Envelope structure of Semliki Forest virus reconstructed from cryo-electron micrographs

The basic principles of the architecture of many viral protein shells have been successfully established from electron microscopy and X-ray data, but enveloped viruses have been more difficult to study because they resist crystallization and are easily deformed when prepared for electron microscopy. To avoid the limitations of conventional techniques when applied to enveloped viruses, we have used a cryo-electron microscopy method in which unfixed and unstained viruses are observed in an unsupported thin layer of vitrified suspension. Because of electron beam damage, the many different views required for high-resolution three-dimensional reconstruction cannot be obtained from a tilt series of the same particle. The images of many differently oriented viruses are combined using a novel reconstruction method, 'reconstruction by optimized series expansion' (ROSE). The structure of the envelope of Semliki Forest virus has been reconstructed to 3.5-nm resolution. The T = 4 geometry of the surface lattice, the shape of the trimeric spikes and their arrangement on the lipid bilayer are visualized.     

Conformational change and protein-protein interactions of the fusion protein of Semliki Forest virus

Fusion of biological membranes is mediated by specific lipid-interacting proteins that induce the formation and expansion of an initial fusion pore. Here we report the crystal structure of the ectodomain of the Semliki Forest virus fusion glycoprotein E1 in its low-pH-induced trimeric form. E1 adopts a folded-back conformation that, in the final post-fusion form of the full-length protein, would bring the fusion peptide loop and the transmembrane anchor to the same end of a stable protein rod. The observed conformation of the fusion peptide loop is compatible with interactions only with the outer leaflet of the lipid bilayer. Crystal contacts between fusion peptide loops of adjacent E1 trimers, together with electron microscopy observations, suggest that in an early step of membrane fusion, an intermediate assembly of five trimers creates two opposing nipple-like deformations in the viral and target membranes, leading to formation of the fusion pore.     

A quantitative protein interaction network for the ErbB receptors using protein microarrays

Although epidermal growth factor receptor (EGFR; also called ErbB1) and its relatives initiate one of the most well-studied signalling networks, there is not yet a genome-wide view of even the earliest step in this pathway: recruitment of proteins to the activated receptors. Here we use protein microarrays comprising virtually every Src homology 2 (SH2) and phosphotyrosine binding (PTB) domain encoded in the human genome to measure the equilibrium dissociation constant of each domain for 61 peptides representing physiological sites of tyrosine phosphorylation on the four ErbB receptors. This involved 77,592 independent biochemical measurements and provided a quantitative protein interaction network that reveals many new interactions, including ones that fall outside of our current view of domain selectivity. By slicing through the network at different affinity thresholds, we found surprising differences between the receptors. Most notably, EGFR and ErbB2 become markedly more promiscuous as the threshold is lowered, whereas ErbB3 does not. Because EGFR and ErbB2 are overexpressed in many human cancers, our results suggest that the extent to which promiscuity changes with protein concentration may contribute to the oncogenic potential of receptor tyrosine kinases, and perhaps other signalling proteins as well.     

空间交互网络研究进展

 空间交互网络是人、商品和信息等在地点之间流动而形成的嵌入在空间中的有向流网络。典型的空间交互网络包括国际贸易网络、人口迁移网络、人群出行网络及电话通信网络等。理解和预测空间交互网络中的流量分布模式不仅是区域科学、交通科学、经济地理学等很多领域长期以来的一个重要研究主题,在城市和交通规划、疾病传播防控、商业服务等领域也具有广泛应用价值。本文在简要介绍引力模型、介入机会模型等经典空间交互模型的基础上,着重对近年来复杂系统研究领域在空间交互网络建模方面的研究成果进行介绍,包括辐射模型、人口权重机会模型及空间交互网络上的随机游走模型等,并且对空间交互网络研究中存在的挑战性问题进行探讨,包括个体多样性行为建模、群体空间交互决策行为实验、数据驱动的活动-出行行为研究等。     

含Syntaxin 1A基因的SFV表达载体的构建与表达

用绿色荧光蛋白 (EGFP)标记了Syntaxin 1A(Syn1A)蛋白 ,构建了含有EGFP Syn1A融合蛋白的森林脑炎病毒表达载体 pSFV1 EGFP Syn1A ,测序结果表明表达载体构建正确 .用荧光显微成像技术研究了Syn1A在原代大鼠胰腺 β细胞中的定位 ,结果表明Syn1A主要定位于细胞质膜上 .     

基于网络药理学探讨金荞麦抗呼吸道合胞病毒作用机制

基于网络药理学筛选金荞麦抗呼吸道合胞病毒的核心作用成分及靶点,并使用芯片数据挖掘和分子对接做初步验证。通过中药系统药理学数据库与分析平台(traditional Chinese medicine systems pharmacology database and analysis platform,TCMSP)筛选核心作用成分,借助SwissTargetPrediction预测核心作用成分靶点,通过GeneCards、GenCLiP 3、NCBI获取呼吸道合胞病毒涉及肺炎靶点。经靶点映射生成交集靶点网络,并通过STRING、DAVID平台构建蛋白质-蛋白质相互作用(Protein-protein interaction,PPI)关系及核心富集通路,获取核心靶点与通路。使用GEO芯片数据挖掘及AutoDock Vina分子对接初步验证核心靶点的有效性。最终通过TCMSP筛选到金荞麦15个成分,经靶点映射发现金荞麦通过45个靶点发挥作用,通过PPI和KEGG(Kyoto encyclopedia of genes and genomes) 通路综合分析可得金荞麦发挥抗呼吸道合胞病毒的作用靶点为AKT1、VEGFA、PTGS2、SRC、EGFR、KDR、STAT3、BCL2等,数据挖掘和分子对接结果与预测基本一致,为进一步深入揭示其作用机制奠定了良好基础。     

