Protein–protein interactions and selection: yeast-based approaches that exploit guanine nucleotide-binding protein signaling

For elucidating protein–protein interactions, many methodologies have been developed during the past two decades. For investigation of interactions inside cells under physiological conditions, yeast is an attractive organism with which to quickly screen for hopeful candidates using versatile genetic technologies, and various types of approaches are now available.Among them, a variety of unique systems using the guanine nucleotide-binding protein (G-protein) signaling pathway in yeast have been established to investigate the interactions of proteins for biological study and pharmaceutical research. G-proteins involved in various cellular processes are mainly divided into two groups: small monomeric G-proteins,and heterotrimeric G-proteins. In this minireview, we summarize the basic principles and applications of yeast-based screening systems, using these two types of G-protein, which are typically used for elucidating biological protein interactions but are differentiated from traditional yeast two-hybrid systems.     

用于蛋白质间相互作用研究的新型双杂交系统

近年来,一些不依赖于转录因子活性的新型双杂交系统相继建立,如分离的泛素系统、蛋白质片段互补分析、阻遏物重构分析和SOS恢复系统等。同利用转录因子活性的酵母双杂交系统相似,这些方法也利用了一些活性蛋白的结构与功能特点来研究蛋白质间相互作用,这些活性蛋白不是转录因子,但也可在结构上进行分离可通过重构使其生物活性得以恢复。由于这些新型双杂交系统的各自特点,使得它们成为酵母双杂交系统的有益补充和研究蛋白质间相互作用的有力工具。     

酵母双杂合系统的改进和发展

酵母双杂合系统是在１９８９年由ＳｔａｎｌｅｙＦｉｅｌｄｓ和Ｏｋ－ｋｙｕＳｏｎｇ等提出并初步建立的［１］,该系统是在酿酒酵母（Ｓａｃｈａｒｏｍｙｃｅｓｃｅｒｅｖｉｓｉａｅ）中研究蛋白质间相互作用的一种非常有效的分子生物学方法。近几年来随着人们对该系统的广泛应用,这一系统得到了不断的完善及改进,同时也衍生出单杂合系统,三杂合系统等一系列相关的技术。这些技术在不同研究领域中的广泛应用有力地推动了蛋白质与ＤＮＡ,蛋白质与ＲＮＡ,以及多种蛋白质分子间相互作用的研究。     

Protein recruitment systems for the analysis of protein +/- protein interactions

The yeast Saccharomyces cerevisiae serves as an excellent genetic tool for the analysis of protein +/- protein interactions. The most common system, used to date, is the two-hybrid system. Although proven very powerful, the two-hybrid system exhibits several inherent problems and limitations. Recently, two alternative systems have been described that take advantage of the fact that localization of signal transduction effectors to the inner leaflet of the plasma membrane is absolutely necessary for yeast viability. These effectors can either be the Ras guanyl nucleotide exchange factor or Ras itself. The yeast strain used in both systems is a temperature-sensitive mutant in the yeast Ras guanyl nucleotide exchange factor, CDC25. Membrane localization of these effectors is achieved via protein +/- protein interaction. Each system can be used to test interaction between known protein pairs, as well as for isolation of novel protein interactions. Described here are the scientific and technical steps to be considered for both protein recruitment systems.     

Examining post‐translational modification‐mediated protein–protein interactions using a chemical proteomics approach

Post‐translational modifications (PTM) of proteins can control complex and dynamic cellular processes via regulating interactions between key proteins. To understand these regulatory mechanisms, it is critical that we can profile the PTM‐dependent protein–protein interactions. However, identifying these interactions can be very difficult using available approaches, as PTMs can be dynamic and often mediate relatively weak protein–protein interactions. We have recently developed CLASPI (cross‐linking‐assisted and stable isotope labeling in cell culture‐based protein identification), a chemical proteomics approach to examine protein–protein interactions mediated by methylation in human cell lysates. Here, we report three extensions of the CLASPI approach. First, we show that CLASPI can be used to analyze methylation‐dependent protein–protein interactions in lysates of fission yeast, a genetically tractable model organism. For these studies, we examined trimethylated histone H3 lysine‐9 (H3K9Me₃)‐dependent protein–protein interactions. Second, we demonstrate that CLASPI can be used to examine phosphorylation‐dependent protein–protein interactions. In particular, we profile proteins recognizing phosphorylated histone H3 threonine‐3 (H3T3‐Phos), a mitotic histone “mark” appearing exclusively during cell division. Our approach identified survivin, the only known H3T3‐Phos‐binding protein, as well as other proteins, such as MCAK and KIF2A, that are likely to be involved in weak but selective interactions with this histone phosphorylation “mark”. Finally, we demonstrate that the CLASPI approach can be used to study the interplay between histone H3T3‐Phos and trimethylation on the adjacent residue lysine 4 (H3K4Me₃). Together, our findings indicate the CLASPI approach can be broadly applied to profile protein–protein interactions mediated by PTMs.     

