Carbon Stocks in an African Woodland Landscape: Spatial Distributions and Scales of Variation

Current knowledge of Africa’s carbon (C) pools is limited despite its importance in the global C budget. To increase the understanding of C stocks in African woodlands, we asked how C stocks in soil and vegetation vary across a miombo woodland landscape and to what degree and at what scales are these stocks linked? We sampled along a 5-km transect using a cyclic sampling scheme to allow geostatistical analyses. Soil C stocks in the top 5?cm (12.1?±?0.6?Mg?C?ha^?1 (±?SE)) and 30?cm depths (40.1?±?2.5?Mg?C?ha^?1) varied significantly at scales of a few meters (autocorrelation distance 14?m in 0–5-cm and 26?m in 0–30-cm interval), and aboveground (AG) woody C stocks (20.7?±?1.8?Mg?C?ha^?1) varied significantly at kilometer scales (1,426?m). Soil textural distributions were linked to topography (r ²?=?0.54) as were large-tree AG C stocks (r ²?=?0.70). AG C stocks were constrained to an upper boundary by soil texture with greater AG C being associated with coarser textured soils. Vegetation and soil C stocks were coupled in the landscape in the top 5?cm of soil (r ²?=?0.24) but not with deeper soil C stocks, which were coupled to soil clay content (r ²?=?0.38). This study is one of the most complete transect studies in an African miombo woodland, and suggests that C stock distributions are strongly linked to topography and soil texture. To optimize sampling strategies for C stock assessments in miombo, soil C should be sampled at more than 26?m apart, and AG C should be sampled at more than 1,426?m apart in plots larger than 0.5?ha.     

Membrane bending by protein-protein crowding

Curved membranes are an essential feature of dynamic cellular structures, including endocytic pits, filopodia protrusions and most organelles. It has been proposed that specialized proteins induce curvature by binding to membranes through two primary mechanisms: membrane scaffolding by curved proteins or complexes; and insertion of wedge-like amphipathic helices into the membrane. Recent computational studies have raised questions about the efficiency of the helix-insertion mechanism, predicting that proteins must cover nearly 100% of the membrane surface to generate high curvature, an improbable physiological situation. Thus, at present, we lack a sufficient physical explanation of how protein attachment bends membranes efficiently. On the basis of studies of epsin1 and AP180, proteins involved in clathrin-mediated endocytosis, we propose a third general mechanism for bending fluid cellular membranes: protein-protein crowding. By correlating membrane tubulation with measurements of protein densities on membrane surfaces, we demonstrate that lateral pressure generated by collisions between bound proteins drives bending. Whether proteins attach by inserting a helix or by binding lipid heads with an engineered tag, protein coverage above ~20% is sufficient to bend membranes. Consistent with this crowding mechanism, we find that even proteins unrelated to membrane curvature, such as green fluorescent protein (GFP), can bend membranes when sufficiently concentrated. These findings demonstrate a highly efficient mechanism by which the crowded protein environment on the surface of cellular membranes can contribute to membrane shape change.     

Ancestral polymorphism at the major histocompatibility complex (MHCIIbeta) in the Nesospiza bunting species complex and its sister species (Rowettia goughensis)

