Quantitative analysis of protein interaction network dynamics in yeast

Many cellular functions are mediated by protein–protein interaction networks, which are environment dependent. However, systematic measurement of interactions in diverse environments is required to better understand the relative importance of different mechanisms underlying network dynamics. To investigate environment‐dependent protein complex dynamics, we used a DNA‐barcode‐based multiplexed protein interaction assay in Saccharomyces cerevisiae to measure in vivo abundance of 1,379 binary protein complexes under 14 environments. Many binary complexes (55%) were environment dependent, especially those involving transmembrane transporters. We observed many concerted changes around highly connected proteins, and overall network dynamics suggested that “concerted” protein‐centered changes are prevalent. Under a diauxic shift in carbon source from glucose to ethanol, a mass‐action‐based model using relative mRNA levels explained an estimated 47% of the observed variance in binary complex abundance and predicted the direction of concerted binary complex changes with 88% accuracy. Thus, we provide a resource of yeast protein interaction measurements across diverse environments and illustrate the value of this resource in revealing mechanisms of network dynamics.     

Dynamical analysis of yeast protein interaction network during the sake brewing process

Proteins interact with each other for performing essential functions of an organism. They change partners to get involved in various processes at different times or locations. Studying variations of protein interactions within a specific process would help better understand the dynamic features of the protein interactions and their functions. We studied the protein interaction network of Saccharomyces cerevisiae (yeast) during the brewing of Japanese sake. In this process, yeast cells are exposed to several stresses. Analysis of protein interaction networks of yeast during this process helps to understand how protein interactions of yeast change during the sake brewing process. We used gene expression profiles of yeast cells for this purpose. Results of our experiments revealed some characteristics and behaviors of yeast hubs and non-hubs and their dynamical changes during the brewing process. We found that just a small portion of the proteins (12.8 to 21.6%) is responsible for the functional changes of the proteins in the sake brewing process. The changes in the number of edges and hubs of the yeast protein interaction networks increase in the first stages of the process and it then decreases at the final stages.     

Stoichiometry of lipid-protein interaction and integral membrane protein structure

The stoichiometries of lipid-protein interaction obtained from spin label electron spin resonance experiments with integral membrane proteins are compared with simple geometric models for the intramembranous perimeter that are based on the predicted numbers of transmembrane helices. Deviations from the predicted values provide evidence for oligomerization of the protein in the membrane and/or more complex arrangements of the transmembrane segments. Received: 16 January 1997 / Accepted: 5 March 1997     

Functional evolution of the yeast protein interaction network

Protein interactions are central to most biological processes. We investigated the dynamics of emergence of the protein interaction network of Saccharomyces cerevisiae by mapping origins of proteins on an evolutionary tree. We demonstrate that evolutionary periods are characterized by distinct connectivity levels of the emerging proteins. We found that the most-connected group of proteins dates to the eukaryotic radiation, and the more ancient group of pre-eukaryotic proteins is less connected. We show that functional classes have different average connectivity levels and that the time of emergence of these functional classes parallels the observed connectivity variation in evolution. We take these findings as evidence that the evolution of function might be the reason for the differences in connectivity throughout evolutionary time. We propose that the understanding of the mechanisms that generate the scale-free protein interaction network, and possibly other biological networks, requires consideration of protein function.     

Molecular basis for evolving modularity in the yeast protein interaction network

Scale-free networks are generically defined by a power-law distribution of node connectivities. Vastly different graph topologies fit this law, ranging from the assortative, with frequent similar-degree node connections, to a modular structure. Using a metric to determine the extent of modularity, we examined the yeast protein network and found it to be significantly self-dissimilar. By orthologous node categorization, we established the evolutionary trend in the network, from an “emerging” assortative network to a present-day modular topology. The evolving topology fits a generic connectivity distribution but with a progressive enrichment in intramodule hubs that avoid each other. Primeval tolerance to random node failure is shown to evolve toward resilience to hub failure, thus removing the fragility often ascribed to scale-free networks. This trend is algorithmically reproduced by adopting a connectivity accretion law that disfavors like-degree connections for large-degree nodes. The selective advantage of this trend relates to the need to prevent a failed hub from inducing failure in an adjacent hub. The molecular basis for the evolutionary trend is likely rooted in the high-entropy penalty entailed in the association of two intramodular hubs.     

