Protein--protein interaction maps: a lead towards cellular functions

The availability of complete genome sequences now permits the development of tools for functional biology on a proteomic scale. Several experimental approaches or in silico algorithms aim at clustering proteins into networks with biological significance. Among those, the yeast two-hybrid system is the technology of choice to detect protein-protein interactions. Recently, optimized versions were applied at a genomic scale, leading to databases on the web. However, as with any other 'genetic' assay, yeast two-hybrid assays are prone to false positives and false negatives. Here we discuss these various technologies, their general limitations and the potential advances they make possible, especially when in combination with other functional genomics or bioinformatics analyses.     

A Novel Scoring Approach for Protein Co-Purification Data Reveals High Interaction Specificity

Large-scale protein interaction networks (PINs) have typically been discerned using affinity purification followed by mass spectrometry (AP/MS) and yeast two-hybrid (Y2H) techniques. It is generally recognized that Y2H screens detect direct binary interactions while the AP/MS method captures co-complex associations; however, the latter technique is known to yield prevalent false positives arising from a number of effects, including abundance. We describe a novel approach to compute the propensity for two proteins to co-purify in an AP/MS data set, thereby allowing us to assess the detected level of interaction specificity by analyzing the corresponding distribution of interaction scores. We find that two recent AP/MS data sets of yeast contain enrichments of specific, or high-scoring, associations as compared to commensurate random profiles, and that curated, direct physical interactions in two prominent data bases have consistently high scores. Our scored interaction data sets are generally more comprehensive than those of previous studies when compared against four diverse, high-quality reference sets. Furthermore, we find that our scored data sets are more enriched with curated, direct physical associations than Y2H sets. A high-confidence protein interaction network (PIN) derived from the AP/MS data is revealed to be highly modular, and we show that this topology is not the result of misrepresenting indirect associations as direct interactions. In fact, we propose that the modularity in Y2H data sets may be underrepresented, as they contain indirect associations that are significantly enriched with false negatives. The AP/MS PIN is also found to contain significant assortative mixing; however, in line with a previous study we confirm that Y2H interaction data show weak disassortativeness, thus revealing more clearly the distinctive natures of the interaction detection methods. We expect that our scored yeast data sets are ideal for further biological discovery and that our scoring system will prove useful for other AP/MS data sets.     

Identification of proteins that interact with a protein of interest: Applications of the yeast two-hybrid system

The yeast two-hybrid system is a molecular genetic test for protein interaction. Here we describe a step by step procedure to screen for proteins that interact with a protein of interest using the two-hybrid system. This process includes, construction and testing of the bait plasmid, screening a plasmid library for interacting fusion proteins, elimination of false positives and deletion analysis of true positives. This procedure is designed to allow investigators to identify proteins and their encoding cDNAs that have a biologically significant interaction with your protein of interest.     

Functional cloning by phage display

This review focusses on the isolation of proteins from genomic or cDNA expression products libraries displayed on phage. The use of phage display is highlighted for the characterization of binding proteins with diverse biological functions. Phage display is compared with another strategy, the yeast two-hybrid method. The combination of both strategies is especially powerful to eliminate false positives and to get information on the biochemical functions of proteins.     

Divergent Subcellular Locations of HTLV-I Tax and Int-6: A Contrast between in vitro Protein-Protein Binding and Intracellular Protein Colocalization

Protein-protein interactions define many important molecular and cellular processes in prokaryotic and eukaryotic biology. In trying to delineate the contact between two proteins, the yeast two-hybrid assay has emerged as a powerful technique. Complementing the yeast two-hybrid assay are in vitro techniques (e.g. GST-fusion-protein chromatography) that can also yield information on protein-protein associations. However, unambiguous functional significance to these interactions is best supported through a finding of colocalization of two proteins inside cells. In instances where two proteins interact in vitro but have divergent localizations within cells one needs to reconsider the biological importance of the former finding. Here, we present evidence for different subcellular locations of HTLV-I Tax and the Int-6 protein. We suggest a reexploration of the functional significance between Tax and Int-6 in cellular transformation.     

Genomic Libraries and a Host Strain Designed for Highly Efficient Two-Hybrid Selection in Yeast

The two-hybrid system is a powerful technique for detecting protein-protein interactions that utilizes the well-developed molecular genetics of the yeast Saccharomyces cerevisiae. However, the full potential of this technique has not been realized due to limitations imposed by the components available for use in the system. These limitations include unwieldy plasmid vectors, incomplete or poorly designed two-hybrid libraries, and host strains that result in the selection of large numbers of false positives. We have used a novel multienzyme approach to generate a set of highly representative genomic libraries from S. cerevisiae. In addition, a unique host strain was created that contains three easily assayed reporter genes, each under the control of a different inducible promoter. This host strain is extremely sensitive to weak interactions and eliminates nearly all false positives using simple plate assays. Improved vectors were also constructed that simplify the construction of the gene fusions necessary for the two-hybrid system. Our analysis indicates that the libraries and host strain provide significant improvements in both the number of interacting clones identified and the efficiency of two-hybrid selections.     

