Association of the eukaryotic V1VO ATPase subunits a with d and d with A

AbstractOwing to the complex nature of V1VO ATPases, identification of neighboring subunits is essential for mechanistic understanding of this enzyme. Here, we describe the links between the V1 headpiece and the VO-domain of the yeast V1VO ATPase via subunit A and d as well as the VO subunits a and d using surface plasmon resonance and fluorescence correlation spectroscopy. Binding constants of about 60 and 200nM have been determined for the a–d and d–A assembly, respectively. The data are discussed in light of subunit a and d forming a peripheral stalk, connecting the catalytic A3B3 hexamer with VO.Structured summaryMINT-7012054: d (uniprotkb:P32366) binds (MI:0407) to A (uniprotkb:P17255) by fluorescence correlation spectroscopy (MI:0052)MINT-7012041: d (uniprotkb:P32366) binds (MI:0407) to A (uniprotkb:P17255) by surface plasmon resonance (MI:0107)MINT-7012028: d (uniprotkb:P32366) binds (MI:0407) to a (uniprotkb:P32563) by surface plasmon resonance (MI:0107

Structural Determination of Functional Units of the Nucleotide Binding Domain (NBD94) of the Reticulocyte Binding Protein Py235 of Plasmodium yoelii

Invasion of the red blood cells (RBC) by the merozoite of malaria parasites involves a large number of receptor ligand interactions. The reticulocyte binding protein homologue family (RH) plays an important role in erythrocyte recognition as well as virulence. Recently, it has been shown that members of RH in addition to receptor binding may also have a role as ATP/ADP sensor. A 94 kDa region named Nucleotide-Binding Domain 94 (NBD94) of Plasmodium yoelii YM, representative of the putative nucleotide binding region of RH, has been demonstrated to bind ATP and ADP selectively. Binding of ATP or ADP induced nucleotide-dependent structural changes in the C-terminal hinge-region of NBD94, and directly impacted on the RBC binding ability of RH.In order to find the smallest structural unit, able to bind nucleotides, and its coupling module, the hinge region, three truncated domains of NBD94 have been generated, termed NBD94(444-547), NBD94(566-663) and NBD94(674-793), respectively. Using fluorescence correlation spectroscopy NBD94(444-547) has been identified to form the smallest nucleotide binding segment, sensitive for ATP and ADP, which became inhibited by 4-Chloro-7-nitrobenzofurazan. The shape of NBD94(444-547) in solution was calculated from small-angle X-ray scattering data, revealing an elongated molecule, comprised of two globular domains, connected by a spiral segment of about 73.1 A in length. The high quality of the constructs, forming the hinge-region, NBD94(566-663) and NBD94(674-793) enabled to determine the first crystallographic and solution structure, respectively. The crystal structure of NBD94(566-663) consists of two helices with 97.8 A and 48.6 A in length, linked by a loop. By comparison, the low resolution structure of NBD94(674-793) in solution represents a chair-like shape with three architectural segments.These structures give the first insight into how nucleotide binding impacts on the overall structure of RH and demonstrates the potential use of this region as a novel drug target

Intensification of summer precipitation with shorter time-scales in Europe

While daily extreme precipitation intensities increase with global warming on average at approximately the same rate as the availability of water vapor (~7%/°C), a debated topic is whether sub-daily extremes increase more. Modelling at convection-permitting scales has been deemed necessary to reproduce extreme summer precipitation at local scale. Here we analyze multi-model ensembles and apply a 3 km horizontal resolution model over four regions across Europe (S. Norway, Denmark, Benelux and Albania) and find very good agreement with observed daily and hourly summer precipitation extremes. Projections show that daily extreme precipitation intensifies compared to the mean in all regions and across a wide range of models and resolutions. Hourly and 10 min extremes intensify at a higher rate in nearly all regions. Unlike most recent studies, we do not find sub-daily precipitation extremes increasing much more than 7%/°C, even for sub-hourly extremes, but this may be due to robust summer drying over large parts of Europe. However, the absolute strongest local daily precipitation event in a 20 year period will increase by 10%–20%/°C. At the same time, model projections strongly indicate that summer drying will be more pronounced for extremely dry years