A systematic study of yeast sterol biosynthetic protein-protein interactions using the split-ubiquitin system

Sterol biosynthesis occurs in the ER and most sterol biosynthetic enzymes have transmembrane domains. However, due to difficulties in characterizing membrane protein-protein interactions, the nature of the sterol biosynthetic complex as well as in vivo interactions between various enzymes have not been described. We employed a split-ubiquitin membrane protein yeast two-hybrid system to characterize interactions between sterol biosynthetic proteins. Fourteen bait constructs were co-transformed into a reporter yeast strain with 14 prey constructs representing all sterol enzymatic reactions beginning with the synthesis of squalene. Our results not only confirmed several previous interactions, but also allowed us to identify novel interactions. Based on these results, ergosterol biosynthetic enzymes display specific protein-protein interactions forming a functional complex we designate, the ergosome. In this complex, Erg11p, Erg25p, Erg27p, and Erg28p appear to form a core center that can interact with other enzymes in the pathway. Also Erg24p and Erg2p, two enzymes that are sensitive to morpholine antifungals, appear to interact with one another; however, the profile of protein interaction partners appears to be unique. Erg2p and Erg3p, two enzymes catalyzing sequential reactions also appear to have different interaction partners. Our results provide a working model as to how sterol biosynthetic enzymes are topologically organized not only in yeast but in plant and animal systems that share many of these biosynthetic reactions.     

Protein-protein interactions among the components of the biosynthetic machinery responsible for exopolysaccharide production in Streptococcus thermophilus MR-1C

Aim: This study identified protein–protein interactions among the biosynthetic machinery responsible for exopolysaccharide (EPS) production in Streptococcus thermophilus MR‐1C. Methods and Results: Protein–protein interactions were investigated using the yeast two‐hybrid system. A strong protein–protein interaction was detected between the transmembrane activation protein Wzd and the protein tyrosine kinase Wze. Weaker protein–protein interactions were detected between two duplicate Wze proteins and between Wze and the phosphotyrosine phosphatase Wzh. Protein–protein interactions involving a Wzd/Wze fusion protein and Wzd and Wze may indicate that these proteins form multi‐protein complexes. All combinations of the Wzh, Wzd, Wze, Wzg (regulation), CpsE (glycosyl‐1‐phosphate transferase), CpsS (polymerization), CpsL (unknown), CpsW (regulation) and CpsU (membrane translocation) were analysed for protein–protein interactions but no additional interactions were discovered using the yeast two‐hybrid system. Conclusions: Interactions among the phosphotyrosine phosphatase, tyrosine kinase, and transmembrane activation protein are important in the regulation of capsule biosynthesis in Strep. thermophilus MR‐1C. Significance and Impact of the Study: This study provides some valuable insight into the organization and interactions between the many proteins involved in EPS production. A better understanding of this process may facilitate the genetic manipulation of capsule production to impart desirable properties to dairy starter cultures.     

Electron‐deficient p‐benzoyl‐l‐phenylalanine derivatives increase covalent chemical capture yields for protein–protein interactions

The photoactivatable amino acid p‐benzoyl‐l ‐phenylalanine (pBpa) has been used for the covalent capture of protein–protein interactions (PPIs) in vitro and in living cells. However, this technique often suffers from poor photocrosslinking yields due to the low reactivity of the active species. Here we demonstrate that the incorporation of halogenated pBpa analogs into proteins leads to increased crosslinking yields for protein–protein interactions. The analogs can be incorporated into live yeast and upon irradiation capture endogenous PPIs. Halogenated pBpas will extend the scope of PPIs that can be captured and expand the toolbox for mapping PPIs in their native environment.     

