Analysis of conformational motions and related key residue interactions responsible for a specific function of proteins with elastic network model

Protein collective motions play a critical role in many biochemical processes. How to predict the functional motions and the related key residue interactions in proteins is important for our understanding in the mechanism of the biochemical processes. Normal mode analysis (NMA) of the elastic network model (ENM) is one of the effective approaches to investigate the structure-encoded motions in proteins. However, the motion modes revealed by the conventional NMA approach do not necessarily correspond to a specific function of protein. In the present work, a new analysis method was proposed to identify the motion modes responsible for a specific function of proteins and then predict the key residue interactions involved in the functional motions by using a perturbation approach. In our method, an internal coordinate that accounts for the specific function was introduced, and the Cartesian coordinate space was transformed into the internal/Cartesian space by using linear approximation, where the introduced internal coordinate serves as one of the axes of the coordinate space. NMA of ENM in this internal/Cartesian space was performed and the function-relevant motion modes were identified according to their contributions to the specific function of proteins. Then the key residue interactions important for the functional motions of the protein were predicted as the interactions whose perturbation largely influences the fluctuation along the internal coordinate. Using our proposed methods, the maltose transporter (MalFGK₂) from E. Coli was studied. The functional motions and the key residue interactions that are related to the channel-gating function of this protein were successfully identified.     

Ecological and social determinants of association and proximity patterns in the fission–fusion society of spider monkeys (Ateles geoffroyi)

Some social species exhibit high levels of fission–fusion dynamics (FFD) that improve foraging efficiency. In this study, we shed light on the way that FFD allows animal groups to cope with fluctuations in fruit availability. We explore the relative contribution of fruit availability and social factors like sex in determining association and proximity patterns in spider monkeys. We tested the influence of fruit availability and social factors on the association and proximity patterns using three-year data from a group of spider monkeys in the Yucatan Peninsula of Mexico. We identified subgroup members and estimated their Interindividual distances through instantaneous scan sampling. We evaluated fruit availability by monitoring the phenology of the 10 most important food tree species for spider monkeys in the study site. Social network analyses allowed us to evaluate association and proximity patterns in subgroups. We showed that association patterns vary between seasons, respond to changes in fruit availability, and are influenced by the sex of individuals, likely reflecting biological and behavioral differences between sexes and the interplay between ecological and social factors. In contrast, proximity patterns were minimally affected by changes in fruit availability, suggesting that social factors are more important than food availability in determining cohesion within subgroups.     

Genome‐wide analysis of Italian sheep diversity reveals a strong geographic pattern and cryptic relationships between breeds

Italy counts several sheep breeds, arisen over centuries as a consequence of ancient and recent genetic and demographic events. To finely reconstruct genetic structure and relationships between Italian sheep, 496 subjects from 19 breeds were typed at 50K single nucleotide polymorphism loci. A subset of foreign breeds from the Sheep HapMap dataset was also included in the analyses. Genetic distances (as visualized either in a network or in a multidimensional scaling analysis of identical by state distances) closely reflected geographic proximity between breeds, with a clear north–south gradient, likely because of high levels of past gene flow and admixture all along the peninsula. Sardinian breeds diverged more from other breeds, a probable consequence of the combined effect of ancient sporadic introgression of feral mouflon and long‐lasting genetic isolation from continental sheep populations. The study allowed the detection of previously undocumented episodes of recent introgression (Delle Langhe into the endangered Altamurana breed) as well as signatures of known, or claimed, historical introgression (Merino into Sopravissana and Gentile di Puglia; Bergamasca into Fabrianese, Appenninica and, to a lesser extent, Leccese). Arguments that would question, from a genomic point of view, the current breed classification of Bergamasca and Biellese into two separate breeds are presented. Finally, a role for traditional transhumance practices in shaping the genetic makeup of Alpine sheep breeds is proposed. The study represents the first exhaustive analysis of Italian sheep diversity in an European context, and it bridges the gap in the previous HapMap panel between Western Mediterranean and Swiss breeds.     

Muon disrupts AKT hydrogen bond network in cancer

A cancer microenvironment generates strong hydrogen bond network system by the positive feedback loops supporting cancer complexity and robustness. Such network functions through the AKT locus generating high entropic energy supporting cancer metastatic robustness. Charged lepton particle muon follows the rule of Bragg effect during a collision with hydrogen network in cancer cells. Muon beam dismantles hydrogen bond network in cancer by the muon-catalyzed fusion, leading to apoptosis of cancer cells. Muon induces cumulative energy appearance on the hydrogen bond network in a cancer cell with its fast decay to an electron and two neutrinos. Thus, muon beam, muonic atom, muon neutrino shower, and electrons simultaneously cause fast neutralization of the AKT hydrogen bond network by the conversion of hydrogen into deuterium or helium, inactivating the hydrogen bond networks and inducing failure of cancer complexity and robustness with the disappearance of a malignant phenotype.     

