Evidence for network evolution in an Arabidopsis interactome map

Plants have unique features that evolved in response to their environments and ecosystems. A full account of the complex cellular networks that underlie plant-specific functions is still missing. We describe a proteome-wide binary protein-protein interaction map for the interactome network of the plant Arabidopsis thaliana containing about 6200 highly reliable interactions between about 2700 proteins. A global organization of plant biological processes emerges from community analyses of the resulting network, together with large numbers of novel hypothetical functional links between proteins and pathways. We observe a dynamic rewiring of interactions following gene duplication events, providing evidence for a model of evolution acting upon interactome networks. This and future plant interactome maps should facilitate systems approaches to better understand plant biology and improve crops.     

鸡卵泡膜细胞中膜联蛋白A2互作细胞蛋白的筛选及其功能分析

【目的】从鸡卵泡膜细胞蛋白中筛选和鉴定与膜联蛋白A2（ANXA2）相互作用的细胞蛋白并进行功能分析,为深入研究ANXA2调控鸡卵泡发育的作用机制提供理论依据。【方法】制备开产后30周龄贵州黄鸡的卵泡膜细胞,提取卵泡膜总蛋白后利用His Pull-Down联合质谱技术（LC-MS/MS）从卵泡膜细胞中筛选出与鸡ANXA2互作的细胞蛋白,然后通过GO数据库和KEEG数据库分别进行GO功能富集分析及KEEG信号通路注释分析,并利用STRING Version 11.0绘制蛋白互作网络图。【结果】通过His Pull-Down联合LC-MS/MS共鉴定获得41个鸡ANXA2互作细胞蛋白,GO功能富集分析发现这些互作细胞蛋白在分子功能、生物学进程和细胞组成均发挥作用。其中,在分子功能方面主要涉及蛋白结合（占58.06%）、催化活性（占19.35%）、核糖体结构（占16.13%）及细胞骨架结构组成（占6.45%）,在生物学进程方面主要参与细胞骨架（占19.35%）、刺激反应（占19.35%）、翻译（占16.13%）、代谢过程（占12.90%）、细胞迁移（占12.90%）、蛋白折叠（占9.68%）和蛋白运输（占9.68%）,而细胞组分显示以定位于细胞膜的蛋白为主（占32.26%）。鸡ANXA2蛋白互作细胞蛋白参与的KEEG信号通路主要有应激反应、代谢、翻译、信号转导、免疫系统和蛋白定位等。鸡ANXA2互作细胞蛋白互作网络可分为3条,即CNN2-FN1-MYH9-MYH10-ACTN1-CSRP1、ANXA1-ANXA2-ENO1-PRDX4-GPI-ATP5B-PRDX3-HSPA8-TUBB2A和CCT7-CCT4-GNB2L1-ATP5A1-RPS3-RPS3A-RPL23A-RPL22-RPS7;互作细胞蛋白间存在复杂的互作关系,其中又以膜联蛋白A1（ANXA1）与烯醇化酶-1（ENO1）及ANXA2的互作关系最明显。【结论】鸡ANXA2互作细胞蛋白主要参与细胞骨架形成、应对刺激和翻译等生物学过程,涉及应激反应、代谢、翻译、信号转导、免疫及蛋白定位等信号通路。其中,PRDX3、PRDX4、MYH9和TCSC可能通过与ANXA2蛋白相互作用而参与鸡卵巢相关疾病的发生,而ANXA1与ANXA2相互作用可能在鸡卵泡的发育及排卵过程中发挥重要调节作用。     

An in vivo map of the yeast protein interactome

Protein interactions regulate the systems-level behavior of cells; thus, deciphering the structure and dynamics of protein interaction networks in their cellular context is a central goal in biology. We have performed a genome-wide in vivo screen for protein-protein interactions in Saccharomyces cerevisiae by means of a protein-fragment complementation assay (PCA). We identified 2770 interactions among 1124 endogenously expressed proteins. Comparison with previous studies confirmed known interactions, but most were not known, revealing a previously unexplored subspace of the yeast protein interactome. The PCA detected structural and topological relationships between proteins, providing an 8-nanometer-resolution map of dynamically interacting complexes in vivo and extended networks that provide insights into fundamental cellular processes, including cell polarization and autophagy, pathways that are evolutionarily conserved and central to both development and human health.     

