Mast cells supported productive replication of influenza A viruses.

<p>P815 cells were mock-treated or infected with the three subtypes of influenza viruses at an equal MOI of 0.1 for the periods specified. Culture supernatants were collected, and total viral protein quantification and viral titers were determined using a (A) hemagglutination (HA) assay and (B) standard plaque assay. (C) Cells were homogenized in Trizol and relative viral NS1 gene quantification was determined using real time PCR. The results shown here were pooled from three independent replicates.</p

Apoptosis was induced in influenza A viruses infected P815 cells.

<p>P815 cells were mock-treated or infected with H1N1, H5N1, or H7N2 at an MOI of 0.1 for 12 h. (A) Transmission electron microscopy showed ultrastructure of mock-treated and virus-infected cells. (B) A TUNEL assay was used to measure apoptosis in P815 cells using DNase as a positive control. Blue indicates nuclear staining and green indicates positive TUNEL staining due to the presence of apoptosis. The results shown here are representative of three different donors.</p

Caspase inhibitors suppressed the apoptosis in P815 cells infected with influenza A virus.

<p>VAD (abbreviation of Z-VAD-fmk, pan-caspase inhibitor), IETD (abbreviation of Z-IETD-fmk, caspase-8 inhibitor), and LEHD (abbreviation of Z-LEHD-fmk, caspase-9 inhibitor) were added before and after infection with influenza A viruses, and P815 cells were harvested 24 h after infection. (A) Apoptosis was quantified using flow cytometric analysis. Asterisks indicate that the inhibitor-incubated groups were statistically significantly different from the DMSO-incubated groups, as indicated by ANOVA. (B) The expression of full-length and cleaved PARP in P815 cells was measured using Western blot analysis. Graphs show results of one representative case (out of three).</p

GroupRank: Rank Candidate Genes in PPI Network by Differentially Expressed Gene Groups

<div><p>Many cell activities are organized as a network, and genes are clustered into co-expressed groups if they have the same or closely related biological function or they are co-regulated. In this study, based on an assumption that a strong candidate disease gene is more likely close to gene groups in which all members coordinately differentially express than individual genes with differential expression, we developed a novel disease gene prioritization method GroupRank by integrating gene co-expression and differential expression information generated from microarray data as well as PPI network. A candidate gene is ranked high using GroupRank if it is differentially expressed in disease and control or is close to differentially co-expressed groups in PPI network. We tested our method on data sets of lung, kidney, leukemia and breast cancer. The results revealed GroupRank could efficiently prioritize disease genes with significantly improved AUC value in comparison to the previous method with no consideration of co-exprssed gene groups in PPI network. Moreover, the functional analyses of the major contributing gene group in gene prioritization of kidney cancer verified that our algorithm GroupRank not only ranks disease genes efficiently but also could help us identify and understand possible mechanisms in important physiological and pathological processes of disease.</p></div

Inhibition of apoptosis suppressed the viral replication and release of pro-inflammatory cytokines and chemokines.

<p>P815 cells were treated as described in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0100109#pone-0100109-g004" target="_blank">Figure 4</a>. Cell supernatants were harvested 24 h after infection. (A) Viral titers were determined using a standard plaque assay. Results shown were pooled from three independent repeats. (B) Expression levels of IL-1β, IL-6, IL-18, TNF-α, TGF-β1, IFN-γ, and MCP-1 were analyzed using ELISA. Statistically significant differences between the inhibitor-treated groups and corresponding DMSO controls are indicated by * (<i>P</i><0.05) and ** (<i>P</i><0.01). Results shown are pooled from three independent repeats. ND, not detectable.</p

Apoptosis of P815 cells was further measured at specified times after influenza A virus infection.

<p>P815 cells were treated or infected as described in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0100109#pone-0100109-g001" target="_blank">Figure 1</a> and harvested at 6 h, 12 h, and 24 h post-infection. (A) Quantification of the total number of apoptotic cells (early and late-stage apoptosis) by flow cytometric analysis with Taxol as a positive control. Asterisks indicate statistically significantly higher values than among mock-treated cells (*<i>P</i><0.05 and **<i>P</i><0.01). (B) Immunoblotting analysis of the expression levels of apoptosis-associated proteins, caspase 3, caspase 8, caspase 9, Apaf-1, Bcl-2, and Bcl-xL, with β-actin as a loading control. (C) Immunoblotting analysis of the cytosolic and mitochondrial Cyt C expression after fractionation. α-Tubulin and cytochrome oxidase subunit IV (Cox IV) were used as specific markers for the cytosolic and mitochondrial fractionations, respectively. Shown here are representative results of three separate experiments.</p

MRR of GroupRank in four cancer types.

<p>MRR of GroupRank in four cancer types.</p

Schematic graph of gene ranking of kidney cancer using GroupRank.

<p>The graph illustrates gene ranking of kidney cancer using the algorithm GroupRank. The triangle nodes at the top represent known kidney cancer genes and the square nodes at the bottom represent the top 20 ranked genes of kidney cancer using GroupRank. The circle nodes in middle represent the co-expressed gene groups used to rank disease gene candidates. A known or putative cancer gene is connected with a gene group if it contributes more than 5% of the summed ranking score of this cancer gene. The width of the edge linked to a disease gene is proportional to the scoring contribution obtained from the corresponding gene group. The edges explaining more than 20% of the ranking score of the cancer gene candidate are highlighted in dark blue. The edge is colored in light blue if the scoring contribution of the gene group is from 15% to 20%. The darker node color indicates higher fold change at expression level in cancer and normal control. The size of the circle node representing gene group was proportional to its accumulated contribution in ranking scores of all known kidney cancer genes. The enriched functional annotation is labeled on each of the four major contributing gene groups.</p

MRR Comparisons of GroupRank using co-expressed and random groups.

<p>The red sign represents MRR of GroupRank using co-expressed gene groups in four cancers. Boxplots show the distributions of MRRs using random groups of the same size. The random sampling was repeated 1000 times in each cancer type.</p

Mean rank ratio of GroupRank using different distance thresholds.

<p>The gene groups in GroupRank are partitioned based on a distance threshold with a gradient from 0.1 to 0.9. From A to D, the cancer types are lung cancer, kidney cancer, leukemia and breast cancer.</p