河网地区小城镇街尘的粒径分布与多环芳烃污染

街尘是重要的环境介质,其携带的污染物在城镇化过程中对河网地区的水环境构成了一定的威胁。以杭嘉湖平原河网地区饮用水水源河流上游典型小城镇的街尘为研究对象,对街尘、河道沉积物、地表径流以及降雨前后地表水中的多环芳烃进行测定。在对不同粒径街尘中多环芳烃浓度的测定中发现,粒径为< 63、125-63、250-125 和 900-250 μm街尘中多环芳烃的平均含量分别为 7261、5835、4660 和 2909 μg/kg。小粒径的街尘颗粒含有较高的多环芳烃浓度,较小的密度,并且较难清扫,造成了小粒径街尘易被雨水冲刷随地表径流进入河网水体。在对两场降雨的地表径流中多环芳烃检测发现,颗粒态的多环芳烃分别占总浓度的 95%和 94%。地表径流过程增加了受纳水体中多环芳烃浓度的 43%-62%,其中超过 50%的增加表现为颗粒态。在对不同河段沉积物、地表径流中颗粒物和不同粒径街尘中多环芳烃浓度的风险评价中发现,小粒径街尘和地表径流中颗粒物中多环芳烃的浓度相接近并具有较高的生态风险,城镇段河道沉积物较次之。由于河网地区的特殊的水文条件和景观空间格局特征,地表径流沉积物在进入河网水体后易原位沉积,造成了河道沉积物城镇段有较高的多环芳烃浓度。     

An ecological network analysis of the structure,development and sustainability of China’s natural gas supply system security

Mitigating the impacts of climate change and ensuring energy supply security has compelled China’s policy makers to maximise the use of alternative and low carbon fuels. Use and production of natural gas (an energy source with low carbon emissions) has experienced remarkable growth in China during the last decade, making China the third largest consumer and importer in the world. This study applied a powerful system-oriented ecological network analysis (ENA) technique to study China’s natural gas policies as they pertain to guarantee supply security. Several indicators based on the ENA were measured to analyse the degree of connectivity, the contributions of different compartments, resource utilisation (aggradation), development (ascendancy) and sustainability of China’s natural gas supply system. It was found that China’s source and route diversification policy have caused the natural gas supply system to exhibit considerable network complexity, demonstrating the high level of development, flexibility and diversity of China’s natural gas supply system. However, the policy also has caused a decrease in the aggradation and sustainability from the perspective of an ecological system network. The most important compartments in terms of their contribution to China’s natural gas supply system were found to be domestic natural gas production and transit compartments.     

Developing pedotransfer functions to estimate the S-index for indicating soil quality

Indicating soil quality usually requires many soil properties of which the measurements are time consuming. Therefore, it is desirable to developing simple and effective indices for reflecting soil quality based on soil properties that can be readily obtained. The soil physical quality index, S-index, derived from the slope at the inflection point of the water retention curve (particularly the Van-Genuchten equation), is a comprehensive index for indicating soil properties. By comparing the S-index with a widely used soil quality index (SQI), this study used 298 samples to determine soil chemical and physical properties for calculating SQI, and found that the correlation coefficient between the S-index and SQI was 0.88, indicating that the S-index can represent soil quality well. An artificial neural network (ANN) model and a linear regression (LR) model were proposed for estimating S-index. Results showed that the ANN model was better than LR model in estimating S-index. Particularly, the ANN model with the soil bulk density and soil organic carbon (scenario A1) as inputs, had the highest R² of 0.807, while the LR model get the highest R² (predicted v.s. observed) of 0.75 with the combination of soil organic carbon, soil bulk density, total nitrogen and available nitrogen. This study is helpful for extending the applications of S-index.     

Does a reduction in the price of rhino horn prevent poaching?

Rhino poaching around the world has increased inordinately, to the extent that concerns exist over the possible survival of the species. An open access rhino poaching model is developed for South African rhino. The model is a hybrid dynamical model, as both a system dynamics model as well as a Bayesian network model are developed. The system dynamics model is used to estimate the unknown parameter values (through optimisation) and also to determine the intervals for the parameters. These intervals are then used in the Bayesian Belief Network model to assess uncertainty. Hybrid approaches improve the ability to validate models compared with conventional modelling. The resultant model indicates that reducing the price of rhino horn would not be effective at curbing poaching, unless poacher costs are also increased. However, increasing poacher costs is not a realistic policy option since these costs are largely beyond the control of decision-makers. The insensitivity of price to poaching effort has implications for methods proposed to reduce the value of rhinos, such as introducing synthetic rhino horn and the de-horning of rhinos.     

Predicting the effects of climate change on population connectivity and genetic diversity of an imperiled freshwater mussel,Cumberlandia monodonta (Bivalvia: Margaritiferidae), in riverine systems

In the face of global climate change, organisms may respond to temperature increases by shifting their ranges poleward or to higher altitudes. However, the direction of range shifts in riverine systems is less clear. Because rivers are dendritic networks, there is only one dispersal route from any given location to another. Thus, range shifts are only possible if branches are connected by suitable habitat, and stream‐dwelling organisms can disperse through these branches. We used Cumberlandia monodonta (Bivalvia: Unionoida: Margaritiferidae) as a model species to investigate the effects of climate change on population connectivity because a majority of contemporary populations are panmictic. We combined ecological niche models (ENMs) with population genetic simulations to investigate the effects of climate change on population connectivity and genetic diversity of C. monodonta. The ENMs were constructed using bioclimatic and landscape data to project shifts in suitable habitat under future climate scenarios. We then used forward‐time simulations to project potential changes in genetic diversity and population connectivity based on these range shifts. ENM results under current conditions indicated long stretches of highly suitable habitat in rivers where C. monodonta persists; populations in the upper Mississippi River remain connected by suitable habitat that does not impede gene flow. Future climate scenarios projected northward and headwater‐ward range contraction and drastic declines in habitat suitability for most extant populations throughout the Mississippi River Basin. Simulations indicated that climate change would greatly reduce genetic diversity and connectivity across populations. Results suggest that a single, large population of C. monodonta will become further fragmented into smaller populations, each of which will be isolated and begin to differentiate genetically. Because C. monodonta is a widely distributed species and purely aquatic, our results suggest that persistence and connectivity of stream‐dwelling organisms will be significantly altered in response to future climate change.