The presence of TLR3 did not seem to affect WNV load, infectivity or phosphorylation of IRF3. Analysis of experimentally validated NFκB-responsive genes revealed a WNV-induced signature largely independent of TLR3. Since miRNAs are involved in viral pathogenesis and the innate response to infection, we sought to identify changes in miRNA expression upon infection in the presence or absence of TLR3. MiRNA profiling revealed 70 miRNAs induced following WNV infection in a TLR3-independent manner. Further analysis of predicted gene targets of WNV signature miRNAs revealed genes highly associated with pathways regulating cell death, viral pathogenesis and immune cell trafficking.</p></div

Poisson factor models with applications to non-normalized microRNA profiling.

Next-generation (NextGen) sequencing is becoming increasingly popular as an alternative for transcriptional profiling, as is the case for micro RNAs (miRNA) profiling and classification. miRNAs are a new class of molecules that are regulated in response to differentiation, tumorigenesis or infection. Our primary motivating application is to identify different viral infections based on the induced change in the host miRNA profile. Statistical challenges are encountered because of special features of NextGen sequencing data: the data are read counts that are extremely skewed and non-negative; the total number of reads varies dramatically across samples that require appropriate normalization. Statistical tools developed for microarray expression data, such as principal component analysis, are sub-optimal for analyzing NextGen sequencing data. We propose a family of Poisson factor models that explicitly takes into account the count nature of sequencing data and automatically incorporates sample normalization through the use of offsets. We develop an efficient algorithm for estimating the Poisson factor model, entitled Poisson Singular Value Decomposition with Offset (PSVDOS). The method is shown to outperform several other normalization and dimension reduction methods in a simulation study. Through analysis of an miRNA profiling experiment, we further illustrate that our model achieves insightful dimension reduction of the miRNA profiles of 18 samples: the extracted factors lead to more accurate and meaningful clustering of the cell lines. The PSVDOS software is available on request.Link_to_subscribed_fulltex

Venn diagram of miRNAs that were induced in HEK293 Null and HEK293 TLR3 cells.

<p>Venn diagram representation of miRNAs induced following WNV infection of HEK293-Null and HEK293-TLR3 cells or polyI:C stimulation of HEK293-TLR3 cells. The number of shared, induced miRNAs are shown for each sample subset. A detailed list of the miRNAs induced for each category represented in the Venn diagram (HEK293-NULL +WNV, HEK293-TLR3 + WNV and HEK293-TLR3 + polyI:C treatment) is shown in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0104770#pone.0104770.s008" target="_blank">Table S6</a>.</p

MiRNA profiling reveals a WNV-induced signature.

<p>Large-scale miRNA profiling was carried out in HEK293-Null and –TLR3 cells using Taqman-based qPCR. Heatmap representation of all raw data points for the experiment. Sample abbreviations are as follows: UN – mock infected cells; WNV – WNV-infected cells; polyIC – cells treated with TLR3 agonist polyI:C; MB – cells exposed to methylene blue-inactivated WNV; Form – cells exposed to formalin-inactivated WNV. Highly abundant miRNAs are indicated by red and non-expressed miRNAs by blue color. Yellow indicates an intermediate expression level. This is also shown underneath the heatmap. The miRNAs were clustered based on expression. The dendrogram is shown on the top and interesting clusters are highlighted in green and indicated by small letters (a high resolution figure is presented as <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0104770#pone.0104770.s002" target="_blank">Figure S2</a>).</p

WNV infection induces a unique NFκB-responsive gene expression profile.

