Disruption of Intrinsic Motions as a Mechanism for Enzyme Inhibition

Clostridium difficile (C. diff) is one of the most common and most severe hospital-acquired infections; its consequences range from lengthened hospital stay to outright lethality. C. diff causes cellular damage through the action of two large toxins TcdA and TcdB. Recently, there has been increased effort toward developing antitoxin therapies, rather than antibacterial treatments, in hopes of mitigating the acquisition of drug resistance. To date, no analysis of the recognition mechanism of TcdA or TcdB has been attempted. Here, we use small molecule flexible docking followed by unbiased molecular dynamics to obtain a more detailed perspective on how inhibitory peptides, exemplified by two species HQSPWHH and EGWHAHT function. Using principal component analysis and generalized masked Delaunay analysis, an examination of the conformational space of TcdB in its apo form as well as forms bound to the peptides and UDP-Glucose was performed. Although both species inhibit by binding in the active site, they do so in two very different ways. The simulations show that the conformational space occupied by TcdB bound to the two peptides are quite different and provide valuable insight for the future design of toxin inhibitors and other enzymes that interact with their substrates through conformational capture mechanisms and thus work by the disruption of the protein’s intrinsic motions.     

Sampling Issues Affecting Accuracy of Likelihood-based Classification Using Genetical Data

We demonstrate the effectiveness of a genetic algorithm for discovering multi-locus combinations that provide accurate individual assignment decisions and estimates of mixture composition based on likelihood classification. Using simulated data representing different levels of inter-population differentiation (F_st～ 0.01 and 0.10), genetic diversities (four or eight alleles per locus), and population sizes (20, 40, 100 individuals in baseline populations), we show that subsets of loci can be identified that provide comparable levels of accuracy in classification decisions relative to entire multi-locus data sets, where 5, 10, or 20 loci were considered. Microsatellite data sets from hatchery strains of lake trout, Salvelinus namaycush, representing a comparable range of inter-population levels of differentiation in allele frequencies confirmed simulation results. For both simulated and empirical data sets, assignment accuracy was achieved using fewer loci (e.g., three or four loci out of eight for empirical lake trout studies). Simulation results were used to investigate properties of the ‘leave-one-out’ (L1O) method for estimating assignment error rates. Accuracy of population assignments based on L1O methods should be viewed with caution under certain conditions, particularly when baseline population sample sizes are low (<50).     

Cognition,behaviour and academic skills after cognitive rehabilitation in Ugandan children surviving severe malaria: a randomised trial

Background  

Infection with severe malaria in African children is associated with not only a high mortality but also a high risk of cognitive deficits. There is evidence that interventions done a few years after the illness are effective but nothing is known about those done immediately after the illness. We designed a study in which children who had suffered from severe malaria three months earlier were enrolled into a cognitive intervention program and assessed for the immediate benefit in cognitive, academic and behavioral outcomes.     

Accounting for Carbon Flux to Mycorrhizal Fungi May Resolve Discrepancies in Forest Carbon Budgets

Ecosystems - Carbon (C) fluxes among different components of plant growth are important to forest ecosystem C cycling and are strongly influenced by species composition and resource availability....     

Reforestation and surface cooling in temperate zones: Mechanisms and implications

Land‐use/cover change (LUCC) is an important driver of environmental change, occurring at the same time as, and often interacting with, global climate change. Reforestation and deforestation have been critical aspects of LUCC over the past two centuries and are widely studied for their potential to perturb the global carbon cycle. More recently, there has been keen interest in understanding the extent to which reforestation affects terrestrial energy cycling and thus surface temperature directly by altering surface physical properties (e.g., albedo and emissivity) and land–atmosphere energy exchange. The impacts of reforestation on land surface temperature and their mechanisms are relatively well understood in tropical and boreal climates, but the effects of reforestation on warming and/or cooling in temperate zones are less certain. This study is designed to elucidate the biophysical mechanisms that link land cover and surface temperature in temperate ecosystems. To achieve this goal, we used data from six paired eddy‐covariance towers over co‐located forests and grasslands in the temperate eastern United States, where radiation components, latent and sensible heat fluxes, and meteorological conditions were measured. The results show that, at the annual time scale, the surface of the forests is 1–2°C cooler than grasslands, indicating a substantial cooling effect of reforestation. The enhanced latent and sensible heat fluxes of forests have an average cooling effect of ?2.5°C, which offsets the net warming effect (+1.5°C) of albedo warming (+2.3°C) and emissivity cooling effect (?0.8°C) associated with surface properties. Additional daytime cooling over forests is driven by local feedbacks to incoming radiation. We further show that the forest cooling effect is most pronounced when land surface temperature is higher, often exceeding ?5°C. Our results contribute important observational evidence that reforestation in the temperate zone offers opportunities for local climate mitigation and adaptation.     

Development and validation of genetic markers for sex and cannabinoid chemotype in Cannabis sativa L.

Hemp (Cannabis sativa L.) is an emerging dioecious crop grown primarily for grain, fiber, and cannabinoids. There is good evidence for medicinal benefits of the most abundant cannabinoid in hemp, cannabidiol (CBD). For CBD production, female plants producing CBD but not tetrahydrocannabinol (THC) are desired. We developed and validated high‐throughput PACE (PCR Allele Competitive Extension) assays for C. sativa plant sex and cannabinoid chemotype. The sex assay was validated across a wide range of germplasm and resolved male plants from female and monoecious plants. The cannabinoid chemotype assay revealed segregation in hemp populations, and resolved plants producing predominantly THC, predominantly CBD, and roughly equal amounts of THC and CBD. Cultivar populations that were thought to be stabilized for CBD production were found to be segregating phenotypically and genotypically. Many plants predominantly producing CBD accumulated more than the current US legal limit of 0.3% THC by dry weight. These assays and data provide potentially useful tools for breeding and early selection of hemp.