<i>k</i>-means clustering of the significant transcript lists reveals similar clusters.

<p>Mean normalised expression profile of individual clusters (y axis, ±SD, n = 4) at each time point (x axis; 0, 1, 3, 6, 12 and 24 hours) for each cluster. N: number of transcripts within cluster; P: most significant canonical pathway (IPA). Clusters are grouped by similarity in kinetic profile (Pearsons correlation, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0097702#pone.0097702.s007" target="_blank">Table S2</a>) and top canonical pathway.</p

Predicted transcriptional regulator identification and NFκB, IRF and STAT gene expression following LPS and Pam3CSK4 stimulation.

<p>(<b>A</b>) Predicted upstream transcriptional regulators from IPA; stimulations analysed independently using Pam3CSK4 1202 and LPS 4777 transcripts lists, at each time point only genes whose expression were 1.8 FC different from the media control at that time point were taken into consideration. Predicted upstream transcription regulators which met the criteria (<i>p</i><0.01 (Fishers Exact Test) and <i>z</i> activation score >2.5) shown plotted by <i>z</i>-activation score only at the time points where significance criteria met. (<b>B</b>) Mean mRNA expression of predicted transcription regulators plotted as log2 fold change (y axis) across time (x axis; 0, 1, 3, 6, 12 and 24 hours), fold change is relative to the media control at each time point, only those predicted transcription regulators whose mRNA expression is >1.8 FC relative to media control at one or more one time points are shown. (<b>C</b>) <b>NFkB genes.</b> Mean mRNA expression of the NFkB family genes, All 5 genes were significantly expressed and present in both Pam3CSK4 1202 and LPS 4777 transcript lists. (<b>D</b>) <b>Interferon Regulatory Factors.</b> Mean mRNA expression of the IRF and STAT genes. IRF1, IRF4, IRF7, IRF8, IRF9, STAT1, STAT2, STAT3, STAT4 and STAT5A were present in the LPS 4777 significantly expressed transcript list, none of the IRF or STAT genes (except STAT5B) were present in the 1202 Pam3CSK4 significant transcript list. (<b>E</b>) <b>Temporal Kinetics of NFkB and induced IRF and STAT genes.</b> Plotted for both LPS and Pam3CSK4 are mean fold change relative to media controls of the NFkB genes (NFKB1, NFKB2, REL, RELA, RELB) and mean fold change relative to media controls of selected IRF genes (IRF1, IRF2, IRF4, IRF7, IRF8, IRF9, STAT1, STAT2, STAT3, STAT4 and STAT5A).</p

Identifying potential cytokines involved in autocrine gene regulation by upstream analysis within IPA.

<p>(<b>A</b>) Predicted activated cytokines from IPA upstream analysis; stimulations analysed independently using Pam3CSK4 1202 and LPS 4777 transcripts lists, at each time point only genes whose expression were 1.8 fold different from the media control at that time point were taken into consideration. Predicted upstream cytokines which met the criteria (<i>p</i> value <0.01 (Fishers Exact Test) and <i>z</i>- activation score >2.5) shown plotted by <i>z</i>-activation score only at the time points where significance criteria met. (<b>B</b>) Cytokine identified from either predicted upstream analysis or canonical pathway analysis (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0097702#pone-0097702-g003" target="_blank">Fig. 3</a>) mean mRNA expression plotted as log2 fold change (y axis) across time (x axis; 0, 1, 3, 6, 12 and 24 hours), fold change is relative to the media control at each time point, only those predicted cytokines whose mRNA expression is >1.8 fold upregulated relative to media control at one or more one time points are shown.</p

LPS or Pam3CSK4 stimulations results in a differential response in gene expression over time.

<p>(<b>A</b>) 1 ml of human whole blood from healthy volunteers (N = 4) was stimulated with either Pam3CSK4 (200 ng/ml), LPS (1 ng/ml) or media control for different lengths of time (0, 1, 3, 6, 12 and 24 hours). Stimulations were analysed independently: media control compared to Pam3CSK4 and media control compared to LPS revealed 1202 and 4777 significantly expressed transcripts respectively. Transcripts were identified by normalising expression values to the median of the 0 hour samples, filtering by detection from background, statistical filtering (2 way ANOVA with Benjamini Hochberg multiple testing correction <i>p</i><0.01) and retaining transcripts whose expression was greater than 1.8 FC different between the media control and stimulation samples at one or more time point. (<b>B</b>) A Venn diagram of both significant transcript lists. Within the Venn for each subset the number of transcripts is given, with unique genes within IPA in brackets. For transcript lists the top 5 canonical pathways (IPA) are shown as well as a heat map of the normalised expression values of these transcripts for both stimulations over time.</p

Transcript lists analysed at each time point.