ABSTRACT: BACKGROUND: The major histocompatibility complex (MHC) is an important component of the vertebrate immune system and is frequently used to characterise adaptive variation in wild populations due to its co-evolution with pathogens. Passerine birds have an exceptionally diverse MHC with multiple gene copies and large numbers of alleles compared to other avian taxa. The Nesospiza bunting species complex (two species on Nightingale Island; one species with three sub-species on Inaccessible Island) represents a rapid adaptive radiation at a small, isolated archipelago, and is thus an excellent model for the study of adaptation and speciation. In this first study of MHC in Nesospiza buntings, we aim to characterize MHCIIbeta variation, determine the strength of selection acting at this gene region and assess the level of shared polymorphism between the Nesospiza species complex and its putative sister taxon, Rowettia goughensis, from Gough Island. RESULTS: In total, 23 unique alleles were found in 14 Nesospiza and 2 R. goughensis individuals encoding at least four presumably functional loci and two pseudogenes. There was no evidence of ongoing selection on the peptide binding region (PBR). Of the 23 alleles, 15 were found on both the islands inhabited by Nesospiza species, and seven in both Nesospiza and Rowettia; indications of shared, ancestral polymorphism. A gene tree of Nesospiza MHCIIbeta alleles with several other passerine birds shows three highly supported Nesospiza-specific groups. All R. goughensis alleles were shared with Nesospiza, and these alleles were found in all three Nesospiza sequence groups in the gene tree, suggesting that most of the observed variation predates their phylogenetic split. CONCLUSIONS: Lack of evidence of selection on the PBR, together with shared polymorphism across the gene tree, suggests that population variation of MHCIIbeta among Nesospiza and Rowettia is due to ancestral polymorphism rather than local selective forces. Weak or no selection pressure could be attributed to low parasite load at these isolated Atlantic islands. The deep divergence between the highly supported Nesospiza-specific sequence Groups 2 and 3, and the clustering of Group 3 close to the distantly related passerines, provide strong support for preserved ancestral polymorphism, and present evidence of one of the rare cases of extensive ancestral polymorphism in birds.     

Electron microscopy visualization of DNA-protein complexes formed by Ku and DNA ligase IV

The repair of DNA double-stranded breaks (DSBs) is essential for cell viability and genome stability. Aberrant repair of DSBs has been linked with cancer predisposition and aging. During the repair of DSBs by non-homologous end joining (NHEJ), DNA ends are brought together, processed and then joined. In eukaryotes, this repair pathway is initiated by the binding of the ring-shaped Ku heterodimer and completed by DNA ligase IV. The DNA ligase IV complex, DNA ligase IV/XRRC4 in humans and Dnl4/Lif1 in yeast, is recruited to DNA ends in vitro and in vivo by an interaction with Ku and, in yeast, Dnl4/Lif1 stabilizes the binding of yKu to in vivo DSBs. Here we have analyzed the interactions of these functionally conserved eukaryotic NHEJ factors with DNA by electron microscopy. As expected, the ring-shaped Ku complex bound stably and specifically to DNA ends at physiological salt concentrations. At a ratio of 1 Ku molecule per DNA end, the majority of DNA ends were occupied by a single Ku complex with no significant formation of linear DNA multimers or circular loops. Both Dnl4/Lif1 and DNA ligase IV/XRCC4 formed complexes with Ku-bound DNA ends, resulting in intra- and intermolecular DNA end bridging, even with non-ligatable DNA ends. Together, these studies, which provide the first visualization of the conserved complex formed by Ku and DNA ligase IV at juxtaposed DNA ends by electron microscopy, suggest that the DNA ligase IV complex mediates end-bridging by engaging two Ku-bound DNA ends.     

Autonomic Shutdown of Lithium‐Ion Batteries Using Thermoresponsive Microspheres

Autonomic, thermally‐induced shutdown of Lithium‐ion (Li‐ion) batteries is demonstrated by incorporating thermoresponsive polymer microspheres (ca. 4 μm) onto battery anodes or separators. When the internal battery environment reaches a critical temperature, the microspheres melt and coat the anode/separator with a nonconductive barrier, halting Li‐ion transport and shutting down the cell permanently. Three functionalization schemes are shown to perform cell shutdown: 1) poly(ethylene) (PE) microspheres coated on the anode, 2) paraffin wax microspheres coated on the anode, and 3) PE microspheres coated on the separator. Charge and discharge capacity is measured for Li‐ion coin cells containing microsphere‐coated anodes or separators as a function of capsule coverage. For PE coated on the anode, the initial capacity of the battery is unaffected by the presence of the PE microspheres up to a coverage of 12 mg cm^?2 (when cycled at 1C), and full shutdown (>98% loss of initial capacity) is achieved in cells containing greater than 3.5 mg cm^?2. For paraffin microspheres coated on the anode and PE microspheres coated on the separator, shutdown is achieved in cells containing coverages greater than 2.9 and 13.7 mg cm^?2, respectively. Scanning electron microscopy images of electrode surfaces from cells that have undergone autonomic shutdown provides evidence of melting, wetting, and resolidification of PE into the anode and polymer film formation at the anode/separator interface.     

