Association between FABP2 Ala54Thr polymorphisms and type 2 diabetes mellitus risk: a HuGE Review and Meta‐Analysis

Many studies have examined the association between the FABP2 (rs1799883) Ala54Thr gene polymorphism and type 2 diabetes mellitus risk (T2DM) in various populations, but their results have been inconsistent. To assess this relationship more precisely, A HuGE review and meta‐analysis were performed. The PubMed and CNKI database was searched for case‐control studies published up to April 2014. Data were extracted and pooled odds ratios (OR) with 95% confidence intervals (CI) were calculated. Ultimately, 13 studies, comprising 2020 T2DM cases and 2910 controls were included. Overall, for the Thr carriers (Ala/Thr and Thr/Thr) versus the wild‐type homozygotes (Ala/Ala), the pooled OR was 1.18 (95% CI = 1.04–1.34, P = 0.062 for heterogeneity), for Thr/Thr versus Ala/Ala the pooled OR was 1.17 (95% CI = 1.05–1.41 P = 0.087 for heterogeneity). In the stratified analysis by ethnicity, the significantly risks were found among Asians but not Caucasians. This meta‐analysis suggests that the FABP2 (rs1799883) Ala54Thr polymorphisms are associated with increased susceptibility to T2DM risk among Asians but not Caucasians.     

Plant intraspecific functional trait variation is related to within‐habitat heterogeneity and genetic diversity in Trifolium montanum L.

Intraspecific trait variation (ITV), based on available genetic diversity, is one of the major means plant populations can respond to environmental variability. The study of functional trait variation and diversity has become popular in ecological research, for example, as a proxy for plant performance influencing fitness. Up to now, it is unclear which aspects of intraspecific functional trait variation (iFD_CV) can be attributed to the environment or genetics under natural conditions. Here, we examined 260 individuals from 13 locations of the rare (semi‐)dry calcareous grassland species Trifolium montanum L. in terms of iFD_CV, within‐habitat heterogeneity, and genetic diversity. The iFD_CV was assessed by measuring functional traits (releasing height, biomass, leaf area, specific leaf area, leaf dry matter content, F_v/F_m, performance index, stomatal pore surface, and stomatal pore area index). Abiotic within‐habitat heterogeneity was derived from altitude, slope exposure, slope, leaf area index, soil depth, and further soil factors. Based on microsatellites, we calculated expected heterozygosity (H_e) because it best‐explained, among other indices, iFD_CV. We performed multiple linear regression models quantifying relationships among iFD_CV, abiotic within‐habitat heterogeneity and genetic diversity, and also between separate functional traits and abiotic within‐habitat heterogeneity or genetic diversity. We found that abiotic within‐habitat heterogeneity influenced iFD_CV twice as strong compared to genetic diversity. Both aspects together explained 77% of variation in iFD_CV ( = .77, F_{2, 10} = 21.66, p < .001). The majority of functional traits (releasing height, biomass, specific leaf area, leaf dry matter content, F_v/F_m, and performance index) were related to abiotic habitat conditions indicating responses to environmental heterogeneity. In contrast, only morphology‐related functional traits (releasing height, biomass, and leaf area) were related to genetics. Our results suggest that both within‐habitat heterogeneity and genetic diversity affect iFD_CV and are thus crucial to consider when aiming to understand or predict changes of plant species performance under changing environmental conditions.     

An Extreme Value Analysis of Pollutant Concentrations in Surface Soils Due to Atmospheric Deposition

Risk assessments often rely on deterministic models using long-term averages or “steady-state” values of input variables. Such models do not provide the information needed to estimate acute exposures. This study uses extreme value theory to examine the frequency and magnitude of daily pollutant concentrations in surface soils predicted at six U.S. locations. Concentrations are predicted using a deposition-leaching model and 50 years of historical precipitation data. A stochastic model also is used to generate 1000 years of precipitation data as modeling inputs for each location. The annual maximum concentrations at each site are fitted to a Gumbel type I distribution to estimate occurrence probability. For soluble pollutants, the predicted concentration varied substantially with precipitation, and the maximum daily concentrations exceeded annual averages by 4 to 8 times. Observed and synthetic precipitation data produced similar results at most study locations, though the synthetic data provided a slightly better fit to the Gumbel type I distribution. The precipitation model allows the generation of representative precipitation data that extend limited historical records. The extreme value analysis facilitates the evaluation of maximum pollutant concentrations, return periods, and other statistics that are important in evaluating acute exposures.     

A fast dynamic mode of the EF‐G‐bound ribosome

A key intermediate in translocation is an ‘unlocked state’ of the pre‐translocation ribosome in which the P‐site tRNA adopts the P/E hybrid state, the L1 stalk domain closes and ribosomal subunits adopt a ratcheted configuration. Here, through two‐ and three‐colour smFRET imaging from multiple structural perspectives, EF‐G is shown to accelerate structural and kinetic pathways in the ribosome, leading to this transition. The EF‐G‐bound ribosome remains highly dynamic in nature, wherein, the unlocked state is transiently and reversibly formed. The P/E hybrid state is energetically favoured, but exchange with the classical P/P configuration persists; the L1 stalk adopts a fast dynamic mode characterized by rapid cycles of closure and opening. These data support a model in which P/E hybrid state formation, L1 stalk closure and subunit ratcheting are loosely coupled, independent processes that must converge to achieve the unlocked state. The highly dynamic nature of these motions, and their sensitivity to conformational and compositional changes in the ribosome, suggests that regulating the formation of this intermediate may present an effective avenue for translational control.     