Media composition influences yeast one- and two-hybrid results

Although yeast two-hybrid experiments are commonly used to identify protein interactions, the frequent occurrence of false negatives and false positives hampers data interpretation. Using both yeast one-hybrid and two-hybrid experiments, we have identified potential sources of these problems: the media preparation protocol and the source of the yeast nitrogen base may not only impact signal range but also effect whether a result appears positive or negative. While altering media preparation may optimize signal differences for individual experiments, media preparation must be reported in detail to replicate studies and accurately compare results from different experiments.     

Protein Interaction Analysis of Senataxin and the ALS4 L389S Mutant Yields Insights into Senataxin Post-Translational Modification and Uncovers Mutant-Specific Binding with a Brain Cytoplasmic RNA-Encoded Peptide

Senataxin is a large 303 kDa protein linked to neuron survival, as recessive mutations cause Ataxia with Oculomotor Apraxia type 2 (AOA2), and dominant mutations cause amyotrophic lateral sclerosis type 4 (ALS4). Senataxin contains an amino-terminal protein-interaction domain and a carboxy-terminal DNA/RNA helicase domain. In this study, we focused upon the common ALS4 mutation, L389S, by performing yeast two-hybrid screens of a human brain expression library with control senataxin or L389S senataxin as bait. Interacting clones identified from the two screens were collated, and redundant hits and false positives subtracted to yield a set of 13 protein interactors. Among these hits, we discovered a highly specific and reproducible interaction of L389S senataxin with a peptide encoded by the antisense sequence of a brain-specific non-coding RNA, known as BCYRN1. We further found that L389S senataxin interacts with other proteins containing regions of conserved homology with the BCYRN1 reverse complement-encoded peptide, suggesting that such aberrant protein interactions may contribute to L389S ALS4 disease pathogenesis. As the yeast two-hybrid screen also demonstrated senataxin self-association, we confirmed senataxin dimerization via its amino-terminal binding domain and determined that the L389S mutation does not abrogate senataxin self-association. Finally, based upon detection of interactions between senataxin and ubiquitin–SUMO pathway modification enzymes, we examined senataxin for the presence of ubiquitin and SUMO monomers, and observed this post-translational modification. Our senataxin protein interaction study reveals a number of features of senataxin biology that shed light on senataxin normal function and likely on senataxin molecular pathology in ALS4.     

Yeast two-hybrid contributions to interactome mapping

Interactome mapping, the systematic identification of protein interactions within an organism, promises to facilitate systems-level studies of biological processes. Using in vitro technologies that measure specific protein interactions, static maps are being generated that include many of the protein networks that occur in vivo. Most of the binary protein interaction data currently available was generated by large-scale yeast two-hybrid screens. Recent efforts to map interactions in model organisms and in humans illustrate the promise and some of the limitations of the two-hybrid approach. Although these maps are incomplete and include false positives, they are proving useful as a framework around which to elaborate and model the in vivo interactome.     

Estimating gene regulatory networks and protein-protein interactions of Saccharomyces cerevisiae from multiple genome-wide data

MOTIVATION: Biological processes in cells are properly performed by gene regulations, signal transductions and interactions between proteins. To understand such molecular networks, we propose a statistical method to estimate gene regulatory networks and protein-protein interaction networks simultaneously from DNA microarray data, protein-protein interaction data and other genome-wide data. RESULTS: We unify Bayesian networks and Markov networks for estimating gene regulatory networks and protein-protein interaction networks according to the reliability of each biological information source. Through the simultaneous construction of gene regulatory networks and protein-protein interaction networks of Saccharomyces cerevisiae cell cycle, we predict the role of several genes whose functions are currently unknown. By using our probabilistic model, we can detect false positives of high-throughput data, such as yeast two-hybrid data. In a genome-wide experiment, we find possible gene regulatory relationships and protein-protein interactions between large protein complexes that underlie complex regulatory mechanisms of biological processes.     

大规模酵母双杂交技术研究蛋白质相互作用的应用

简介了酵母双杂交技术原理, 总结了酵母双杂交技术大规模筛选蛋白质相互作用的基础、应用及存在的问题。因为大规模酵母双杂交技术结果有大量假阳性及假阴性问题, 因此, 有条件情况下有必要同时开展其他方法的大规模蛋白相互作用研究, 以构建规模更大可信度更高的蛋白质相互作用网络图。     

Deciphering interactions used by the influenza virus NS1 protein to silence the host antiviral sensor protein RIG-I using a bacterial reverse two-hybrid system

The majority of biological processes are controlled and regulated by an intricate network of thousands of interacting proteins. Identifying and understanding the key components of these protein networks, especially those that play a critical role in disease, is a challenge that promises to dramatically alter our current approach to healthcare. To facilitate this process, we have developed a method for the rapid construction of a chromosomally integrated, bacterial reverse two-hybrid system (RTHS) that enables the identification of interacting protein partners. Chromosomal integration of the RTHS enables stable protein expression, free of plasmid copy-number effects, as well as eliminating false positives arising from plasmid ejection. We have utilized this approach to identify the interactions used by the influenza virus NS1 protein to silence the host's antiviral defences.     