Hierarchical organization of modularity in metabolic networks

Spatially or chemically isolated functional modules composed of several cellular components and carrying discrete functions are considered fundamental building blocks of cellular organization, but their presence in highly integrated biochemical networks lacks quantitative support. Here, we show that the metabolic networks of 43 distinct organisms are organized into many small, highly connected topologic modules that combine in a hierarchical manner into larger, less cohesive units, with their number and degree of clustering following a power law. Within Escherichia coli, the uncovered hierarchical modularity closely overlaps with known metabolic functions. The identified network architecture may be generic to system-level cellular organization.     

Herpesviral protein networks and their interaction with the human proteome

The comprehensive yeast two-hybrid analysis of intraviral protein interactions in two members of the herpesvirus family, Kaposi sarcoma-associated herpesvirus (KSHV) and varicella-zoster virus (VZV), revealed 123 and 173 interactions, respectively. Viral protein interaction networks resemble single, highly coupled modules, whereas cellular networks are organized in separate functional submodules. Predicted and experimentally verified interactions between KSHV and human proteins were used to connect the viral interactome into a prototypical human interactome and to simulate infection. The analysis of the combined system showed that the viral network adopts cellular network features and that protein networks of herpesviruses and possibly other intracellular pathogens have distinguishing topologies.     

运用布尔网络模型和贝叶斯网络模型推测基因调控网络的比较研究

基因调控网络的研究从基因之间相互作用的角度揭示复杂的生命现象,是功能基因组学研究的重要内容,也是当前生物信息学研究的前沿。布尔网络模型和贝叶斯网络模型都是研究基因调控网络的有力工具。本文分别采用布尔网络模型和贝叶斯网络模式推测基因调控网络,实验结果显示布尔网络推测出了7条正确的调控关系,而贝叶斯网络仅推测出5条正确的调控关系,在本实验中推测基因之间的调控关系正确数布尔网络模型优于贝叶斯网络模型。     

Evolutionary rate in the protein interaction network

High-throughput screens have begun to reveal the protein interaction network that underpins most cellular functions in the yeast Saccharomyces cerevisiae. How the organization of this network affects the evolution of the proteins that compose it is a fundamental question in molecular evolution. We show that the connectivity of well-conserved proteins in the network is negatively correlated with their rate of evolution. Proteins with more interactors evolve more slowly not because they are more important to the organism, but because a greater proportion of the protein is directly involved in its function. At sites important for interaction between proteins, evolutionary changes may occur largely by coevolution, in which substitutions in one protein result in selection pressure for reciprocal changes in interacting partners. We confirm one predicted outcome of this process-namely, that interacting proteins evolve at similar rates.     

Independently evolved virulence effectors converge onto hubs in a plant immune system network

Plants generate effective responses to infection by recognizing both conserved and variable pathogen-encoded molecules. Pathogens deploy virulence effector proteins into host cells, where they interact physically with host proteins to modulate defense. We generated an interaction network of plant-pathogen effectors from two pathogens spanning the eukaryote-eubacteria divergence, three classes of Arabidopsis immune system proteins, and ~8000 other Arabidopsis proteins. We noted convergence of effectors onto highly interconnected host proteins and indirect, rather than direct, connections between effectors and plant immune receptors. We demonstrated plant immune system functions for 15 of 17 tested host proteins that interact with effectors from both pathogens. Thus, pathogens from different kingdoms deploy independently evolved virulence proteins that interact with a limited set of highly connected cellular hubs to facilitate their diverse life-cycle strategies.     

