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.     

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.     

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.     

Prediction of the structure of a receptor-protein complex using a binary docking method.

To validate procedures of rational drug design, it is important to develop computational methods that predict binding sites between a protein and a ligand molecule. Many small molecules have been tested using such programs, but examination of protein-protein and peptide-protein interactions has been sparse. We were able to test such applications once the structures of both the maltose-binding protein (MBP) and the ligand-binding domain of the aspartate receptor, which binds MBP, became available. Here we predict the binding site of MBP to its receptor using a 'binary docking' technique in which two MBP octapeptide sequences containing mutations that eliminate maltose chemotaxis are independently docked to the receptor. The peptides in the docked solutions superimpose on their original positions in the structure of MBP and allow the formation of an MBP-receptor complex. The consistency of the computational and biological results supports this approach for predicting protein-protein and peptide-protein interactions.     

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.     

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.     

用于深度图内3—D物体识别的表面特性

本文以精确的数学形式重新定义深度图物体的识别为广义道集合映射。由于怎样有效地计算此类映射还没有通用的理论,因此,我们提出基于物体表面特性和表面匹配的计算理论。此理论对深入研究与分析深度图物体识别是十分有用的。     

Global landscape of protein complexes in the yeast Saccharomyces cerevisiae

Identification of protein-protein interactions often provides insight into protein function, and many cellular processes are performed by stable protein complexes. We used tandem affinity purification to process 4,562 different tagged proteins of the yeast Saccharomyces cerevisiae. Each preparation was analysed by both matrix-assisted laser desorption/ionization-time of flight mass spectrometry and liquid chromatography tandem mass spectrometry to increase coverage and accuracy. Machine learning was used to integrate the mass spectrometry scores and assign probabilities to the protein-protein interactions. Among 4,087 different proteins identified with high confidence by mass spectrometry from 2,357 successful purifications, our core data set (median precision of 0.69) comprises 7,123 protein-protein interactions involving 2,708 proteins. A Markov clustering algorithm organized these interactions into 547 protein complexes averaging 4.9 subunits per complex, about half of them absent from the MIPS database, as well as 429 additional interactions between pairs of complexes. The data (all of which are available online) will help future studies on individual proteins as well as functional genomics and systems biology.     

遗传作图软件应用及辅助软件的研制

介绍了当前普遍用于遗传图谱构建和ＱＴＬ定位的软件ＭＡＰＭＡＫＥＲ３．０（ｆｏｒＰＣ）的功能、数据结构和基本操作命令与步骤；指出了该软件存在的问题与不足。介绍了作者开发的用于遗传图谱构建中方便研究者建立符合ＭＡＰＭＡＫＥＲ要求的分析数据文件，以及对标记的分离比进行检验的辅助软件ＭＤＡＣ。提出了进一步开发中文版新一代遗传作图软件、建立基因组图谱数据库和基于因特网（Ｉｎｔｅｒｎｅｔ）的基因组信息检索等设想。     

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.     

蛋白质-蛋白质相互作用的实验检测方法

生物体内的蛋白质分子常常通过与其他蛋白质分子发生相互作用来发挥其生物功能. 因此, 研究蛋白质-蛋白质相互作用 (protein-protein interaction, PPI) 对于阐明蛋白质分子的生物功能以及分子作用机理具有重要的意义. 主要介绍基于生物物理和生物化学原理的检测蛋白质-蛋白质相互作用的实验研究方法, 并对发展趋势做出展望.     

基于酵母基因组高通量数据的基因-基因相互作用预测

后基因组时代的显著特点是大规模基因组和蛋白质组实验平台所产生的大量高通量数据,整合并利用基因组和蛋白组信息成为这一时代的主要挑战之一. 因此,基因-基因相互作用将有助于理解细胞内基因之间的相互作用以及信号传导通路研究提供有价值的参考. 为预测酵母基因组中基因-基因相互作用,我们利用高通量数据中的蛋白-蛋白相互作用、遗传表型数据、基因微阵列表达数据以及功能基因注释数据等来分析酵母中的基因-基因相互作用. 本文建立的预测方法为在系统水平上理解酵母基因组中的基因功能提供了依据,也为揭示酵母基因组中的基因-基因相互作用网络奠定理论基础.     

