Protein Kinase PKR Mediates the Apoptosis Induction and Growth Restriction Phenotypes of C Protein-Deficient Measles Virus

The measles virus (MV) accessory proteins V and C play important roles in MV replication and pathogenesis. Infection with recombinant MV lacking either V or C causes more cell death than infection with the parental vaccine-equivalent virus (MVvac), and C-deficient virus grows poorly relative to the parental virus. Here, we show that a major effector of the C phenotype is the RNA-dependent protein kinase PKR. Using human HeLa cells stably deficient in PKR as a result of RNA interference-mediated knockdown (PKR^kd cells), we demonstrated that a reduction in PKR partially rescued the growth defect of C knockout (C^ko) virus but had no effect on the growth of either wild-type (WT) or V knockout (V^ko) virus. Increased growth of the C^ko virus in PKR^kd cells correlated with increased viral protein expression, while defective growth and decreased protein expression in PKR-sufficient cells correlated with increased phosphorylation of PKR and the α subunit of eukaryotic initiation factor 2. Furthermore, infection with WT, V^ko, or especially C^ko virus caused significantly less apoptosis in PKR^kd cells than in PKR-sufficient cells. Although apoptosis induced by C^ko virus infection in PKR-sufficient cells was blocked by a caspase antagonist, the growth of C^ko virus was not restored to the WT level by treatment with this pharmacologic inhibitor. Taken together, these results indicate that PKR plays an important antiviral role during MV infection but that the virus growth restriction by PKR is not dependent upon the induction of apoptosis. Furthermore, the results establish that a principal function of the MV C protein is to antagonize the proapoptotic and antiviral activities of PKR.     

Genome-wide analysis of the SET DOMAIN GROUP family in grapevine

The SET DOMAIN GROUP (SDG) proteins represent an evolutionarily-conserved family of epigenetic regulators present in eukaryotes and are putative candidates for the catalysis of lysine methylation in histones. Plant genomes analyses of this family have been performed in arabidopsis, maize, and rice and functional studies have shown that SDG genes are involved in the control of plant development. In this work, we describe the identification and structural characterization of SDG genes in the Vitis vinifera genome. This analysis revealed the presence of 33 putative SDG genes that can be grouped into different classes, as it has been previously described for plants. In addition to the SET domain, the proteins identified possessed other domains in the different classes. As part of our study regarding the growth and development of grapevine, we selected eight genes and their expression levels were analyzed in representative vegetative and reproductive organs of this species. The selected genes showed different patterns of expression during inflorescence and fruit development, suggesting that they participate in these processes. Furthermore, we showed that the expression of selected SDGs changes during viral infection, using as a model Grapevine Leafroll Associated Virus 3-infected symptomatic grapevine leaves and fruits. Our results suggest that developmental changes caused by this virus could be the result of alterations in SDG expression.     

Modelling the effect of forest cover on shallow landslides at the river basin scale

The potential for reducing the occurrence of shallow landslides through targeted reforestation of critical parts of a river basin is explored through mathematical modelling. Through the systematic investigation of land management options, modelling allows the optimum strategies to be selected ahead of any real intervention in the basin. Physically based models, for which the parameters can be evaluated using physical reasoning, offer particular advantages for predicting the effects of possible future changes in land use and climate. Typically a physically based landslide model consists of a coupled hydrological model (for soil moisture) and a geotechnical slope stability model, along with an impact model, such as basin sediment yield. An application of the SHETRAN model to the 65.8-km² Guabalcón basin in central Ecuador demonstrates a technique for identifying the areas of a basin most susceptible to shallow landsliding and for quantifying the effects of different vegetation covers on landslide incidence. Thus, for the modelled scenario, increasing root cohesion from 300 to 1500 Pa causes a two-thirds reduction in the number of landslides. Useful information can be obtained even on the basis of imperfect data availability but model output should be interpreted carefully in the light of parameter uncertainty.     