Foraging behavior and prey of sea otters in a soft- and mixed-sediment benthos in Alaska

Sea otter (Enhydra lutris kenyoni) foraging behavior and prey preference were studied from June to August 2001–2004 in Simpson Bay, Prince William Sound, Alaska. The study area has an average water depth of 30 m and a benthos primarily of soft- and mixed-sediment with no canopy-forming kelps. A total of 1816 foraging dives from 211 bouts were recorded. Overall, dives ranged in depth from <5 to 82 m; most dives were less than 15 m (40%) with smaller, secondary peaks at 25–30 m (10%) and 50–55 m (7%). Average dive depth and duration were 27 m ± 19.5 and 1.89 min ± 0.88, respectively. Dive durations were all significantly different: male > unknown > female. Dive depths reflected the bathymetry (percentage of the bay within a depth range) of Simpson Bay but favored shallow areas. 87% of foraging dives were successful, and 44% of the prey was positively identified: 75% clams, 9% Pacific blue mussels, 6% crabs, 2% Reddish scallops and a variety of other invertebrates. There was no evidence for prey specialization among the sexes. Although sea otters in Simpson Bay rely heavily on bivalves, their diet has remained unchanged for the past 18 years, and the minimum summer population has been constant for at least the past nine years. It appears that bivalves are the predominant and stable component of the diet, and their productivity is sufficient to sustain a stable population of sea otters with a minimum peak summer density of 4.3 adult otters km^?2 and an average annual density of ca. 2.9 adult otters km^?2 for the past nine years and probably longer.     

Simultaneous analysis of multiple data types in pharmacogenomic studies using weighted sparse canonical correlation analysis

Variation in drug response results from a combination of factors that include differences in gender, ethnicity, and environment, as well as genetic variation that may result in differences in mRNA and protein expression. This article presents two integrative analytic approaches that make use of both genome-wide SNP and mRNA expression data available on the same set of subjects: a step-wise integrative approach and a comprehensive analysis using sparse canonical correlation analysis (SCCA). In addition to applying standard SCCA, we present a novel modification of SCCA which allows different weighting for the various pair-wise relationships in the SCCA. These integrative approaches are illustrated with both simulated data and data from a pharmacogenomic study of the drug gemcitabine. Results from these analyses found little overlap in terms of genes detected, possibly detecting different biological mechanisms. In addition, we found the proposed weighted SCCA to outperform its unweighted counterpart in detecting associations between the genomic features and phenotype. Further research is needed to develop and assess new integrative methods for pharmacogenomic studies, as these types of analyses may uncover novel insights into the relationship between genomic variation and drug response.     

Automatic segmentation and supervised learning-based selection of nuclei in cancer tissue images

Analysis of preferential localization of certain genes within the cell nuclei is emerging as a new technique for the diagnosis of breast cancer. Quantitation requires accurate segmentation of 100-200 cell nuclei in each tissue section to draw a statistically significant result. Thus, for large-scale analysis, manual processing is too time consuming and subjective. Fortuitously, acquired images generally contain many more nuclei than are needed for analysis. Therefore, we developed an integrated workflow that selects, following automatic segmentation, a subpopulation of accurately delineated nuclei for positioning of fluorescence in situ hybridization-labeled genes of interest. Segmentation was performed by a multistage watershed-based algorithm and screening by an artificial neural network-based pattern recognition engine. The performance of the workflow was quantified in terms of the fraction of automatically selected nuclei that were visually confirmed as well segmented and by the boundary accuracy of the well-segmented nuclei relative to a 2D dynamic programming-based reference segmentation method. Application of the method was demonstrated for discriminating normal and cancerous breast tissue sections based on the differential positioning of the HES5 gene. Automatic results agreed with manual analysis in 11 out of 14 cancers, all four normal cases, and all five noncancerous breast disease cases, thus showing the accuracy and robustness of the proposed approach. ? Published 2012 Wiley Periodicals, Inc.