Global landscape of HIV-human protein complexes

Human immunodeficiency virus (HIV) has a small genome and therefore relies heavily on the host cellular machinery to replicate. Identifying which host proteins and complexes come into physical contact with the viral proteins is crucial for a comprehensive understanding of how HIV rewires the host's cellular machinery during the course of infection. Here we report the use of affinity tagging and purification mass spectrometry to determine systematically the physical interactions of all 18 HIV-1 proteins and polyproteins with host proteins in two different human cell lines (HEK293 and Jurkat). Using a quantitative scoring system that we call MiST, we identified with high confidence 497 HIV-human protein-protein interactions involving 435 individual human proteins, with ～40% of the interactions being identified in both cell types. We found that the host proteins hijacked by HIV, especially those found interacting in both cell types, are highly conserved across primates. We uncovered a number of host complexes targeted by viral proteins, including the finding that HIV protease cleaves eIF3d, a subunit of eukaryotic translation initiation factor 3. This host protein is one of eleven identified in this analysis that act to inhibit HIV replication. This data set facilitates a more comprehensive and detailed understanding of how the host machinery is manipulated during the course of HIV infection.     

Interaction network containing conserved and essential protein complexes in Escherichia coli

Proteins often function as components of multi-subunit complexes. Despite its long history as a model organism, no large-scale analysis of protein complexes in Escherichia coli has yet been reported. To this end, we have targeted DNA cassettes into the E. coli chromosome to create carboxy-terminal, affinity-tagged alleles of 1,000 open reading frames (approximately 23% of the genome). A total of 857 proteins, including 198 of the most highly conserved, soluble non-ribosomal proteins essential in at least one bacterial species, were tagged successfully, whereas 648 could be purified to homogeneity and their interacting protein partners identified by mass spectrometry. An interaction network of protein complexes involved in diverse biological processes was uncovered and validated by sequential rounds of tagging and purification. This network includes many new interactions as well as interactions predicted based solely on genomic inference or limited phenotypic data. This study provides insight into the function of previously uncharacterized bacterial proteins and the overall topology of a microbial interaction network, the core components of which are broadly conserved across Prokaryota.     

Proteome survey reveals modularity of the yeast cell machinery

Protein complexes are key molecular entities that integrate multiple gene products to perform cellular functions. Here we report the first genome-wide screen for complexes in an organism, budding yeast, using affinity purification and mass spectrometry. Through systematic tagging of open reading frames (ORFs), the majority of complexes were purified several times, suggesting screen saturation. The richness of the data set enabled a de novo characterization of the composition and organization of the cellular machinery. The ensemble of cellular proteins partitions into 491 complexes, of which 257 are novel, that differentially combine with additional attachment proteins or protein modules to enable a diversification of potential functions. Support for this modular organization of the proteome comes from integration with available data on expression, localization, function, evolutionary conservation, protein structure and binary interactions. This study provides the largest collection of physically determined eukaryotic cellular machines so far and a platform for biological data integration and modelling.     

Proteomics to study genes and genomes

Proteomics, the large-scale analysis of proteins, will contribute greatly to our understanding of gene function in the post-genomic era. Proteomics can be divided into three main areas: (1) protein micro-characterization for large-scale identification of proteins and their post-translational modifications; (2) 'differential display' proteomics for comparison of protein levels with potential application in a wide range of diseases; and (3) studies of protein-protein interactions using techniques such as mass spectrometry or the yeast two-hybrid system. Because it is often difficult to predict the function of a protein based on homology to other proteins or even their three-dimensional structure, determination of components of a protein complex or of a cellular structure is central in functional analysis. This aspect of proteomic studies is perhaps the area of greatest promise. After the revolution in molecular biology exemplified by the ease of cloning by DNA methods, proteomics will add to our understanding of the biochemistry of proteins, processes and pathways for years to come.     

The protein-protein interaction map of Helicobacter pylori

With the availability of complete DNA sequences for many prokaryotic and eukaryotic genomes, and soon for the human genome itself, it is important to develop reliable proteome-wide approaches for a better understanding of protein function. As elementary constituents of cellular protein complexes and pathways, protein-protein interactions are key determinants of protein function. Here we have built a large-scale protein-protein interaction map of the human gastric pathogen Helicobacter pylori. We have used a high-throughput strategy of the yeast two-hybrid assay to screen 261 H. pylori proteins against a highly complex library of genome-encoded polypeptides. Over 1,200 interactions were identified between H. pylori proteins, connecting 46.6% of the proteome. The determination of a reliability score for every single protein-protein interaction and the identification of the actual interacting domains permitted the assignment of unannotated proteins to biological pathways.     