Analysis and visualization of H7 influenza using genomic,evolutionary and geographic information in a modular web service

We have reported previously on use of a web‐based application, Supramap ( http://supramap.org ) for the study of biogeographic, genotypic, and phenotypic evolution. Using Supramap we have developed maps of the spread of drug‐resistant influenza and host shifts in H1N1 and H5N1 influenza and coronaviruses such as SARS. Here we report on another zoonotic pathogen, H7 influenza, and provide an update on the implementation of Supramap as a web service. We find that the emergence of pathogenic strains of H7 is labile with many transitions from high to low pathogenicity, and from low to high pathogenicity. We use Supramap to put these events in a temporal and geospatial context. We identify several lineages of H7 influenza with biomarkers of high pathogenicity in regions that have not been reported in the scientific literature. The original implementation of Supramap was built with tightly coupled client and server software. Now we have decoupled the components to provide a modular web service for POY ( http://poyws.org ) that can be consumed by a data provider to create a novel application. To demonstrate the web service, we have produced an application, Geogenes ( http://geogenes.org ). Unlike in Supramap, in which the user is required to create and upload data files, in Geogenes the user works from a graphical interface to query an underlying dataset. Geogenes demonstrates how the web service can provide underlying processing for any sequence and metadata database. © The Willi Hennig Society 2012.     

The Macrophage Inhibitor CNI-1493 Blocks Metastasis in a Mouse Model of Ewing Sarcoma through Inhibition of Extravasation

Metastatic Ewing Sarcoma carries a poor prognosis, and novel therapeutics to prevent and treat metastatic disease are greatly needed. Recent evidence demonstrates that tumor-associated macrophages in Ewing Sarcoma are associated with more advanced disease. While some macrophage phenotypes (M1) exhibit anti-tumor activity, distinct phenotypes (M2) may contribute to malignant progression and metastasis. In this study, we show that M2 macrophages promote Ewing Sarcoma invasion and extravasation, pointing to a potential target of anti-metastatic therapy. CNI-1493 is a selective inhibitor of macrophage function and has shown to be safe in clinical trials as an anti-inflammatory agent. In a xenograft mouse model of metastatic Ewing Sarcoma, CNI-1493 treatment dramatically reduces metastatic tumor burden. Furthermore, metastases in treated animals have a less invasive morphology. We show in vitro that CNI-1493 decreases M2-stimulated Ewing Sarcoma tumor cell invasion and extravasation, offering a functional mechanism through which CNI-1493 attenuates metastasis. These data indicate that CNI-1493 may be a safe and effective adjuvant agent for the prevention and treatment of metastatic Ewing Sarcoma.     

A Temporally Explicit Production Efficiency Model for Fuel Load Allocation in Southern Africa

Abstract We present a regional fuel load model (1 km² spatial resolution) applied in the southern African savanna region. The model is based on a patch-scale production efficiency model (PEM) scaled up to the regional level using empirical relationships between patch-scale behavior and multi-source remote sensing data (spatio-temporal variability of vegetation and climatic variables). The model requires the spatial distribution of woody vegetation cover, which is used to determine separate respiration rates for tree and grass. Net primary production, grass and tree leaf death, and herbivory are also taken into account in this mechanistic modeling approach. The fuel load model has been calibrated and validated from independent measurements taken from savanna vegetation in Africa southward from the equator. A sensitivity analysis on the effect of climate variables (incoming radiation, air temperature, and precipitation) has been conducted to demonstrate the strong role that water availability has in determining productivity and subsequent fuel load over the southern African region. The model performance has been tested in four different areas representative of a regional increasing rainfall gradient—Etosha National Park, Namibia, Mongu and Kasama, Zambia, as well as in Kruger National Park, South Africa. Within each area, we analyze model output from three different magnitudes of canopy coverage (<5, 30, and 50%). We find that fuel load ranges predicted by the model are globally in agreement with field measurements for the same year. High rainfall sustains green herbaceous production late in the dry season and delays tree leaf litter production. Effect of water on production varies across the rainfall gradient with delayed start of green material production in more arid regions.