Sea level variability in the Arctic Ocean from AOMIP models

Author Posting. © American Geophysical Union, 2007. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research 112 (2007): C04S08, doi:10.1029/2006JC003916.Monthly sea levels from five Arctic Ocean Model Intercomparison Project (AOMIP) models are analyzed and validated against observations in the Arctic Ocean. The AOMIP models are able to simulate variability of sea level reasonably well, but several improvements are needed to reduce model errors. It is suggested that the models will improve if their domains have a minimum depth less than 10 m. It is also recommended to take into account forcing associated with atmospheric loading, fast ice, and volume water fluxes representing Bering Strait inflow and river runoff. Several aspects of sea level variability in the Arctic Ocean are investigated based on updated observed sea level time series. The observed rate of sea level rise corrected for the glacial isostatic adjustment at 9 stations in the Kara, Laptev, and East Siberian seas for 1954–2006 is estimated as 0.250 cm/yr. There is a well pronounced decadal variability in the observed sea level time series. The 5-year running mean sea level signal correlates well with the annual Arctic Oscillation (AO) index and the sea level atmospheric pressure (SLP) at coastal stations and the North Pole. For 1954–2000 all model results reflect this correlation very well, indicating that the long-term model forcing and model reaction to the forcing are correct. Consistent with the influences of AO-driven processes, the sea level in the Arctic Ocean dropped significantly after 1990 and increased after the circulation regime changed from cyclonic to anticyclonic in 1997. In contrast, from 2000 to 2006 the sea level rose despite the stabilization of the AO index at its lowest values after 2000.This research is supported by the National Science Foundation Office of Polar Programs (under cooperative agreements OPP- 0002239 and OPP- 0327664) with the International Arctic Research Center, University of Alaska Fairbanks, and by the Climate Change Prediction Program of the Department of Energy’s Office of Biological and Environmental Research. The development of the UW model is also supported by NASA grants NNG04GB03G and NNG04GH52G and NSF grants OPP-0240916 and OPP-0229429

The Community Climate System Model version 4

Author Posting. © American Meteorological Society, 2011. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Journal of Climate 24 (2011): 4973–4991, doi:10.1175/2011JCLI4083.1.The fourth version of the Community Climate System Model (CCSM4) was recently completed and released to the climate community. This paper describes developments to all CCSM components, and documents fully coupled preindustrial control runs compared to the previous version, CCSM3. Using the standard atmosphere and land resolution of 1° results in the sea surface temperature biases in the major upwelling regions being comparable to the 1.4°-resolution CCSM3. Two changes to the deep convection scheme in the atmosphere component result in CCSM4 producing El Niño–Southern Oscillation variability with a much more realistic frequency distribution than in CCSM3, although the amplitude is too large compared to observations. These changes also improve the Madden–Julian oscillation and the frequency distribution of tropical precipitation. A new overflow parameterization in the ocean component leads to an improved simulation of the Gulf Stream path and the North Atlantic Ocean meridional overturning circulation. Changes to the CCSM4 land component lead to a much improved annual cycle of water storage, especially in the tropics. The CCSM4 sea ice component uses much more realistic albedos than CCSM3, and for several reasons the Arctic sea ice concentration is improved in CCSM4. An ensemble of twentieth-century simulations produces a good match to the observed September Arctic sea ice extent from 1979 to 2005. The CCSM4 ensemble mean increase in globally averaged surface temperature between 1850 and 2005 is larger than the observed increase by about 0.4°C. This is consistent with the fact that CCSM4 does not include a representation of the indirect effects of aerosols, although other factors may come into play. The CCSM4 still has significant biases, such as the mean precipitation distribution in the tropical Pacific Ocean, too much low cloud in the Arctic, and the latitudinal distributions of shortwave and longwave cloud forcings.National Science Foundation, which sponsors NCAR and the CCSM Project. The project is also sponsored by the U.S. Department of Energy (DOE). Thanks are also due to the many other software engineers and scientists who worked on developing CCSM4, and to the Computational and Information Systems Laboratory at NCAR, which provided the computing resources through the Climate Simulation Laboratory. Hunke was supported within theClimate, Ocean and Sea Ice Modeling project at Los Alamos National Laboratory, which is funded by the Biological and Environmental Research division of the DOE Office of Science. The Los Alamos National Laboratory is operated by theDOENationalNuclear Security Administration under Contract DE-AC52-06NA25396. Raschwas supported by theDOEOffice of Science, Earth System Modeling Program, which is part of the DOE Climate Change Research Program. The Pacific Northwest National Laboratory is operated forDOEbyBattelle Memorial Institute under Contract DE-AC06-76RLO 1830. Worley was supported by the Climate Change Research Division of the Office of Biological and Environmental Research and by the Office ofAdvanced Scientific Computing Research, both in the DOE Office of Science, under Contract DE-AC05-00OR22725 with UT-Batelle, LLC