DMSO处理后中国仓鼠卵巢细胞的蛋白质组变化分析

在培养基中添加二甲基亚砜(DMSO)可使基因工程中国仓鼠卵巢细胞(CHO)外源蛋白乙肝表面抗原(HBsAg)的比生产速率提高4倍以上.为了进一步研究DMSO的作用机理,采用双相凝胶电泳技术分离在培养基中添加1.5%的DMSO后CHO细胞的总蛋白,胶态考马斯亮蓝G-250染色,GS-800凝胶扫描仪获取凝胶图像,并用PDQUEST软件分析,测得每张图谱平均斑点数量为1852±123,以其中一块胶为参考胶进行4块胶间的斑点匹配,其平均匹配的点数达1326±100,平均匹配率为71.6%以上.通过分析得到18个蛋白质点在添加了DMSO后表达量有明显变化(其中12个蛋白表达量明显降低,6个蛋白表达量明显增加.用基质辅助激光解析电离飞行时间质谱测定其胶内酶解后的肽质指纹谱图和串级质谱图,用GPS软件查询NCBI数据库进行了鉴定.鉴定结果表明,这些差异蛋白中一些是与细胞周期有关的蛋白,一些是与细胞能量代谢相关的蛋白,还有一些是与蛋白翻译后修饰有关的酶,这些结果进一步深化了对DMSO提高CHO细胞表达HBsAg的机理的理解.     

Discovering protein complexes from protein-protein interaction data by dense subgraph

High-throughput techniques,such as the yeast-two-hybrid system,produce mass protein-protein interaction data. The new technique makes it possible to predict protein complexes by com-putation. A novel method,named DSDA,has been put forward to predict protein complexes via dense subgraph because the proteins among a protein complex have a much tighter relation among them than with others. This method chooses a node with its neighbors to form the initial subgraph,and chooses a node which has the tightest relation with the subgraph according to greedy strategy,then the chosen node is added into the initial subgraph until the subgraph density is below the threshold value. The ob-tained subgraph is then removed from the network and the process continues until no subgraph can be detected. Compared with other algorithms,DSDA can predict not only non-overlap protein com-plexes but also overlap protein complexes. The experiment results show that DSDA predict as many protein complexes as possible. And in Y78K network the accuracy of DSDA is as twice times as that of RNSC and MCL.     

两种胰蛋白酶酶解羊肌肉总蛋白样品的质谱分析

摘要: 目的比较国产和进口两种胰蛋白酶对蛋白质的酶解效果,为后续蛋白质组学稳定研究提供依据。方法用超声破碎法提取羊肌肉组织总蛋白,经两种胰蛋白酶酶解后液相色谱串联质谱检测酶解肽段,将结果上传蛋白质序列数据库,利用质谱分析鉴定方法分析比较两种胰蛋白酶的酶解效果,并借助生物信息学工具对所得数据进行分析。结果两种胰蛋白酶酶解同种蛋白质样品产生的肽段长度86%以上均为6-18 个氨基酸,适用于质谱检测。酶解后肽段产生的质量国产胰蛋白酶优于进口胰蛋白酶,国产胰蛋白酶比进口胰酶酶解可多鉴定到19% 的蛋白质和34%的肽段。结论进口、国产的胰蛋白酶在酶解蛋白质方面均可用于质谱检测前蛋白质的酶解消化。但国产胰蛋白酶价格明显低于进口胰酶,更具应用优势。本研究为评价胰蛋白酶酶解效果提供了一种有效、全面的研究方法。     

果蝇NOMPC相互作用蛋白的筛选与鉴定

NOMPC是果蝇感受触觉的机械力敏感离子通道,属于瞬时受体电位(TRP)离子通道家族,机械力敏感离子通道通过怎样的机制被机械力激活?与NOMPC相互作用的蛋白有哪些?为了研究这些问题,本研究从果蝇NOMPC全长cDNA中扩增得到其N端的29个锚蛋白重复序列(ARs),ORF长度为3 039bp.然后将这29个ARs构建到表达载体pUAST-EGFP上,转染果蝇S2细胞后,通过免疫沉淀、质谱分析和Western blot筛选和鉴定NOMPC相互作用的蛋白,实验筛选出NOMPC N端的29ARs和NOMPC全长的相互作用蛋白,通过免疫共沉淀(Co-IP)实验,对可能与NOMPC存在相互作用的蛋白质进行验证,鉴定出Annexin B9、CG3195、CG3731、CG5374与NOMPC存在相互作用,为进一步研究NOMPC介导触觉转导的分子机制提供了基础.     