利用酵母双杂交系统筛选水稻组蛋白去乙酰化酶HDA705的互作蛋白

为了解水稻(Oryza sativa)组蛋白去乙酰化酶HDA705的生物学功能,构建了HDA705酵母双杂交诱饵表达载体与双杂交文库,并筛选了与HDA705相互作用的蛋白。结果表明,HDA705的诱饵载体无自激活活性且对酵母无毒性作用,文库的滴度也适合常规的酵母双杂交文库筛选。通过对酵母双杂交文库的筛选,共获得了164个阳性克隆,经DNA测序分析,这些克隆编码47个可能与HDA705相互作用的蛋白,其中包括3个在逆境响应或激素信号转导过程中起到重要作用的(辅)转录因子、6个参与光合作用的叶绿体蛋白、1个含有R3H结构域的蛋白以及22种酶类等。这为进一步研究HDA705的生物学功能提供了重要的线索。     

细菌双杂交筛选大豆GmWNK1互作蛋白系统的建立及应用

本研究利用大肠杆菌双杂交系统构建了一个高质量的大豆根系cDNA文库,同时利用大肠杆菌双杂交表达载体pBT构建了融合表达质粒pBT．GmWNK1,经酶切和测序鉴定、诱饵融合蛋白的表达检测及诱饵融合蛋白的自激活鉴定后作为诱饵,从大豆根部cDNA文库中筛选与GmWNK1发生互作的蛋白质,共获得18个阳性克隆。经测序和同源性比对发现,有10个阳性克隆编码已知蛋白,8个为假阳性。研究结果为揭示WNK基因家族的生物学功能和调控机制提供了重要的参考数据和研究材料。     

Network compression as a quality measure for protein interaction networks

With the advent of large-scale protein interaction studies, there is much debate about data quality. Can different noise levels in the measurements be assessed by analyzing network structure? Because proteomic regulation is inherently co-operative, modular and redundant, it is inherently compressible when represented as a network. Here we propose that network compression can be used to compare false positive and false negative noise levels in protein interaction networks. We validate this hypothesis by first confirming the detrimental effect of false positives and false negatives. Second, we show that gold standard networks are more compressible. Third, we show that compressibility correlates with co-expression, co-localization, and shared function. Fourth, we also observe correlation with better protein tagging methods, physiological expression in contrast to over-expression of tagged proteins, and smart pooling approaches for yeast two-hybrid screens. Overall, this new measure is a proxy for both sensitivity and specificity and gives complementary information to standard measures such as average degree and clustering coefficients.     

酵母双杂交技术筛选并回转验证在胞内与PML-C结构域相互作用的蛋白

目的 利用酵母双杂交技术在活细胞内筛选并回转验证与PML-C结构域相互作用的蛋白质.方法 通过诱饵质粒pGBKT7-PML-C,利用酵母双杂交系统从白血病细胞cDNA文库中筛选与PML-C结构域相互作用的蛋白质.结果 利用酵母双杂交技术筛选到43个能与PML-C结构域相互作用的克隆;经进一步的归类与酵母回转试验得到9个阳性克隆.结论 在细胞内PML-C结构域能与多种蛋白质有相互作用.中性粒细胞弹性蛋白酶（neutrophil elastase,NE）介导的急性早幼粒细胞白血病的发生可能与这些相互作用所致的生物学功能改变有关.     

酵母双杂交系统筛选GATA-1相互作用蛋白质及功能验证

目的 利用酵母双杂交技术从人脑cDNA文库中筛选与人GATA-1相互作用的蛋白质.方法 从人K562细胞中扩增出全长GATA1基因,设计引物将其3段截断体亚克隆入酵母表达载体pDBLeu中,转化至AH109感受态酵母中,利用酵母双杂交技术筛选人脑cDNA文库中与其相互作用的蛋白质,阳性克隆通过回转及免疫共沉淀试验进行验证,利用3xGATA荧光素酶报告基因对相互作用蛋白质进行功能验证.结果 成功构建出酵母诱饵蛋白表达质粒pDBLeu-GATA1（1）,pDBLeu-GATA1（2）,pDBLeu-GATA1（3）,筛到34个阳性克隆,用生物信息学分析及回转验证得到5个与GATA-1相互作用的候选蛋白,通过免疫共沉淀试验进一步验证,获得3个蛋白质能与GATA-1相互作用,分别是ECSIT,EFEMP1和GPS2.荧光素酶试验表明这3个蛋白质均能对GATA1的转录活性产生影响,证实它们之间的相互作用具有影响GATA1转录的功能.结论 应用酵母双杂交技术及免疫共沉淀试验,从人脑cDNA文库中成功获得3个与GATA-1相互作用并对其转录活性具有调节作用的蛋白质,为研究GATA1蛋白质的功能提供了新的线索.