<p>HEK293-Null and –TLR3 cells under the specified conditions were analyzed for gene expression profiles using a qPCR array consisting of ∼90 NFκB-responsive genes. (A,B) Fold induction of genes was calculated by comparing WNV-infected samples to cells treated with formalin-inactivated virus. WNV-induced gene expression is shown at 0 hours post-infection (A) and 2 hours post-infection (B) with WNV (MOI = 10). Black bars denote TLR3-expressing HEK293 cells while open bars represent HEK293-Nulls. (C) The median CT across all samples was calculated and is shown +/− SEM for each gene analyzed. All genes shown were abundantly expressed (CT<35). (D) Heatmap of NFκB genes profiled. Highly abundant miRNAs are indicated by red and non-expressed miRNAs by blue color. Yellow indicates an intermediate expression level. This is also shown underneath the heatmap. The miRNAs were clustered based on expression.</p

The cellular response to WNV infection is unaffected by TLR3 status.

<p>(A) RT-PCR analysis of TLR3 expression in HEK293-Null and HEK293-TLR3 cells. RT negative reactions were performed as a control. (B) Immunofluorescence images of cells either mock- or WNV-infected are shown. Cells were stained with WNV E antibody (red) and DAPI (blue) and merged, deconvoluted images are shown at 630× magnification. (C–F) Western blots of phosphorylated IRF3 and beta actin in HEK293-Null and HEK293-TLR3 cells at various time points following WNV infection or post-treatment with the TLR3 agonist poly I:C. Mock infected cells and cells treated with inactivated WNV are shown as controls. (G, H) xCelligence analysis of cell viability following infection with serial dilutions of WNV NY99 (MOI = 5 to 0.00005). WNV-induced cytopathogenicity curves are shown for HEK293-Null (G) and HEK293-TLR3 cells (H). Reads were taken every 30 minutes for a period of 100 hours. (I) WNV-induced CPE kinetics were obtained by plotting the time of peak cell index for each sample against the concentration of WNV. HEK293-Nulls are represented by the blue line while HEK293-TLR3s are denoted by the red line. This panel shows a linear regression across 5 log dilutions. Shown are the individual cell indices at each dilution, the calculated robust linear regression lines (R² = 0.968) and in the gray shading the standard error (SE) band across the entire dilution range. (J) Viral load was determined by QPCR analysis for WNV envelope protein using a set of known WNV envelope standards. Panel J shows WNV copy number as determined by real-time qPCR using two biological replicate experiments (1 and 2) conducted one week apart. There was no significant growth difference.</p

WNV-induced miRNAs target processes functionally relevant to WNV pathogenesis.

<p>WNV signature miRNAs were analyzed for functions of predicted targets using Ingenuity Pathway Analysis software (IPA). Predicted targets of these miRNAs were determined and filtered through several criteria to yield functional categories for target genes. (A) The top functional categories are represented and the number of miRNA target genes in each category is denoted. (B) More detailed functions of the WNV-induced miRNA targets. Functions are shown along with statistical significance (P value) and the number of genes that correspond to each function. The p value was calculated in IPA using the right-tailed Fisher Exact Test and compares the number of focus genes that participate in a given functional process and the total number of genes known to be associated with the function in the selected set of miRNA target genes.</p

Directed Comparison of abundant miRNAs.

<p>All miRNAs with at least one data point had a CT≤28 were selected, normalized to stable small RNAs, and the median CT across the 2, 4, and 8 hr time point was calculated. These were further standardized to yield a Z score, which reflects relative changes. The Z score is shown on the vertical axis and miRNAs on the horizontal axis. The Z scores were ordered by the level of uninfected HEK293-Null (A, B) or HEK293-TLR3 (C, D) cells. Panels (A) and (C) compare the response of WNV to formalin-inactivated virus. Panels (B) and (D) compare the response of WNV infection to polyI:C stimulation. (E) Caliper LabChip analysis of a highly expressed and undetected miRNA. qPCR products of miRNA assays were run on a Caliper LabChip GX and the resulting electropheregram is shown. The sample yields a single peak corresponding to the expressed miRNA and two assay marker bands (UM – upper marker and LM – lower marker). The undetected miRNA electropheregram shows only an upper and lower marker peak with very little to no background signal, confirming the high specificity of this assay.</p