Insulin-like growth factor binding protein-2: NMR analysis and structural characterization of the N-terminal domain

The insulin-like growth factor binding proteins are a family of six proteins (IGFBP-1 to -6) that bind insulin-like growth factors-I and -II (IGF-I/II) with high affinity. In addition to regulating IGF actions, IGFBPs have IGF-independent functions. IGFBP-2, the largest member of this family, is over-expressed in many cancers and has been proposed as a possible target for the development of novel anti-cancer therapeutics. The IGFBPs have a common architecture consisting of conserved N- and C-terminal domains joined by a variable linker domain. The solution structure and dynamics of the C-terminal domain of human IGFBP-2 have been reported (Kuang Z. et al. J. Mol. Biol. 364, 690-704, 2006) but neither the N-domain (N-BP-2) nor the linker domain have been characterised. Here we present NMR resonance assignments for human N-BP-2, achieved by recording spectra at low protein concentration using non-uniform sampling and maximum entropy reconstruction. Analysis of secondary chemical shifts shows that N-BP-2 possesses a secondary structure similar to that of other IGFBPs. Although aggregation hampered determination of the solution structure for N-BP-2, a homology model was generated based on the high degree of sequence and structure homology exhibited by the IGFBPs. This model was consistent with experimental NMR and SAXS data and displayed some unique features such as a Pro/Ala-rich non-polar insert, which formed a flexible solvent-exposed loop on the surface of the protein opposite to the IGF-binding interface. NMR data indicated that this loop could adopt either of two alternate conformations in solution - an entirely flexible conformation and one containing nascent helical structure. This loop and an adjacent poly-proline sequence may comprise a potential SH3 domain interaction site for binding to other proteins.     

Tetrahydrobiopterin improves endothelial function and decreases arterial stiffness in estrogen-deficient postmenopausal women

The mechanisms mediating arterial stiffening with aging and menopause are not completely understood. We determined whether administration of tetrahydrobiopterin (BH(4)), a critical cofactor for endothelial nitric oxide synthase to produce nitric oxide, would increase vascular endothelial-dependent vasodilatory tone and decrease arterial stiffness in estrogen-deficient postmenopausal women. Additionally, we examined whether the beneficial effects of estrogen on vascular function were possibly related to BH(4). Arterial stiffness (carotid artery compliance) and endothelial-dependent vasodilation [brachial artery flow-mediated dilation (FMD)] were measured in postmenopausal (n = 24; 57 ± 1 yr, mean ± SE) and eumenorrheic premenopausal (n = 9; 33 ± 2 yr) women before and 3 h after the oral administration of BH(4). Subsequently, in postmenopausal women, vascular testing (before and after BH(4)) was repeated following randomization to either 2 days of transdermal estradiol or placebo. Baseline carotid artery compliance and brachial artery FMD were lower in postmenopausal than in premenopausal women (P < 0.0001). BH(4) administration increased carotid artery compliance (0.61 ± 0.05 to 0.73 ± 0.04 mm(2)·mmHg(-1)·10(-1) vs. baseline, P < 0.0001) and brachial artery FMD (P < 0.001) in postmenopausal women but had no effect in premenopausal women (P = 0.62). Carotid artery compliance (0.59 ± 0.05 to 0.78 ± 0.06 mm(2)·mmHg(-1)·10(-1), P < 0.001) and FMD increased in postmenopausal women in response to estradiol (P = 0.02) but were not further improved with the coadministration of BH(4), possibly because estrogen increased BH(4) bioavailability. Carotid artery compliance and FMD increased with BH(4) in the placebo group (P = 0.02). Although speculative, these results suggest that reduced vascular BH(4) may be an important contributor to arterial stiffening in estrogen-deficient postmenopausal women, related in part to reduced endothelial-dependent vasodilatory tone.     