<p>(<b>A</b>) A graph showing the number of genes from the respective significant transcript lists (4777 LPS and 1202 Pam3CSK4 lists) at each time point which are more than 1.8 FC different compared to the media control at that time point. (<b>B</b>) The significantly expressed transcript lists (1202 Pam3CSK4 transcript list and 4777 LPS transcript list) were analysed in IPA. For each time point only genes whose expression were 1.8 FC different from the media control at that time point were taken into consideration. Shown is a heatmap of pathway significance of the top 25 IPA canonical pathways for each time point where significance criteria met (Fishers Exact test <i>p</i><0.01). The IPA canonical pathways were chosen by identifying from the LPS stimulation analyses the top 25 most significant pathways across the time points (mean –log <i>p</i> value) and then compared to Pam3CSK4. (<b>C</b>) Venn diagrams of cytokine/chemokines and transcriptional regulators identified using IPA gene functional classification from LPS 4777 and Pam3CSK4 1202 transcript lists with mean expression greater than 1.8 FC different to media control at 1 hour. Listed adjacent to the Venn diagrams are the genes from each subset.</p

NFκB and Interferon signalling pathways.

<p>Shown at the peak of their significance, 3 and 6 hours respectively. Significantly expressed genes within the pathway (from Pam3CSK4 1202 and LPS 4777 lists) shaded red if upregulated or blue if down regulated.</p

<i>L</i>. <i>monocytogenes</i> infection modulates a number of IFN signaling pathway and IFN response genes in the blood and spleen.

<p><b>(A)</b> The IFN signaling pathway (QIAGEN Ingenuity® Pathway Analysis) was overlaid with the day 3 post infection blood genes shown in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0150251#pone.0150251.g001" target="_blank">Fig 1A</a>. Genes (IFNαβ and JAK1) with opposite expression patterns between blood and spleen are highlighted with black circles. Red: upregulated, Blue: downregulated. <b>(B)</b> IFN response genes (type I, type II, and type I and II) associated with blood and spleen transcripts reported in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0150251#pone.0150251.g001" target="_blank">Fig 1A and 1B</a> and the Interferome database (<a href="http://www.interferome.org/" target="_blank">www.interferome.org</a>) were quantitated.</p

Validation of several IFN regulated genes by qRT-PCR.

<p><b>(A)</b> qRT-PCR validation of several IFN regulated genes identified in Figs <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0150251#pone.0150251.g004" target="_blank">4</a> and <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0150251#pone.0150251.g005" target="_blank">5</a>. Blood (left panel), spleen (middle panel) and liver (right panel) RNA was extracted at the indicated times post <i>L</i>. <i>monocytogenes</i> infection. RNA was reverse transcribed to cDNA, and expression of the indicated genes was analyzed by qRT-PCR. Values were normalized relative to <i>Hprt1</i> expression levels (mean with SD). Data are from one experiment with four mice per group. <b>(B)</b> Ly6C⁺ monocytes and pDC in blood and spleen of uninfected and infected WT and <i>Ifnar1</i>^<i>-/-</i> mice as a percentage of total live cells. Pooled results from 3 independent experiments, mean with SEM, n = 3 per group/experiment.</p

<i>Ifnar1</i>^-/- uninfected mice show a lowered expression of several IFN regulated genes as compared with WT uninfected mice.

<p><b>(A–C)</b> The strain-associated subsets of transcripts identified from the 2-way ANOVA as in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0150251#pone.0150251.g003" target="_blank">Fig 3B</a> for an independent experiment were filtered to identify baseline differences (fold-ratio of 1.5 between day 3 uninfected <i>Ifnar1</i>^<b>-/-</b> to day 3 uninfected WT mice) for blood, spleen and liver. Heatmaps and a list of top three IPA® canonical pathways are shown. <b>(D)</b> Venn diagram of above detailed transcripts identifies 50 transcripts that are commonly shared between blood, spleen and liver. These transcripts map to 35 genes in IPA® and include a number of Interferome-based type I IFN responsive genes that are marked in red. <b>(E)</b> Heatmap of mean-normalised expression values for selected (<i>Irf1</i>, <i>Irf3</i>, <i>Irf7</i>, <i>Irf9</i>, <i>Stat1</i> and <i>Stat2</i>) IFN transcriptional regulator transcripts. <b>(F)</b> qRT-PCR validation of <i>Irf7</i> gene normalized relative to <i>Hprt1</i> gene in blood (left panel), spleen (middle panel) and liver (right panel) at indicated times post infection (mean with SD). Data from one experiment with four mice per group.</p

Canonical pathways associated with blood transcripts that are differentially expressed in <i>L</i>. <i>monocytogenes</i> infected <i>Ifnar1</i>^-/- versus WT mice against control uninfected <i>Ifnar1</i>^-/- mice.

<p>Top IPA® canonical pathways that are associated with differentially expressed blood day 1, day 2 and day 3 transcripts from <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0150251#pone.0150251.g003" target="_blank">Fig 3B</a> and pass a further 1.5-fold change filter ratio between <b>(A)</b> WT infected to KO uninfected; <b>(B)</b> KO infected to KO uninfected; and <b>(C)</b> (KO infected to KO uninfected) as compared to (WT infected to KO uninfected). Percent pathway modulation relative to each dataset and pathway size is indicated in red for up-regulated and blue for down-regulated genes. Pathway rank for pathways passing <i>p<0</i>.<i>05</i> after Fisher’s Exact test at each time-point is marked. <b>(D and E)</b> Detailed heat map of differentially expressed genes found in the <b>(D)</b> Interferon Signaling Pathway; and <b>(E)</b> Antigen Presentation Pathway.</p