利用酵母双杂交系统筛选玉米ZmPRR73的互作蛋白

为了阐明ZmPRR73基因的生物学功能,构建诱饵表达载体pGBKT7-ZmPRR73,利用酵母双杂交技术,从长日照光照环境诱导的热带玉米自交系的cDNA文库中筛选与ZmPRR73互作的蛋白。结果显示：构建的诱饵载体pGBKT7-ZmPRR73对酵母菌株无毒性,且对报告基因无自激活活性,共鉴定出12个与ZmPRR73互作的候选蛋白。生物信息学分析表明,这些候选互作蛋白的功能涉及植物的转录调控、离子跨膜转运的调节、信号转导、电子传递链等多个方面,推测ZmPRR73蛋白与以上蛋白互作参与多个信号转导和代谢途径,研究结果补充和完善了ZmPRR73蛋白参与的调控途径,为进一步研究生物钟核心元件ZmPRR73的分子功能提供了新的分子证据。     

Neuronal computations with stochastic network states

Neuronal networks in vivo are characterized by considerable spontaneous activity, which is highly complex and intrinsically generated by a combination of single-cell electrophysiological properties and recurrent circuits. As seen, for example, during waking compared with being asleep or under anesthesia, neuronal responsiveness differs, concomitant with the pattern of spontaneous brain activity. This pattern, which defines the state of the network, has a dramatic influence on how local networks are engaged by inputs and, therefore, on how information is represented. We review here experimental and theoretical evidence of the decisive role played by stochastic network states in sensory responsiveness with emphasis on activated states such as waking. From single cells to networks, experiments and computational models have addressed the relation between neuronal responsiveness and the complex spatiotemporal patterns of network activity. The understanding of the relation between network state dynamics and information representation is a major challenge that will require developing, in conjunction, specific experimental paradigms and theoretical frameworks.     

GST-pull down技术筛选毛白杨天冬氨酸蛋白酶PtoAED3互作蛋白

[目的]天冬氨酸蛋白酶属于蛋白水解酶家族,为了解析毛白杨天冬氨酸蛋白酶PtoAED3在植物生长发育中的分子调节机制,利用GST-pull down联合质谱技术,对PtoAED3的互作蛋白进行鉴定和分析.[方法]通过同源克隆获得了毛白杨PtoAED3的CDS序列,构建含GST标签的原核表达载体pGEX-4T-PtoAED...     

Aromatic-aromatic interaction: a mechanism of protein structure stabilization

Analysis of neighboring aromatic groups in four biphenyl peptides or peptide analogs and 34 proteins reveals a specific aromatic-aromatic interaction. Aromatic pairs (less than 7 A between phenyl ring centroids) were analyzed for the frequency of pair type, their interaction geometry (separation and dihedral angle), their nonbonded interaction energy, the secondary structural locations of interacting residues, their environment, and their conservation in related molecules. The results indicate that on average about 60 percent of aromatic side chains in proteins are involved in aromatic pairs, 80 percent of which form networks of three or more interacting aromatic side chains. Phenyl ring centroids are separated by a preferential distance of between 4.5 and 7 A, and dihedral angles approaching 90 degrees are most common. Nonbonded potential energy calculations indicate that a typical aromatic-aromatic interaction has energy of between -1 and -2 kilocalories per mole. The free energy contribution of the interaction depends on the environment of the aromatic pair. Buried or partially buried pairs constitute 80 percent of the surveyed sample and contribute a free energy of between -0.6 and -1.3 kilocalories per mole to the stability of the protein's structure at physiologic temperature. Of the proteins surveyed, 80 percent of these energetically favorable interactions stabilize tertiary structure, and 20 percent stabilize quaternary structure. Conservation of the interaction in related molecules is particularly striking.     

A general mechanism for network-dosage compensation in gene circuits

Coping with variations in network dosage is crucial for maintaining optimal function in gene networks. We explored how network structure facilitates network-level dosage compensation. By using the yeast galactose network as a model, we combinatorially deleted one of the two copies of its four regulatory genes and found that network activity was robust to the change in network dosage. A mathematical analysis revealed that a two-component genetic circuit with elements of opposite regulatory activity (activator and inhibitor) constitutes a minimal requirement for network-dosage invariance. Specific interaction topologies and a one-to-one interaction stoichiometry between the activating and inhibiting agents were additional essential elements facilitating dosage invariance. This mechanism of network-dosage invariance could represent a general design for gene network structure in cells.     