GENETIC APPROACHES TO THE IDENTIFICATION OF INTERACTIONS BETWEEN MEMBRANE PROTEINS IN YEAST

ABSTRACT

The recent sequencing of entire eukaryotic genomes has renewed the interest in identifying and characterizing all gene products that are expressed in a given organism. The characterization of unknown gene products is facilitated by the knowledge of its binding partners. Thus, a novel protein may be classified by identifying previously characterized proteins that interact with it. If such an approach is carried out on a large scale, it may allow the rapid characterization of the thousands of predicted open reading frames identified by recent sequencing projects. Currently, the yeast two-hybrid system is the most widely used genetic assay for the detection of protein–protein interactions. The yeast two-hybrid system has become popular because it requires little individual optimization and because, as compared to conventional biochemical methods, the identification and characterization of protein–protein interactions can be completed in a relatively short time span. In this review, we briefly discuss the yeast two-hybrid system and its application to large scale screening studies that aim at deciphering all protein–protein interactions taking place in a given cell type or organism. We then focus on a class of proteins that is unsuitable for conventional yeast two-hybrid systems, namely integral membrane proteins and membrane-associated proteins, and describe several novel genetic systems that combine the advantages of the yeast two-hybrid system with the potential to identify interaction partners of membrane-associated proteins in their natural setting.     

发展中的酵母杂交体系

酵母杂交体系包括双杂交、反向双杂交和三杂交等体系。双杂交作为一种新兴的体内研究蛋白质之间相互作用的方法,已经得到了广泛的应用。而反向双杂交和三杂交系统是在双杂交基础上发展起来的两种新技术。反向双杂交除了筛选突变株,以获取蛋白质结合的信息外,还能发现可导致已知蛋白质间特异相互作用发生解离的肽类或其他小分子物质,进一步分析蛋白质间作用位点、调控。三杂交系统则在蛋白质与小分子配基之间以及多种蛋白质之间相     

Lysine methylation modulates the protein–protein interactions of yeast cytochrome C Cyc1p

In recent years, protein methylation has been established as a major intracellular PTM. It has also been proposed to modulate protein‐protein interactions (PPIs) in the interactome. To investigate the effect of PTMs on PPIs, we recently developed the conditional two‐hybrid (C2H) system. With this, we demonstrated that arginine methylation can modulate PPIs in the yeast interactome. Here, we used the C2H system to investigate the effect of lysine methylation. Specifically, we asked whether Ctm1p‐mediated trimethylation of yeast cytochrome c Cyc1p, on lysine 78, modulates its interactions with Erv1p, Ccp1p, Cyc2p and Cyc3p. We show that the interactions between Cyc1p and Erv1p, and between Cyc1p and Cyc3p, are significantly increased upon trimethylation of lysine 78. This increase of interaction helps explain the reported facilitation of Cyc1p import into the mitochondrial intermembrane space upon methylation. This first application of the C2H system to the study of methyllysine‐modulated interactions further confirms its robustness and flexibility.     

Interactive learning: Lessons from two hybrids over two decades

The initial yeast two‐hybrid experiment – published in 1989 – described an approach to detecting protein–protein interactions that has flourished over the last two decades, leading to the assembly of large‐scale data sets of these interactions. Yet the yeast assay originated because of the laboratory's interests in technology development, not because of its need to identify partners of any protein then under study. In addition to such motivating forces, other features of the process of originating a technology can be revealed by considering the lessons of the two‐hybrid approach. These include the value of timeliness in a method's development, the willingness of an investigator to try experimental approaches that prove fruitless, the ability of biological macromolecules to display surprising attributes, the benefits of a community expending efforts to expand the uses of a technology platform, and the role of scientific training of those who work in technology.     

Purification and characterization of HIV–human protein complexes

To fully understand how pathogens infect their host and hijack key biological processes, systematic mapping of intra-pathogenic and pathogen–host protein–protein interactions (PPIs) is crucial. Due to the relatively small size of viral genomes (usually around 10–100 proteins), generation of comprehensive host–virus PPI maps using different experimental platforms, including affinity tag purification-mass spectrometry (AP-MS) and yeast two-hybrid (Y2H) approaches, can be achieved. Global maps such as these provide unbiased insight into the molecular mechanisms of viral entry, replication and assembly. However, to date, only two-hybrid methodology has been used in a systematic fashion to characterize viral–host protein–protein interactions, although a deluge of data exists in databases that manually curate from the literature individual host–pathogen PPIs. We will summarize this work and also describe an AP-MS platform that can be used to characterize viral-human protein complexes and discuss its application for the HIV genome.     