Reference genome sequence of the model plant Setaria

We generated a high-quality reference genome sequence for foxtail millet (Setaria italica). The ～400-Mb assembly covers ～80% of the genome and >95% of the gene space. The assembly was anchored to a 992-locus genetic map and was annotated by comparison with >1.3 million expressed sequence tag reads. We produced more than 580 million RNA-Seq reads to facilitate expression analyses. We also sequenced Setaria viridis, the ancestral wild relative of S. italica, and identified regions of differential single-nucleotide polymorphism density, distribution of transposable elements, small RNA content, chromosomal rearrangement and segregation distortion. The genus Setaria includes natural and cultivated species that demonstrate a wide capacity for adaptation. The genetic basis of this adaptation was investigated by comparing five sequenced grass genomes. We also used the diploid Setaria genome to evaluate the ongoing genome assembly of a related polyploid, switchgrass (Panicum virgatum).     

Classification of the Universe of Immune Epitope Literature: Representation and Knowledge Gaps

Background

A significant fraction of the more than 18 million scientific articles currently indexed in the PubMed database are related to immune responses to various agents, including infectious microbes, autoantigens, allergens, transplants, cancer antigens and others. The Immune Epitope Database (IEDB) is an online repository that catalogs immune epitope reactivity data derived from articles listed in the National Library of Medicine PubMed database. The IEDB is maintained and continually updated by monitoring PubMed for new, potentially relevant references.

Methodology

Herein we detail the classification of all epitope-specific literature in over 100 different immunological domains representing Infectious Diseases and Microbes, Autoimmunity, Allergy, Transplantation and Cancer. The relative number of references in each category reflects past and present areas of research on immune reactivities. In addition to describing the overall landscape of data distribution, this particular characterization of the epitope reference data also allows for the exploration of possible correlations with global disease morbidity and mortality data.

Conclusions/Significance

While in most cases diseases associated with high morbidity and mortality rates were amongst the most studied, a number of high impact diseases such as dengue, Schistosoma, HSV-2, B. pertussis and Chlamydia trachoma, were found to have very little coverage. The data analyzed in this fashion represents the first estimate of how reported immunological data corresponds to disease-related morbidity and mortality, and confirms significant discrepancies in the overall research foci versus disease burden, thus identifying important gaps to be pursued by future research. These findings may also provide a justification for redirecting a portion of research funds into some of the underfunded, critical disease areas.     

Camel exposure and knowledge about MERS-CoV among Australian Hajj pilgrims in 2014

正Dear Editor,Middle East respiratory syndrome coronavirus(MERS-CoV)affected 1,621 patients worldwide,with a 36%mortality rate by the end of 2015.The highest number of cases was recorded in Saudi Arabia,the location for Hajj     

Partitioning of ecosystem respiration of CO2 released during land‐use transition from temperate agricultural grassland to Miscanthus × giganteus

Conversion of large areas of agricultural grassland is inevitable if European and UK domestic production of biomass is to play a significant role in meeting demand. Understanding the impact of these land‐use changes on soil carbon cycling and stocks depends on accurate predictions from well‐parameterized models. Key considerations are cultivation disturbance and the effect of autotrophic root input stimulation on soil carbon decomposition under novel biomass crops. This study presents partitioned parameters from the conversion of semi‐improved grassland to Miscanthus bioenergy production and compares the contribution of autotrophic and heterotrophic respiration to overall ecosystem respiration of CO₂ in the first and second years of establishment. Repeated measures of respiration from within and without root exclusion collars were used to produce time‐series model integrations separating live root inputs from decomposition of grass residues ploughed in with cultivation of the new crop. These parameters were then compared to total ecosystem respiration derived from eddy covariance sensors. Average soil surface respiration was 13.4% higher in the second growing season, increasing from 2.9 to 3.29 g CO₂‐C m^?2 day^?1. Total ecosystem respiration followed a similar trend, increasing from 4.07 to 5.4 g CO₂‐C m^?2 day^?1. Heterotrophic respiration from the root exclusion collars was 32.2% lower in the second growing season at 1.20 g CO₂‐C m^?2 day^?1 compared to the previous year at 1.77 g CO₂‐C m^?2 day^?1. Of the total respiration flux over the two‐year time period, aboveground autotrophic respiration plus litter decomposition contributed 38.46% to total ecosystem respiration while belowground autotrophic respiration and stimulation by live root inputs contributed 46.44% to soil surface respiration. This figure is notably higher than mean figures for nonforest soils derived from the literature and demonstrates the importance of crop‐specific parameterization of respiration models.     