数码显微互动网络教室在病理学教学中的应用

实验课是病理学教学的一个重要环节,我院于2006年将数码互动教学模式引入病理学教学,采用多媒体课件、多媒体数码互动系统、病理切片及大体标本观察等手段,发挥教学过程中"教师启发、学生参与、师生互动"的作用,扩展病理学实验的深度和广度,提高实验教学质量。     

水稻蛋白质相互作用网络的预测与分析

通过同源映射的方法,利用6个模式物种的蛋白质相互作用数据预测水稻的蛋白质相互作用网络.预测到水稻中有4483个蛋白质参与了24942个蛋白质相互作用.通过GO注释,结构域相互作用,基因共表达等3个证据评估预测网络的质量,并对网络进行了拓扑属性分析.结果表明水稻的蛋白质相互作用网络符合scale-free属性.通过对网络中功能模块的分析,可以预测蛋白质的功能和亚细胞定位信息.     

可信的网络交互模式设计与实现

为了充分利用信任关系来建立网络交互模式,提出了基于信任的基础交互模式及其模糊产生式规则,建立了交互事件确信度和整体交互模式确信度等概念,进一步提出了基于基础交互模式的网络交互模式的搜索算法和更新方法。模式的搜索算法是基于堆栈的深度优先搜索算法的,整体交互模式的主动更新是根据用户的需求进行改进,被动更新是根据交互实体信任关系的变化和交互事件的增减对模式进行更新。理论分析和实验结果表明,该方法可以快速建立可信的整体交互模式和更新整体交互模式的确信度。     

Evidence for dynamically organized modularity in the yeast protein-protein interaction network

In apparently scale-free protein-protein interaction networks, or 'interactome' networks, most proteins interact with few partners, whereas a small but significant proportion of proteins, the 'hubs', interact with many partners. Both biological and non-biological scale-free networks are particularly resistant to random node removal but are extremely sensitive to the targeted removal of hubs. A link between the potential scale-free topology of interactome networks and genetic robustness seems to exist, because knockouts of yeast genes encoding hubs are approximately threefold more likely to confer lethality than those of non-hubs. Here we investigate how hubs might contribute to robustness and other cellular properties for protein-protein interactions dynamically regulated both in time and in space. We uncovered two types of hub: 'party' hubs, which interact with most of their partners simultaneously, and 'date' hubs, which bind their different partners at different times or locations. Both in silico studies of network connectivity and genetic interactions described in vivo support a model of organized modularity in which date hubs organize the proteome, connecting biological processes--or modules--to each other, whereas party hubs function inside modules.     

基于三维技术的设计学网络互动方法研究

随着三维技术在教育领域的广泛深入,着重分析了三维技术在设计学网络化实验教学方面的方法、特点、发展前景和存在的问题。并且使用MAYA软件建立了一系列三维模型,从材质设置、灯光设置、动画设计到后期渲染影视输出一系列过程进行了深入分析和探索。从视频效果上看,三维技术制作出来的互动教学模式在课堂上互动效果比传统的平面教学方法效果更加直观和易于学生对课堂内容的消化吸收,信息载入量更大,趣味性也更强。当然也存在一系列的限制因素需要不断完善和加以解决。     

基于BP神经网络的森林可燃物负荷量估测

森林可燃物负荷量是决定林火行为的一个重要因子,因此,森林可燃物负荷量估测对于森林防火管理具有重要意义。该文利用BP神经网络方法和多元回归方法对大兴安岭地区落叶松林32块森林样地数据构建森林可燃物负荷量预测模型,用以研究利用林龄、郁闭度、平均高、胸径等林分因子估测该地区森林可燃物负荷量的方法。通过MATLAB软件实现BP神经网络森林可燃物负荷量估测模型;通过SPSS软件建立多元回归森林可燃物负荷量估测模型。BP神经网络森林可燃物负荷量估测模型拟合精度为99.9%、外推精度为65.51%;多元回归可燃物负荷量估测模型拟合精度为68.29%、外推精度为62.1%。通过比较分析,得出结论:利用BP神经网络方法估测森林可燃物负荷量是可行的;BP神经网络模型精度高于多元回归模型;由于训练样本太少,2种模型外推精度低于70%。     

Optimization of specificity in a cellular protein interaction network by negative selection

Most proteins that participate in cellular signalling networks contain modular protein-interaction domains. Multiple versions of such domains are present within a given organism: the yeast proteome, for example, contains 27 different Src homology 3 (SH3) domains. This raises the potential problem of cross-reaction. It is generally thought that isolated domain-ligand pairs lack sufficient information to encode biologically unique interactions, and that specificity is instead encoded by the context in which the interaction pairs are presented. Here we show that an isolated peptide ligand from the yeast protein Pbs2 recognizes its biological partner, the SH3 domain from Sho1, with near-absolute specificity--no other SH3 domain present in the yeast genome cross-reacts with the Pbs2 peptide, in vivo or in vitro. Such high specificity, however, is not observed in a set of non-yeast SH3 domains, and Pbs2 motif variants that cross-react with other SH3 domains confer a fitness defect, indicating that the Pbs2 motif might have been optimized to minimize interaction with competing domains specifically found in yeast. System-wide negative selection is a subtle but powerful evolutionary mechanism to optimize specificity within an interaction network composed of overlapping recognition elements.