Modularity in the evolution of yeast protein interaction network

Protein interaction networks are known to exhibit remarkable structures: scale-free and small-world and modular structures. To explain the evolutionary processes of protein interaction networks possessing scale-free and small-world structures, preferential attachment and duplication-divergence models have been proposed as mathematical models. Protein interaction networks are also known to exhibit another remarkable structural characteristic, modular structure. How the protein interaction networks became to exhibit modularity in their evolution? Here, we propose a hypothesis of modularity in the evolution of yeast protein interaction network based on molecular evolutionary evidence. We assigned yeast proteins into six evolutionary ages by constructing a phylogenetic profile. We found that all the almost half of hub proteins are evolutionarily new. Examining the evolutionary processes of protein complexes, functional modules and topological modules, we also found that member proteins of these modules tend to appear in one or two evolutionary ages. Moreover, proteins in protein complexes and topological modules show significantly low evolutionary rates than those not in these modules. Our results suggest a hypothesis of modularity in the evolution of yeast protein interaction network as systems evolution.     

A novel approach for the identification of protein–protein interaction with integral membrane proteins

Protein–protein interaction plays a major role in all biological processes. The currently available genetic methods such as the two-hybrid system and the protein recruitment system are relatively limited in their ability to identify interactions with integral membrane proteins. Here we describe the development of a reverse Ras recruitment system (reverse RRS), in which the bait used encodes a membrane protein. The bait is expressed in its natural environment, the membrane, whereas the protein partner (the prey) is fused to a cytoplasmic Ras mutant. Protein–protein interaction between the proteins encoded by the prey and the bait results in Ras membrane translocation and activation of a viability pathway in yeast. We devised the expression of the bait and prey proteins under the control of dual distinct inducible promoters, thus enabling a rapid selection of transformants in which growth is attributed solely to specific protein–protein interaction. The reverse RRS approach greatly extends the usefulness of the protein recruitment systems and the use of integral membrane proteins as baits. The system serves as an attractive approach to explore novel protein–protein interactions with high specificity and selectivity, where other methods fail.     

A network synthesis model for generating protein interaction network families

In this work, we introduce a novel network synthesis model that can generate families of evolutionarily related synthetic protein-protein interaction (PPI) networks. Given an ancestral network, the proposed model generates the network family according to a hypothetical phylogenetic tree, where the descendant networks are obtained through duplication and divergence of their ancestors, followed by network growth using network evolution models. We demonstrate that this network synthesis model can effectively create synthetic networks whose internal and cross-network properties closely resemble those of real PPI networks. The proposed model can serve as an effective framework for generating comprehensive benchmark datasets that can be used for reliable performance assessment of comparative network analysis algorithms. Using this model, we constructed a large-scale network alignment benchmark, called NAPAbench, and evaluated the performance of several representative network alignment algorithms. Our analysis clearly shows the relative performance of the leading network algorithms, with their respective advantages and disadvantages. The algorithm and source code of the network synthesis model and the network alignment benchmark NAPAbench are publicly available at http://www.ece.tamu.edu/bjyoon/NAPAbench/.     

A novel mechanism for localizing membrane proteins to yeast trans-Golgi network requires function of synaptojanin-like protein