Yeast "N"-hybrid systems for protein-protein and drug-protein interaction discovery

The majority of small molecule drugs act on protein targets to exert a therapeutic function. It has become apparent in recent years that many small molecule drugs act on more than one particular target and consequently, approaches which profile drugs to uncover their target binding spectrum have become increasingly important. Classical yeast two-hybrid systems have mainly been used to discover and characterize protein-protein interactions, but recent modifications and improvements have opened up new routes towards screening for small molecule-protein interactions. Such yeast "n"-hybrid systems hold great promise for the development of drugs which interfere with protein-protein interactions and for the discovery of drug-target interactions. In this review, we discuss several yeast two-hybrid based approaches with applications in drug discovery and describe a protocol for yeast three-hybrid screening of small molecules to identify their direct targets.     

Evaluation of different biological data and computational classification methods for use in protein interaction prediction

Protein–protein interactions play a key role in many biological systems. High‐throughput methods can directly detect the set of interacting proteins in yeast, but the results are often incomplete and exhibit high false‐positive and false‐negative rates. Recently, many different research groups independently suggested using supervised learning methods to integrate direct and indirect biological data sources for the protein interaction prediction task. However, the data sources, approaches, and implementations varied. Furthermore, the protein interaction prediction task itself can be subdivided into prediction of (1) physical interaction, (2) co‐complex relationship, and (3) pathway co‐membership. To investigate systematically the utility of different data sources and the way the data is encoded as features for predicting each of these types of protein interactions, we assembled a large set of biological features and varied their encoding for use in each of the three prediction tasks. Six different classifiers were used to assess the accuracy in predicting interactions, Random Forest (RF), RF similarity‐based k‐Nearest‐Neighbor, Naïve Bayes, Decision Tree, Logistic Regression, and Support Vector Machine. For all classifiers, the three prediction tasks had different success rates, and co‐complex prediction appears to be an easier task than the other two. Independently of prediction task, however, the RF classifier consistently ranked as one of the top two classifiers for all combinations of feature sets. Therefore, we used this classifier to study the importance of different biological datasets. First, we used the splitting function of the RF tree structure, the Gini index, to estimate feature importance. Second, we determined classification accuracy when only the top‐ranking features were used as an input in the classifier. We find that the importance of different features depends on the specific prediction task and the way they are encoded. Strikingly, gene expression is consistently the most important feature for all three prediction tasks, while the protein interactions identified using the yeast‐2‐hybrid system were not among the top‐ranking features under any condition. Proteins 2006. © 2006 Wiley‐Liss, Inc.     

Disulfide trapping of protein complexes on the yeast surface

Protein complexes are common in nature and play important roles in biology, but studying the quaternary structure formation in vitro is challenging since it involves lengthy and expensive biochemical steps. There are frequent technical difficulties as well with the sensitivity and resolution of the assays. In this regard, a technique that can analyze protein–protein interactions in high throughput would be a useful experimental tool. Here, we introduce a combination of yeast display and disulfide trapping that we refer to as stabilization of transient and unstable complexes by engineered disulfide (STUCKED) that can be used to detect the formation of a broad spectrum of protein complexes on the yeast surface using fluorescence labeling. The technique uses an engineered intersubunit disulfide to covalently crosslink the subunits of a complex, so that the disulfide‐trapped complex can be displayed on the yeast surface for detection and analysis. Transient protein complexes are difficult to display on the yeast surface, since they may dissociate before they can be detected due to a long induction period in yeast. To this end, we show that three different quaternary structures with the subunit dissociation constant K_d ～ 0.5–20 µM, the antibody variable domain (Fv), the IL‐8 dimer, and the p53–MDM2 complex, cannot be displayed on the yeast surface as a noncovalent complex. However, when we introduce an interchain disulfide between the subunits, all three systems are efficiently displayed on the yeast surface, showing that disulfide trapping can help display protein complexes that cannot be displayed otherwise. We also demonstrate that a disulfide forms only between the subunits that interact specifically, the displayed complexes exhibit functional characteristics that are expected of wt proteins, the mutations that decrease the affinity of subunit interaction also reduce the display efficiency, and most of the disulfide stabilized complexes are formed within the secretory pathway during export to the surface. Disulfide crosslinking is therefore a convenient way to study weak protein association in the context of yeast display. Biotechnol. Bioeng. 2010; 106: 27–41. © 2009 Wiley Periodicals, Inc.