Single-molecule imaging reveals mechanisms of protein disruption by a DNA translocase

In physiological settings, nucleic-acid translocases must act on substrates occupied by other proteins, and an increasingly appreciated role of translocases is to catalyse protein displacement from RNA and DNA. However, little is known regarding the inevitable collisions that must occur, and the fate of protein obstacles and the mechanisms by which they are evicted from DNA remain unexplored. Here we sought to establish the mechanistic basis for protein displacement from DNA using RecBCD as a model system. Using nanofabricated curtains of DNA and multicolour single-molecule microscopy, we visualized collisions between a model translocase and different DNA-bound proteins in real time. We show that the DNA translocase RecBCD can disrupt core RNA polymerase, holoenzymes, stalled elongation complexes and transcribing RNA polymerases in either head-to-head or head-to-tail orientations, as well as EcoRI(E111Q), lac repressor and even nucleosomes. RecBCD did not pause during collisions and often pushed proteins thousands of base pairs before evicting them from DNA. We conclude that RecBCD overwhelms obstacles through direct transduction of chemomechanical force with no need for specific protein-protein interactions, and that proteins can be removed from DNA through active disruption mechanisms that act on a transition state intermediate as they are pushed from one nonspecific site to the next.     

Analysis of correlations between protein complex and protein-protein interaction and mRNA expression

Protein-protein interaction is a physical interaction of two proteins in living cells. In budding yeast Saccharomyces cerevisiae, large-seale protein-protein interaction data have been obtained through high-throughput yeast two-hybrid systems (Y2H) and protein complex purification techniques based on mass-spectrometry. Here, we collect 11855 interactions between total 2617 proteins. Through seriate genome-wide mRNA expression data, similarity between two genes could be measured. Protein complex data can also be obtained publicly and can be translated to pair relationship that any two proteins can only exist in the same complex or not. Analysis of protein complex data, protein-protein interaction data and mRNA expression data can elucidate correlations between them. The results show that proteins that have interactions or similar expression patterns have a higher possibility to be in the same protein complex than randomized selected proteins, and proteins which have interactions and similar expression patterns are even more possible to exist in the same protein complex. The work indirates that comprehensive integration and analysis of public large-seale bioinformatical data, such as protein complex data, protein-protein interaction data and mRNA expression data, may help to uncover their relationships and common biological information underlying these data. The strategies described here may help to integrate and analyze other functional genomic and proteomic data, such as gene expression profiling, protein-localization mapping and large-scale phenotypic data, both in yeast and in other organisms.     

The molecular sociology of the cell

Proteomic studies have yielded detailed lists of the proteins present in a cell. Comparatively little is known, however, about how these proteins interact and are spatially arranged within the 'functional modules' of the cell: that is, the 'molecular sociology' of the cell. This gap is now being bridged by using emerging experimental techniques, such as mass spectrometry of complexes and single-particle cryo-electron microscopy, to complement traditional biochemical and biophysical methods. With the development of integrative computational methods to exploit the data obtained, such hybrid approaches will uncover the molecular architectures, and perhaps even atomic models, of many protein complexes. With these structures in hand, researchers will be poised to use cryo-electron tomography to view protein complexes in action within cells, providing unprecedented insights into protein-interaction networks.     

食管鳞癌淋巴结转移的蛋白质组分析

分析食管鳞癌转移淋巴结中鳞癌细胞与食管鳞癌组织中鳞癌细胞的蛋白质的表达差异,获取鉴别两者的分子标志物。用激光捕获显微切割技术分离出食管鳞癌转移淋巴结和食管鳞癌组织中较纯的鳞癌细胞,运用双向电泳和质谱的方法检测两者表达的差异蛋白,并用免疫印迹技术对差异候选蛋白进行分析、验证。发现29个差异蛋白点,通过质谱鉴定出6种有意义的蛋白,转移淋巴结中的鳞癌细胞中如peroxiredoxin 1等5种蛋白表达明显增高,1种蛋白MTCBP-1表达下调。因此激光捕获显微切割可以有效地解决组织异质性的问题;食管鳞癌组织中的鳞癌细胞与转移淋巴结中的鳞癌细胞的2-DE蛋白质图谱具有明显的差异表达,提示食管鳞癌的淋巴结转移过程的发生是多种蛋白质功能共同作用的结果,从而造成肿瘤细胞迁移性和侵袭性的进一步增强。     

A comprehensive analysis of protein-protein interactions in Saccharomyces cerevisiae

