Interaction effects calculated by multiple linear regression.

<p>This schematic visualization of second order linear regression models interaction effects. The diagram of the linear regression model includes two main covariates (strain <i>H</i> and stimulation with <i>Γ</i>) and their interaction covariate <i>H∶Γ</i>. The main covariates can assume two values (<i>H</i>: C57BL/6 or BALB/c; <i>Γ</i>: IFN-γ stimulation or no stimulation). The arrows indicate the estimated effects β. The pink and turquoise arrows reflect the aggravating or alleviating interaction effects as deviations from the additive model. A second order linear model can dissect the effects arising from two perturbations and their interaction by looking at the magnitude and significance of its regression covariates. Most importantly, the interaction covariate can indicate either an alleviating (weaker than expected from the single intervention effects) or aggravating (stronger than expected) interaction. The linear model includes two main covariates <i>H</i> and <i>Γ</i> and their interaction covariate <i>Η∶Γ</i>.</p

Eruption plot.

<p>A: Effect size is displayed along the x-axis at log₂ scale and the y-axis shows the negative log₁₀ p-value. The vertical blue lines indicate 1.5 fold up and down-regulation and the horizontal blue line indicates a significance of 0.05 after Bonferroni adjustment. They bound the regions of biological interest (ROI), which are characterized by a sufficiently high effect, and a sufficiently low p-value. I.e., biologically interesting effects are found in the top left and the top right segment of the plot. Each gene is represented by an arrow comparing the effect size and significance estimate of a covariate (the interaction covariate <i>H∶Γ</i> in this case) between Model 1 (arrow tail) to Model 2 (arrow head). The details of Models 1 and 2 are given in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0091840#pone-0091840-t002" target="_blank">Table 2</a>. Black and grey arrows represent genes completely contained within ROI and excluded completely from ROI, respectively. Red and blue arrows represent genes that are located within ROI solely in Model 1 and Model 2, respectively. B: Density plot of the p-values of Model 1 (red) and Model 2 (green). The dashed lines indicate the median of each density.</p

Schematic visualization for the interpretation of the eruption plot.

<p>The results of two models can be compared in the eruption plot. The arrows of an eruption plot can have different sizes and directions. This scheme helps to interpret the arrow. Effect size is displayed along the x-axis and the significance on the y-axis. The red area shows the region of interest (ROI).</p

Experimental setup.

<p>Experimental setup.</p

Linear regression models.

<p>Linear regression models.</p

Cluster and pathway analysis.

<p>A: the effect estimates of Model 3 were subjected to a hierarchical cluster analysis. Genes are displayed in the rows, which showed a significant global effect (F-test p-value <0.05 after FDR correction and at least one of the covariates having +/−1.5 fold change). The three columns are the covariates <i>Η</i>, <i>Γ</i>, and <i>Η∶Γ</i>. The column <i>strain</i> shows differences between C57BL/6 and BALB/c, up-regulation shown in red and down-regulation shown in green. The column <i>Γ</i> shows in red up-regulation in BALB/c and in green down-regulation upon IFN-γ stimulation. The third column helps to distinguish alleviating and aggravating effects. Aggravating effects are represented in pink and alleviating effects in turquoise. P-values are plotted separately in a heatmap. The order of the genes is given by the effect estimate clustering. P-values are given in −log₁₀ scale and start from 0 displayed in colors ranging from blue to white. B: The results of a pathway enrichment analysis of cluster 6 as a bar plot. The direction of regulation of the genes of cluster 6 is indicated by the color bar. Gene Ontology ‘Biological Process’ terms and KEGG pathway categories (p<0.01) are sorted from bottom (most significant) to top. To reduce redundancy, similar terms are represented by the most significant and specific term. For complete list of functional annotations see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0091840#pone.0091840.s010" target="_blank">Table S2</a>. The right side shows the results of a TFBS analysis of this gene cluster. The two most significantly represented TFBS are given by the name of the transcription factor, the motif, and the p-value.</p

Real-time transcriptional profiling of cellular and viral gene expression during lytic cytomegalovirus infection

