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.     

基于指标自动筛选的新疆开孔河流域生态健康评价

生态健康评价对了解区域生态健康状况和促进区域可持续发展具有重要意义,如何自动筛选出能反映生态系统特性的重要指标,是生态健康定量评估的关键问题。基于压力-状态-响应(PSR,Press-State-Response)框架和生态等级网络框架(EHN,Ecological Hierarchy Network),通过文献调研和因果分析建立要素层与指标层之间的交叉联系,构建了生态健康评价"网状"指标体系;在保证指标体系完备性基础上,通过结合主成分分析和熵权法的候选指标权重的客观计算,基于目标优化理论构建了评价指标的自动筛选模型,并基于中选指标计算了新疆开孔河流域2001—2017年生态健康指数(EHCI,Ecological Health Comprehensive Indexes),分析其空间分异和时间变化特征。结果表明:利用所建立的评价指标自动筛选模型,开孔河流域生态健康评价指标由31个候选指标自动筛选出了17个中选指标,用54.8%的指标表达了85.98%的信息,中选的17个指标在干旱/半干旱区域有关文献中应用较多,使用频次比例都在20%以上,其中归一化植被指数(NDVI,Normalized Difference Vegetation Index)、年降水量和植被覆盖度(FVC,Fractional Vegetation Coverage)3个指标的使用频次百分比均超过了50%,说明指标自动筛选模型的合理性;开孔河流域空间分布差异显著,总体上西北高、东南低,东南部和中部绿洲区外围生态健康状况较差,西北部河谷地带和中部两大绿洲区生态健康状况较好;17年来,流域生态质量整体趋于改善,显著改善区域占10.26%,远高于显著退化的1.61%,显著改善区域以孔雀河绿洲最为明显。开孔河流域生态健康的总体好转趋势说明区域生态综合治理取得一定成效。     

Evaluation of environmentally conscious manufacturing programs using a three-hybrid multi-criteria decision analysis method

Environmental management, being an important component in strategies for achieving sustainable development of processes and products, has emerged as a proactive approach in majority of the manufacturing organizations. From the strategic perspective environmentally conscious manufacturing (ECM) programs lead to better environmental management practice. The objective of the current paper is to present an integrated and holistic framework to evaluate ECM programs. This framework combines three multi-criteria decision analysis (MCDA) methods to consider eight major environmentally conscious manufacturing indicators (ECMI) in order to identify the efficiency of each ECM program. First the interdependence relationship among the ECMIs is established using decision-making trail and evaluation laboratory (DEMATEL). Then a range of weightage (i.e. upper and lower bounds) is created for each ECMI using analytic network process (ANP) to include managerial preferences. Finally, this range of weightage for each indicator is applied to perform restricted multiplier data envelopment analysis (RMDEA). Results show that the technical efficiency of the inefficient ECM programs for integrated RMDEA, on average, is calculated as 53.2% whereas traditional input oriented DEA provides the same score as 72.3%. This clearly indicates that integrated RMDEA is better than the input oriented DEA because same level of output could be produced with lesser resources if the ECM programs perform on the frontier. Hence, the advantage of this methodology is that the managerial preferences are successfully implemented through this newly developed hybrid methodology that will help to reduce less resource consumption and lead to better environmental policy.     

What is plant behaviour?*

The nature of plant behaviour is discussed, and it is concluded that it is best described as what plants do. The possibility that plant behaviour is simply signal‐induced phenotypic plasticity is outlined, and some limitations of this assumption are considered. Natural environments present many challenges to growing plants, and the consequent signalling that plants perceive is becoming extremely complex. Plant behaviour is active, purposeful and intentional, and examples are discussed. Much plant behaviour, concerned with stress and herbivory, is also based on an assessment of the future likelihood of further damaging episodes and is therefore predictive. Plant behaviour involves the acquisition and processing of information. Informational terminology provides a suitable way of incorporating the concepts of learning, memory and intelligence into plant behaviour, capabilities that plants are rarely credited with. Finally, trade‐offs, cost–benefit assessments and decision making are common plant behavioural attributes. It is suggested that intelligent assessments that involve the whole plant are essential to optimize these adaptive capabilities.     

Pre‐/post‐otic rhombomeric interactions control the emergence of a fetal‐like respiratory rhythm in the mouse embryo

How regional patterning of the neural tube in vertebrate embryos may influence the emergence and the function of neural networks remains elusive. We have begun to address this issue in the embryonic mouse hindbrain by studying rhythmogenic properties of different neural tube segments. We have isolated pre‐ and post‐otic hindbrain segments and spinal segments of the mouse neural tube, when they form at embryonic day (E) 9, and grafted them into the same positions in stage‐matched chick hosts. Three days after grafting, in vitro recordings of the activity in the cranial nerves exiting the grafts indicate that a high frequency (HF) rhythm (order: 10 bursts/min) is generated in post‐otic segments while more anterior pre‐otic and more posterior spinal territories generate a low frequency (LF) rhythm (order: 1 burst/min). Comparison with homo‐specific grafting of corresponding chick segments points to conservation in mouse and chick of the link between the patterning of activities and the axial origin of the hindbrain segment. This HF rhythm is reminiscent of the respiratory rhythm known to appear at E15 in mice. We also report on pre‐/post‐otic interactions. The pre‐otic rhombomere 5 prevents the emergence of the HF rhythm at E12. Although the nature of the interaction with r5 remains obscure, we propose that ontogeny of fetal‐like respiratory circuits relies on: (i) a selective developmental program enforcing HF rhythm generation, already set at E9 in post‐otic segments, and (ii) trans‐segmental interactions with pre‐otic territories that may control the time when this rhythm appears. © 2006 Wiley Periodicals, Inc. J Neurobiol, 2006     

Ionotropic Receptors as a Driving Force behind Human Synapse Establishment

The origin of nervous systems is a main theme in biology and its mechanisms are largely underlied by synaptic neurotransmission. One problem to explain synapse establishment is that synaptic orthologs are present in multiple aneural organisms. We questioned how the interactions among these elements evolved and to what extent it relates to our understanding of the nervous systems complexity. We identified the human neurotransmission gene network based on genes present in GABAergic, glutamatergic, serotonergic, dopaminergic, and cholinergic systems. The network comprises 321 human genes, 83 of which act exclusively in the nervous system. We reconstructed the evolutionary scenario of synapse emergence by looking for synaptic orthologs in 476 eukaryotes. The Human–Cnidaria common ancestor displayed a massive emergence of neuroexclusive genes, mainly ionotropic receptors, which might have been crucial to the evolution of synapses. Very few synaptic genes had their origin after the Human–Cnidaria common ancestor. We also identified a higher abundance of synaptic proteins in vertebrates, which suggests an increase in the synaptic network complexity of those organisms.     

Molecular Simulation of Solution Conformations of the Amyloid β-Peptide Aβ(1–42) by a Backpropagation Neural Network Model

Abstract

The predictive power of solution-dependent conformational states of the Aβ(1–42) peptide of Alzheimer's disease by an optimized backpropagation neural network was tested. It was found that the neural network simulates well the solution-dependent conformations. The model was also examined by using geometry-optimized conformations (hybrid approach of Gasteiger charges plus MM+ molecular-mechanics) where the initial coordinates were obtained by NMR solution spectroscopy.