Reconstruction of linkage maps in the distorted segregation populations of backcross, doubled haploid and recombinant inbred lines

Non-Mendelian segregation of markers, known as distorted segregation, is a common biological phenomenon. Although segregation distortion affects the estimation of map distances and the results of quantitative trait loci (QTL) mapping, the effects of distorted markers are often ignored in the construction of linkage maps and in QTL mapping. Recently, we have developed a multipoint method via a Hidden Markov chain method to reconstruct linkage maps in an F2 population that corrects for bias of map distances between distorted markers. In this article, the method is extended to cover backcross, doubled haploid and recombinant inbred line (RIL) populations. The results from simulated experiments show that: (1) the degree that two linked segregation distortion loci (SDL) affect the estimation of map distances increases as SDL heritability and interval length between adjacent markers increase, whereas sample size has little effect on the bias; (2) two linked SDL result in the underesti- mation of linkage distances for most cases, overestimation for an additive model with opposite additive effects, and unbiased estimation for an epistatic model with negative additive-by-additive effects; (3) the proposed method can obtain the unbiased estimation of linkage distance. This new method was applied to a rice RIL population with severely distorted segregation to reconstruct the linkage maps, and a bootstrap method was used to obtain 95% confidence intervals of map distances. The results from real data analysis further demonstrate the utility of our method, which provides a foundation for the inheritance analysis of quantitative and viability traits.     

Identifying changed protein-protein interactions in biological processes by gene coexpression analysis

The interaction strength between 2 proteins is not constant but variable under different conditions. For a given biological process, identification of protein-protein interactions (PPIs) undergoing dynamic change in interaction strength is highly valuable but never achieved before. In this work, we presented a computational approach to identify changed PPIs (cPPIs) on a global scale by analyzing the coexpression level of genes encoding the interacting protein pairs. This approach stemmed from the biological...     

基于MODIS数据的生物保护区域土地覆被分类

中分辨率(250 m和500 m)MODIS数据比1 km分辨率的AVHRR具有更高的空间和光谱分辨率,在区域尺度上土地利用/覆盖得到了广泛的应用.该文主要探讨了如何在生物保护中利用MODIS数据获得区域土地覆被分类信息.采用决策树和最大似然法相结合的分类方法,对MODIS数据进行了生物保护区域土地覆被分类制图,并利用Landsat TM土地覆被制图作为参考数据对MODIS数据土地覆被制图进行了精度评价.结果表明,利用MODIS数据在区域尺度上可以获取令人满意的土地覆被分类.     

帐篷映射的几何构造方法

利用几何方法构造了一种区间映射的混沌集,它是Cantor集,而且这种区间映射本质是帐篷映射.     

基于自然柱状特征地图的智能车定位

针对室外环境中手工测量柱状自然特征建立环境的特征地图(简称柱图)工作量大、精度低的问题,提出了一种基于激光雷达的地图自动生成方法.在此基础上,采用基于柱图的定位方法,使用迭代最近点算法进行地图匹配,提高了定位精度.仿真数据和实际数据的实验结果表明,该方法具有精度高、速度快等特点.     

度量空间中强链回归点集的研究

研究了紧致度量空间中连续自映射强链回归点集的动力学性质,利用映射的一致收敛性,得到了强链回归点的一些结论:同胚映射f的强链回点集等于它的逆映射f-1的强链回归点集;同胚映射f的强链回归点集对f强不变;连续映射f限制在它的强链回归点集上形成的强链回归点集就是连续映射f在度量空间上形成的强链回归点集.最后给出一个例子,表明了强链回归点的概念不同于链回归点的概念.这些结论推广和改进了早期文献中链回归点的相关结果.