植物中泛素/蛋白酶体介导的蛋白质水解对细胞周期调控的研究

细胞周期进程要求细胞周期调控蛋白如周期蛋白依赖性蛋白激酶(CDKs)和周期蛋白(Cyclins)在细胞中周期性的出现。这些调节蛋白被控制在几个水平,包括表达水平、磷酸化水平以及与其他调控蛋白之间的互作。最近,这些蛋白的可控性和程序性破坏在细胞周期调控中所起的作用的机理也越来越清楚,并且26S蛋白酶体与蛋白的破坏有关。例如,在细胞周期依赖性途径中Cyc(cyclin)A,Cyc B,Cyc D和B-CDK是通过26S蛋白酶体降解的。综述了植物中通过泛素/蛋白酶体介导的蛋白质水解对细胞周期调控的最新进展。     

无尺度网络理论与旅游产业集群的构建

网络理论及其方法在产业集群研究中得到广泛应用,但随机网络理论很难完美解释复杂的产业集群网络。无尺度网络具有集散节点、结构洞、社团结构、强弱连结4个方面的结构特点。旅游产业集群是典型的无尺度网络。笔者说明了可根据无尺度网络结构特点在旅游产业集群建设中,通过填补结构洞、控制强弱连结、打破社团结构和加强集散节点建设4种手段,提升旅游产业集群的活力,促进其健康发展。     

GST pull-down联合LC-MS/MS筛选柑橘抗溃疡病转录因子CsBZIP40的互作蛋白

【目的】CsBZIP40是一个与溃疡病抗性相关的转录因子,本研究旨在筛选转录因子CsBZIP40在响应柑橘溃疡病菌（Xanthomonas citri subsp. citri,Xcc）侵染过程中的互作蛋白,对CsBZIP40的互作网络进行分析,为柑橘抗溃疡病的分子育种提供理论依据。【方法】采用GST pull-down技术筛选柑橘在溃疡病菌侵染过程中CsBZIP40的互作蛋白。首先,构建带有GST标签的CsBZIP40蛋白融合表达载体,经IPTG（异丙基硫代半乳糖苷）诱导表达、纯化后获得GST-CsBZIP40融合蛋白作为诱饵蛋白;然后,将GST-CsBZIP40融合蛋白固定在谷胱甘肽亲和磁珠上,用固定在亲和磁珠的GST-CsBZIP40诱饵蛋白与接种溃疡病菌或LB培养基后柑橘叶片总蛋白进行孵育,与GST-CsBZIP40诱饵蛋白结合的蛋白复合物洗脱收集后进行SDS-PAGE凝胶电泳验证。将验证成功的样品洗脱液进行液相色谱串联质谱（LC-MS/MS）检测,鉴定出未侵染和侵染状态下CsBZIP40的互作蛋白,将检测到的蛋白利用甜橙基因组数据库进行注释,筛选出在溃疡病菌侵染过程中与CsBZIP40特异结合的蛋白,并进行GO、KEGG和互作网络分析。【结果】过表达CsBZIP40的转基因植株表型正常,与对照植株无明显差异。过表达CsBZIP40的转基因植株溃疡病抗性评价中病斑面积、病情指数均显著小于野生型植株,分别为野生型的45%和54%。以该转基因植株为材料成功提取出侵染溃疡病菌后和未接种溃疡病菌状态下的柑橘叶片总蛋白。成功构建出GST-CsBZIP40诱饵蛋白表达载体,诱导表达纯化出GST-BZIP40诱饵蛋白。利用GST-CsBZIP40诱饵蛋白从侵染溃疡病菌后柑橘总蛋白和未接菌柑橘总蛋白中成功钓取蛋白,并用LC-MS/MS检测。经过比对、注释和筛选,在柑橘溃疡病菌侵染过程中与GST-BZIP40特异结合的蛋白有53个,这些蛋白参与多个分子功能和通路。在这53个蛋白中,有6个蛋白（Cs1g02310、Cs3g05280、Cs3g23950、Cs6g13880、Cs7g12130、orange1.1t04973）可能与植物抗病性密切相关。数据库中已经证明53个蛋白中44个与CsBZIP40有直接或间接的互作关系。【结论】溃疡病菌侵染过程中有53个蛋白与CsBZIP40互作,根据注释6个蛋白与植物抗病性密切相关,这些蛋白可能在提高柑橘生物胁迫抗逆性方面发挥着重要的作用。