Using structured decision‐making to set restoration objectives when multiple values and preferences exist

Achieving global targets for restoring native vegetation cover requires restoration projects to identify and work toward common management objectives. This is made challenging by the different values held by concerned stakeholders, which are not often accounted for. Additionally, restoration is time‐dependent and yet there is often little explicit acknowledgment of the time frames required to achieve outcomes. Here, we argue that explicitly incorporating value and time considerations into stated objectives would help to achieve restoration goals. We reviewed the peer‐reviewed literature on restoration of terrestrial vegetation and found that while there is guidance on how to identify and account for stakeholder values and time considerations, there is little evidence these are being incorporated into decision‐making processes. In this article, we explore how a combination of stakeholder surveys and workshops can be used within a structured decision‐making framework to facilitate the integration of diverse stakeholder values and time frame considerations to set restoration objectives. We demonstrate this approach with a case of restoration decision‐making at a regional scale (southeast Queensland, Australia) with a view to this experience supporting similar restoration projects elsewhere.     

Incorporating climate change into ecosystem service assessments and decisions: a review

Climate change is having a significant impact on ecosystem services and is likely to become increasingly important as this phenomenon intensifies. Future impacts can be difficult to assess as they often involve long timescales, dynamic systems with high uncertainties, and are typically confounded by other drivers of change. Despite a growing literature on climate change impacts on ecosystem services, no quantitative syntheses exist. Hence, we lack an overarching understanding of the impacts of climate change, how they are being assessed, and the extent to which other drivers, uncertainties, and decision making are incorporated. To address this, we systematically reviewed the peer‐reviewed literature that assesses climate change impacts on ecosystem services at subglobal scales. We found that the impact of climate change on most types of services was predominantly negative (59% negative, 24% mixed, 4% neutral, 13% positive), but varied across services, drivers, and assessment methods. Although uncertainty was usually incorporated, there were substantial gaps in the sources of uncertainty included, along with the methods used to incorporate them. We found that relatively few studies integrated decision making, and even fewer studies aimed to identify solutions that were robust to uncertainty. For management or policy to ensure the delivery of ecosystem services, integrated approaches that incorporate multiple drivers of change and account for multiple sources of uncertainty are needed. This is undoubtedly a challenging task, but ignoring these complexities can result in misleading assessments of the impacts of climate change, suboptimal management outcomes, and the inefficient allocation of resources for climate adaptation.     

Improved Coral Population Estimation Reveals Trends at Multiple Scales on Australia’s Great Barrier Reef

The global erosion of biodiversity presents unique challenges for identifying major changes in population dynamics, establishing their causes, and managing and conserving affected ecosystems at broad spatial scales. Adaptive learning approaches connecting different spatial scales through the transfer of hierarchical information are powerful tools to address such challenges. Here, we use a Semi-Parametric Bayesian Hierarchical (SPa-BaH) model to estimate coral cover trajectories using 16 years of a broad-scale survey on Australia’s Great Barrier Reef (GBR). The spatiotemporal variability of coral populations has been considered by separating three-tiered spatial scales and allowing for alternating phases of increasing and decreasing in the estimation of their trajectories. Model estimates revealed coral cover trajectories that were highly variable according to location but that fairly consistently declined at a regional spatial scale. Notwithstanding this general trend, individual reefs within subregions in the central part of the GBR often displayed different trajectory types between sites separated by only a few hundred meters. These coral dynamics were also associated with reduced recovery rates in the Cairns and Swain subregions. Our study highlights the importance of accounting for local variation in coral cover when estimating the spatiotemporal trends in coral cover trajectories, in this case, at the GBR scale. By retaining information at different hierarchical spatial scales, our SPa-BaH model supports better estimation of large-scale coral cover trajectories. The quantitative approaches developed here can also be applied to other species with complex dynamics thereby enhancing estimations of their trajectories at local- and larger-scales and options for their management.