Two large-scale yeast two-hybrid screens were undertaken to identify protein-protein interactions between full-length open reading frames predicted from the Saccharomyces cerevisiae genome sequence. In one approach, we constructed a protein array of about 6,000 yeast transformants, with each transformant expressing one of the open reading frames as a fusion to an activation domain. This array was screened by a simple and automated procedure for 192 yeast proteins, with positive responses identified by their positions in the array. In a second approach, we pooled cells expressing one of about 6,000 activation domain fusions to generate a library. We used a high-throughput screening procedure to screen nearly all of the 6,000 predicted yeast proteins, expressed as Gal4 DNA-binding domain fusion proteins, against the library, and characterized positives by sequence analysis. These approaches resulted in the detection of 957 putative interactions involving 1,004 S. cerevisiae proteins. These data reveal interactions that place functionally unclassified proteins in a biological context, interactions between proteins involved in the same biological function, and interactions that link biological functions together into larger cellular processes. The results of these screens are shown here.     

Probing cellular protein complexes using single-molecule pull-down

Proteins perform most cellular functions in macromolecular complexes. The same protein often participates in different complexes to exhibit diverse functionality. Current ensemble approaches of identifying cellular protein interactions cannot reveal physiological permutations of these interactions. Here we describe a single-molecule pull-down (SiMPull) assay that combines the principles of a conventional pull-down assay with single-molecule fluorescence microscopy and enables direct visualization of individual cellular protein complexes. SiMPull can reveal how many proteins and of which kinds are present in the in vivo complex, as we show using protein kinase A. We then demonstrate a wide applicability to various signalling proteins found in the cytosol, membrane and cellular organelles, and to endogenous protein complexes from animal tissue extracts. The pulled-down proteins are functional and are used, without further processing, for single-molecule biochemical studies. SiMPull should provide a rapid, sensitive and robust platform for analysing protein assemblies in biological pathways.     

基于OFFGEL预分离二维液质联用技术在大鼠海马膜蛋白中的应用

以大鼠海马膜组分为研究对象,以等电聚焦OFFGEL为研究手段,结合反相液相色谱质谱联用技术,考察对酶切肽段的分离富集性能,同时结合DAVID分析工具对分离富集得到的酸性蛋白质进行的GO分析.结果表明,海马膜组分的酶切肽段经过OFFGEL分离后,得到24个不同馏分,每个馏分经过纳流液相色谱-质谱检测,发现有77% 的肽段专属于一个馏分,在酸性范围内的肽段等电点偏差较小,可以达到良好的聚焦效果;酸性蛋白的GO分析结果显示,质膜和物质的跨膜运输所占比例最大.OFFGEL作为一种预分离手段,可以应用于生物样品的大规模蛋白鉴定,在进一步蛋白质层面的生物功能研究中表现出良好的应用前景.     

聚苯乙烯为致孔剂的分子印迹膜对溶菌酶吸附性能的研究

探索聚苯乙烯微球的添加对于分子印迹膜对溶菌酶(Lysozyme, Lyz)吸附性能的影响.以溶菌酶为模板分子,丙烯酰胺、N,N'-亚甲基双丙烯酰胺为功能单体、聚苯乙烯(Polystyrene,PS)微球为致孔剂,制备聚苯乙烯为致孔剂的分子印迹聚合物膜(PS-MIP).PS-MIP的吸附平衡时间为30 min,短于未添加聚苯乙烯微球的分子印迹聚合物膜(MIP);PS-MIP与MIP对于Lyz的吸附能力均明显好于聚苯乙烯为致孔剂的非分子印迹聚合物膜(PS-NIP)与未添加聚苯乙烯微球的非分子印迹聚合物膜(NIP);PS-MIP对Lyz的选择性要好于MIP,而卵清蛋白和牛血清白蛋白在PS-MIP和MIP上的荧光信号没有差别.实验结果表明,在分子印迹膜聚合过程中添加聚苯乙烯微球,有利于缩短吸附时间,增大溶菌酶的吸附量并提升选择性.     

基于蛋白质相互作用网络的蛋白质复合物和功能模块预测算法研究进展

蛋白质相互作用网络中的模块化结构通常对应于蛋白质复合物或者蛋白质功能模块。基于蛋白质相互作用网络预测蛋白质复合物和功能模块不仅有助于理解生命有机体的细胞生物过程,而且可为探讨疾病的发生、发展和治疗以及合理的药物开发提供重要的基础。本文通过回顾近二十年来基于蛋白质相互作用网络的蛋白质复合物和功能模块预测算法研究的发展历程,按照静态蛋白质相互作用网络(SPIN)和动态蛋白质相互作用网络(DPIN)两个方向分别梳理预测算法所涉及的方法和技术,同时归纳常用的数据集并分析所面临的问题,为进一步研究提供有价值的参考。