Dengue Virus Inhibits Immune Responses in Aedes aegypti Cells

The ability of many viruses to manipulate the host antiviral immune response often results in complex host-pathogen interactions. In order to study the interaction of dengue virus (DENV) with the Aedes aegypti immune response, we have characterized the DENV infection-responsive transcriptome of the immune-competent A. aegypti cell line Aag2. As in mosquitoes, DENV infection transcriptionally activated the cell line Toll pathway and a variety of cellular physiological systems. Most notably, however, DENV infection down-regulated the expression levels of numerous immune signaling molecules and antimicrobial peptides (AMPs). Functional assays showed that transcriptional induction of AMPs from the Toll and IMD pathways in response to bacterial challenge is impaired in DENV-infected cells. In addition, Escherichia coli, a Gram-negative bacteria species, grew better when co-cultured with DENV-infected cells than with uninfected cells, suggesting a decreased production of AMPs from the IMD pathway in virus-infected cells. Pre-stimulation of the cell line with Gram-positive bacteria prior to DENV infection had no effect on DENV titers, while pre-stimulation with Gram-negative bacteria resulted in an increase in DENV titers. These results indicate that DENV is capable of actively suppressing immune responses in the cells it infects, a phenomenon that may have important consequences for virus transmission and insect physiology

Human Papillomavirus-16 E7 Interacts with Glutathione S-Transferase P1 and Enhances Its Role in Cell Survival

Background:Human Papillomavirus (HPV)-16 is a paradigm for "high-risk" HPVs, the causative agents of virtually all cervical carcinomas. HPV E6 and E7 viral genes are usually expressed in these tumors, suggesting key roles for their gene products, the E6 and E7 oncoproteins, in inducing malignant transformation.Methodology/Principal Findings:By protein-protein interaction analysis, using mass spectrometry, we identified glutathione S-transferase P1-1 (GSTP1) as a novel cellular partner of the HPV-16 E7 oncoprotein. Following mapping of the region in the HPV-16 E7 sequence that is involved in the interaction, we generated a three-dimensional molecular model of the complex between HPV-16 E7 and GSTP1, and used this to engineer a mutant molecule of HPV-16 E7 with strongly reduced affinity for GSTP1.When expressed in HaCaT human keratinocytes, HPV-16 E7 modified the equilibrium between the oxidized and reduced forms of GSTP1, thereby inhibiting JNK phosphorylation and its ability to induce apoptosis. Using GSTP1-deficient MCF-7 cancer cells and siRNA interference targeting GSTP1 in HaCaT keratinocytes expressing either wild-type or mutant HPV-16 E7, we uncovered a pivotal role for GSTP1 in the pro-survival program elicited by its binding with HPV-16 E7.Conclusions/Significance:This study provides further evidence of the transforming abilities of this oncoprotein, setting the groundwork for devising unique molecular tools that can both interfere with the interaction between HPV-16 E7 and GSTP1 and minimize the survival of HPV-16 E7-expressing cancer cells. © 2009 Mileo et al

Bridging a yawning chasm: EEG investigations into the debate concerning the role of the human mirror neuron system in contagious yawning

Ongoing debate in the literature concerns whether there is a link between contagious yawning and the human mirror neuron system (hMNS). One way of examining this issue is with the use of the electroencephalogram (EEG) to measure changes in mu activation during the observation of yawns. Mu oscillations are seen in the alpha bandwidth of the EEG (8-12 Hz) over sensorimotor areas. Previous work has shown that mu suppression is a useful index of hMNS activation and is sensitive to individual differences in empathy. In two experiments, we presented participants with videos of either people yawning or control stimuli. We found greater mu suppression for yawns than for controls over right motor and premotor areas, particularly for those scoring higher on traits of empathy. In a third experiment, auditory recordings of yawns were compared against electronically scrambled versions of the same yawns. We observed greater mu suppression for yawns than for the controls over right lateral premotor areas. Again, these findings were driven by those scoring highly on empathy. The results from these experiments support the notion that the hMNS is involved in contagious yawning, emphasise the link between contagious yawning and empathy, and stress the importance of good control stimuli. © Psychonomic Society, Inc. 2011

The UEA small RNA workbench:A suite of computational tools for small RNA analysis

RNA silencing (RNA interference, RNAi) is a complex, highly conserved mechanism mediated by short, typically 20-24 nt in length, noncoding RNAs known as small RNAs (sRNAs). They act as guides for the sequence-specific transcriptional and posttranscriptional regulation of target mRNAs and play a key role in the fine-tuning of biological processes such as growth, response to stresses, or defense mechanism. High-throughput sequencing (HTS) technologies are employed to capture the expression levels of sRNA populations. The processing of the resulting big data sets facilitated the computational analysis of the sRNA patterns of variation within biological samples such as time point experiments, tissue series or various treatments. Rapid technological advances enable larger experiments, often with biological replicates leading to a vast amount of raw data. As a result, in this fast-evolving field, the existing methods for sequence characterization and prediction of interaction (regulatory) networks periodically require adapting or in extreme cases, a complete redesign to cope with the data deluge. In addition, the presence of numerous tools focused only on particular steps of HTS analysis hinders the systematic parsing of the results and their interpretation. The UEA small RNA Workbench (v1-4), described in this chapter, provides a user-friendly, modular, interactive analysis in the form of a suite of computational tools designed to process and mine sRNA datasets for interesting characteristics that can be linked back to the observed phenotypes. First, we show how to preprocess the raw sequencing output and prepare it for downstream analysis. Then we review some quality checks that can be used as a first indication of sources of variability between samples. Next we show how the Workbench can provide a comparison of the effects of different normalization approaches on the distributions of expression, enhanced methods for the identification of differentially expressed transcripts and a summary of their corresponding patterns. Finally we describe individual analysis tools such as PAREsnip, for the analysis of PARE (degradome) data or CoLIde for the identification of sRNA loci based on their expression patterns and the visualization of the results using the software. We illustrate the features of the UEA sRNA Workbench on Arabidopsis thaliana and Homo sapiens datasets