During viral infections cellular gene expression is subject to rapid alterations induced by both viral and antiviral mechanisms. In this study, we applied metabolic labeling of newly transcribed RNA with 4-thiouridine (4sU-tagging) to dissect the real-time kinetics of cellular and viral transcriptional activity during lytic murine cytomegalovirus (MCMV) infection. Microarray profiling on newly transcribed RNA obtained at different times during the first six hours of MCMV infection revealed discrete functional clusters of cellular genes regulated with distinct kinetics at surprising temporal resolution. Immediately upon virus entry, a cluster of NF-κB- and interferon-regulated genes was induced. Rapid viral counter-regulation of this coincided with a very transient DNA-damage response, followed by a delayed ER-stress response. Rapid counter-regulation of all three clusters indicated the involvement of novel viral regulators targeting these pathways. In addition, down-regulation of two clusters involved in cell-differentiation (rapid repression) and cell-cycle (delayed repression) was observed. Promoter analysis revealed all five clusters to be associated with distinct transcription factors, of which NF-κB and c-Myc were validated to precisely match the respective transcriptional changes observed in newly transcribed RNA. 4sU-tagging also allowed us to study the real-time kinetics of viral gene expression in the absence of any interfering virion-associated-RNA. Both qRT-PCR and next-generation sequencing demonstrated a sharp peak of viral gene expression during the first two hours of infection including transcription of immediate-early, early and even well characterized late genes. Interestingly, this was subject to rapid gene silencing by 5-6 hours post infection. Despite the rapid increase in viral DNA load during viral DNA replication, transcriptional activity of some viral genes remained remarkably constant until late-stage infection, or was subject to further continuous decline. In summary, this study pioneers real-time transcriptional analysis during a lytic herpesvirus infection and highlights numerous novel regulatory aspects of virus-host-cell interaction

Gene expression kinetics define distinct functional clusters.

<p>(<b>A</b>) Heat-maps indicating the fold-changes are shown as matrices with rows representing genes and columns representing the time points post infection. Red represents up-regulation, blue down-regulation (>2-fold, p≤0.01) in newly transcribed RNA relative to uninfected cells. Ordering of genes in the heat-maps was determined using non-supervised hierarchical clustering. Shown are the 5 clusters of genes we identified. (<b>B</b>) All clusters are associated with distinct functional annotations. Enrichment analysis results of Gene Ontology ‘Biological Process’ terms and KEGG pathways are shown for each of the five clusters with the most significant (p≤0.01) categories displayed in the graphs as bars, sorted from bottom (most significant) to top. To reduce redundancy, similar terms are represented by the most significant and specific term. For complete list of functional annotations see <a href="http://www.plospathogens.org/article/info:doi/10.1371/journal.ppat.1002908#ppat.1002908.s009" target="_blank">Table S2a</a>. (<b>C</b>) Specific transcription factor binding sites correlate with functional clusters. Shown are exemplary transcription factors with over-represented binding sites unique for the different clusters. For a complete list of over-represented transcription factor weight matrices see <a href="http://www.plospathogens.org/article/info:doi/10.1371/journal.ppat.1002908#ppat.1002908.s009" target="_blank">Table S2b</a>. Illustrated are the transcription factor weight matrices, the percentage of promoters with sites and p-value.</p

Establishment of 4sU-tagging for lytic MCMV infection.

<p>(<b>A</b>) Incorporation of 4sU throughout MCMV infection. Cells were infected with MCMV at an MOI of 10 and exposed to 200 µM 4sU for 1 h at different times of infection before total RNA was isolated. Thiol-specifically biotinylated RNA was subjected to dot blot analysis in 10-fold dilutions (1 µg down to 1 ng). A biotinylated oligonucleotide of 81 nt (PC, 100 ng down to 0.1 ng) was used to quantify 4sU-incorporation; M = mock control. (<b>B</b>)–(<b>D</b>) Comparison of genes identified to be regulated in newly transcribed RNA to genes regulated in total RNA. (<b>B</b>) Numbers of genes up- and down-regulated (>2-fold, p≤0.05) at different times of infection are shown for newly transcribed RNA and total RNA. (<b>C</b>) Venn diagrams of all genes regulated more then 2-fold in newly transcribed RNA and total RNA. (<b>D</b>) Venn diagrams showing genes regulated >2-fold in total RNA at 2, 4 and 6 hpi and in newly transcribed RNA at and prior to the indicated time point of infection; red = newly transcribed RNA, blue = total RNA.</p

Validation of exemplary transcription factors.

<p>NIH-3T3 fibroblasts were infected with MCMV at an MOI of 10 for the indicated time points and lysates were prepared for western blot analysis (<b>A</b>), for immune staining (<b>B</b>) or luciferase assay (<b>C</b>). Western blot analysis was performed on samples prepared from uninfected and infected NIH-3T3 cells probed for RelA and IkBα (<b>A</b>). GAPDH was probed as loading control. For the immunofluorescence staining (<b>B</b>) cells were fixed and stained with the indicated antibodies; white circle indicating nucleus, nuclear dimensions were acquired by DAPI staining and its outline was overlaid into the shown channels; green, RelA; red, viral IE1. For the luciferase assays cells were transfected with a c-Myc-reporter construct (<b>C</b>) and infected 48 hours post transfection with MCMV at an MOI of 10. At the indicated times post infection, Firefly-Luciferase measurements were performed in triplicates. Shown is the mean +/− SD of a representative of three experiment; mpi = minutes post infection, hpi = hours post infection.</p