Biosensors based on peptide exposure show single molecule conformations in live cells

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Evolutionary assembly of cooperating cell types in an animal chemical defense system

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Structural Insight into Chromatin Recognition by Multiple Domains of the Tumor Suppressor RBBP1

Retinoblastoma-binding protein 1 (RBBP1) is involved in gene regulation, epigenetic regulation, and disease processes. RBBP1 contains five domains with DNA-binding or histone-binding activities, but how RBBP1 specifically recognizes chromatin is still unknown. An AT-rich interaction domain (ARID) in RBBP1 was proposed to be the key region for DNA-binding and gene suppression. Here, we first determined the solution structure of a tandem PWWP-ARID domain mutant of RBBP1 after deletion of a long flexible acidic loop L12 in the ARID domain. NMR titration results indicated that the ARID domain interacts with DNA with no GC- or AT-rich preference. Surprisingly, we found that the loop L12 binds to the DNA-binding region of the ARID domain as a DNA mimic and inhibits DNA binding. The loop L12 can also bind weakly to the Tudor and chromobarrel domains of RBBP1, but binds more strongly to the DNA-binding region of the histone H2A-H2B heterodimer. Furthermore, both the loop L12 and DNA can enhance the binding of the chromobarrel domain to H3K4me3 and H4K20me3. Based on these results, we propose a model of chromatin recognition by RBBP1, which highlights the unexpected multiple key roles of the disordered acidic loop L12 in the specific binding of RBBP1 to chromatin.     

Intraspecific genetic variation of a Fagus sylvatica population in a temperate forest derived from airborne imaging spectroscopy time series

1. The growing pace of environmental change has increased the need for large‐scale monitoring of biodiversity. Declining intraspecific genetic variation is likely a critical factor in biodiversity loss, but is especially difficult to monitor: assessments of genetic variation are commonly based on measuring allele pools, which requires sampling of individuals and extensive sample processing, limiting spatial coverage. Alternatively, imaging spectroscopy data from remote platforms may hold the potential to reveal genetic structure of populations. In this study, we investigated how differences detected in an airborne imaging spectroscopy time series correspond to genetic variation within a population of Fagus sylvatica under natural conditions.
2. We used multi‐annual APEX (Airborne Prism Experiment) imaging spectrometer data from a temperate forest located in the Swiss midlands (Laegern, 47°28'N, 8°21'E), along with microsatellite data from F. sylvatica individuals collected at the site. We identified variation in foliar reflectance independent of annual and seasonal changes which we hypothesize is more likely to correspond to stable genetic differences. We established a direct connection between the spectroscopy and genetics data by using partial least squares (PLS) regression to predict the probability of belonging to a genetic cluster from spectral data.
3. We achieved the best genetic structure prediction by using derivatives of reflectance and a subset of wavebands rather than full‐analyzed spectra. Our model indicates that spectral regions related to leaf water content, phenols, pigments, and wax composition contribute most to the ability of this approach to predict genetic structure of F. sylvatica population in natural conditions.
4. This study advances the use of airborne imaging spectroscopy to assess tree genetic diversity at canopy level under natural conditions, which could overcome current spatiotemporal limitations on monitoring, understanding, and preventing genetic biodiversity loss imposed by requirements for extensive in situ sampling.

     

A Comparison of Bone Mineral Density and Its Predictors in HIV-Infected and HIV-Uninfected Older Men

ObjectiveBone health in older individuals with HIV infection has not been well studied. This study aimed to compare bone mineral density (BMD), trabecular bone score (TBS), and bone markers between HIV-infected men and age- and body mass index (BMI)-matched HIV-uninfected men aged ≥60 years. We investigated the associations of risk factors related to fracture with BMD, TBS, and bone markers in HIV-infected men.MethodsThis cross-sectional study included 45 HIV-infected men receiving antiretroviral therapy and 42 HIV-uninfected men. Medical history, BMD and TBS measurements, and laboratory tests related to bone health were assessed in all the participants. HIV-related factors known to be associated with bone loss were assessed in the HIV-infected men.ResultsThe mean BMD, TBS, and osteopenia or osteoporosis prevalence were similar among the cases and controls. The HIV-infected men had significantly higher mean N-terminal propeptide of type 1 procollagen and C-terminal cross-linking telopeptide of type I collagen levels. Stepwise multiple linear regression analysis demonstrated that low BMI (lumbar spine, P = .015; femoral neck, P = .018; and total hip, P = .005), high C-terminal cross-linking telopeptide of type I collagen concentration (total hip, P = .042; and TBS, P = .010), and low vitamin D supplementation (TBS, P = .035) were independently associated with low BMD and TBS.ConclusionIn older HIV-infected men with a low fracture risk, the mean BMD and TBS were similar to those of the age- and BMI-matched controls. The mean bone marker levels were higher in the HIV group. Traditional risk factors for fracture, including low BMI, high C-terminal cross-linking telopeptide of type I collagen level, and low vitamin D supplementation, were significant predictors of low BMD and TBS.