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.     

Influence of rainfall on sleeping site choice by a group of anubis baboons (Papio anubis)

For diurnal nonhuman primates, shifting among different sleeping sites may provide multiple benefits such as better protection from predators, reduced risk of parasitic infection, and closer proximity to spatially and temporally heterogeneous food and water. This last benefit may be particularly important in sleeping site selection by primates living in savanna‐woodlands where rainfall is more limited and more seasonally pronounced than in rainforests. Here, we examined the influence of rainfall, a factor that affects food and water availability, on the use of sleeping sites by anubis baboons (Papio anubis) over two 13‐month study periods that differed in rainfall patterns. We predicted that during wet periods, when food and water availability should be higher, the study group would limit the number of sleeping sites and would stay at each one for more consecutive nights than during dry periods. Conversely, we predicted that during dry periods the group would increase the number of sleeping sites and stay at each one for fewer consecutive nights as they searched more widely for food and water. We also predicted that the group would more often choose sleeping sites closer to the center of the area used during daytime (between 07:00 and 19:00) during wet months than during dry months. Using Global Positioning System data from collared individuals, we found that our first prediction was not supported on either monthly or yearly timescales, although past monthly rainfall predicted the use of the main sleeping site in the second study period. Our second prediction was supported only on a yearly timescale. This study suggests that baboons’ choice of sleeping sites is fluid over time while being sensitive to local environmental conditions, one of which may be rainfall.     

Noni as an anxiolytic and sedative: A mechanism involving its gamma-aminobutyric acidergic effects

Noni (Morinda citrifolia) is increasing in worldwide popularity as a food or dietary supplement with versatile health benefits. The aim of this study was to investigate the effects of Noni fruit on anxiety symptoms in vitro. To this end, a competitive GABAa receptor-binding assay was developed. Our preliminary study indicates that the methanol crude extract of Noni fruit showed significant affinity to the gamma-aminobutyric acid A (GABAa) inhibitory neurotransmitter receptors, and displayed 75% binding inhibition of the agonist radioligand [3H] muscimol at a concentration of 100 microg/ml. Further experiments demonstrated that the MeOH extract, and its BuOH and H2O partitions, exhibited IC50 values of 22.8, 27.2, and 17.1 microg/ml, respectively, in the GABAa-binding assay. Experimental results with Noni fruit indicate the presence of competitive ligand(s), which may bind to the GABAa receptor as an agonist, and thus induce its anxiolytic and sedative effects. The study provides an in vitro rationale for one of Noni's versatile and traditional uses. In addition, an HPLC fingerprint profile of the methanolic extract of Noni fruit has been established for quality control purpose.     

EPR Monitored Redox Titration of the Cofactors of Saccharomyces cerevisiae Nar1

Electron Paramagnetic Resonance (EPR) monitored redox titrations are a powerful method to determine the midpoint potential of cofactors in proteins and to identify and quantify the cofactors in their detectable redox state.The technique is complementary to direct electrochemistry (voltammetry) approaches, as it does not offer information on electron transfer rates, but does establish the identity and redox state of the cofactors in the protein under study. The technique is widely applicable to any protein containing an electron paramagnetic resonance (EPR) detectable cofactor.A typical titration requires 2 ml protein with a cofactor concentration in the range of 1-100 µM. The protein is titrated with a chemical reductant (sodium dithionite) or oxidant (potassium ferricyanide) in order to poise the sample at a certain potential. A platinum wire and a Ag/AgCl reference electrode are connected to a voltmeter to measure the potential of the protein solution. A set of 13 different redox mediators is used to equilibrate between the redox cofactors of the protein and the electrodes. Samples are drawn at different potentials and the Electron Paramagnetic Resonance spectra, characteristic for the different redox cofactors in the protein, are measured. The plot of the signal intensity versus the sample potential is analyzed using the Nernst equation in order to determine the midpoint potential of the cofactor.