Localization of resident membrane proteins to the yeast trans-Golgi network (TGN) involves both their retrieval from a prevacuolar/endosomal compartment (PVC) and a "slow delivery" mechanism that inhibits their TGN-to-PVC transport. A screen for genes required for the slow delivery mechanism uncovered INP53, a gene encoding a phosphoinositide phosphatase. A retrieval-defective model TGN protein, A(F-->A)-ALP, was transported to the vacuole in inp53 mutants approximately threefold faster than in wild type. Inp53p appears to function in a process distinct from PVC retrieval because combining inp53 with mutations that block retrieval resulted in a much stronger phenotype than either mutation alone. In vps27 strains defective for both anterograde and retrograde transport out of the PVC, a loss of Inp53p function markedly accelerated the rate of transport of TGN residents A-ALP and Kex2p into the PVC. Inp53p function is cargo specific because a loss of Inp53p function had no effect on the rate of Vps10p transport to the PVC in vps27 cells. The rate of early secretory pathway transport appeared to be unaffected in inp53 mutants. Cell fractionation experiments suggested that Inp53p associates with Golgi or endosomal membranes. Taken together, these results suggest that a phosphoinositide signaling event regulates TGN-to-PVC transport of select cargo proteins.     

Preferential duplication in the sparse part of yeast protein interaction network

Gene duplication is an important mechanism driving the evolution of biomolecular network. Thus, it is expected that there should be a strong relationship between a gene's duplicability and the interactions of its protein product with other proteins in the network. We studied this question in the context of the protein interaction network (PIN) of Saccharomyces cerevisiae. We found that duplicates have, on average, significantly lower clustering coefficient (CC) than singletons, and the proportion of duplicates (PD) decreases steadily with CC. Furthermore, using functional annotation data, we observed a strong negative correlation between PD and the mean CC for functional categories. By partitioning the network into modules and assigning each protein a modularity measure Q(n), we found that CC of a protein is a reflection of its modularity. Moreover, the core components of complexes identified in a recent high-throughput experiment, characterized by high CC, have lower PD than that of the attachments. Subsequently, 2 types of hub were identified by their degree, CC and Q(n). Although PD of intramodular hubs is much less than the network average, PD of intermodular hubs is comparable to, or even higher than, the network average. Our results suggest that high CC, and thus high modularity, pose strong evolutionary constraints on gene duplicability, and gene duplication prefers to happen in the sparse part of PINs.     

The yeast integral membrane protein Apq12 potentially links membrane dynamics to assembly of nuclear pore complexes

Although the structure and function of components of the nuclear pore complex (NPC) have been the focus of many studies, relatively little is known about NPC biogenesis. In this study, we report that Apq12 is required for efficient NPC biogenesis in Saccharomyces cerevisiae. Apq12 is an integral membrane protein of the nuclear envelope (NE) and endoplasmic reticulum. Cells lacking Apq12 are cold sensitive for growth, and a subset of their nucleoporins (Nups), those that are primarily components of the cytoplasmic fibrils of the NPC, mislocalize to the cytoplasm. APQ12 deletion also causes defects in NE morphology. In the absence of Apq12, most NPCs appear to be associated with the inner but not the outer nuclear membrane. Low levels of benzyl alcohol, which increases membrane fluidity, prevented Nup mislocalization and restored the proper localization of Nups that had accumulated in cytoplasmic foci upon a shift to lower temperature. Thus, Apq12p connects nuclear pore biogenesis to the dynamics of the NE.     

A novel approach for the identification of protein-protein interaction with integral membrane proteins

Protein-protein interaction plays a major role in all biological processes. The currently available genetic methods such as the two-hybrid system and the protein recruitment system are relatively limited in their ability to identify interactions with integral membrane proteins. Here we describe the development of a reverse Ras recruitment system (reverse RRS), in which the bait used encodes a membrane protein. The bait is expressed in its natural environment, the membrane, whereas the protein partner (the prey) is fused to a cytoplasmic Ras mutant. Protein-protein interaction between the proteins encoded by the prey and the bait results in Ras membrane translocation and activation of a viability pathway in yeast. We devised the expression of the bait and prey proteins under the control of dual distinct inducible promoters, thus enabling a rapid selection of transformants in which growth is attributed solely to specific protein-protein interaction. The reverse RRS approach greatly extends the usefulness of the protein recruitment systems and the use of integral membrane proteins as baits. The system serves as an attractive approach to explore novel protein-protein interactions with high specificity and selectivity, where other methods fail.     

Virtual identification of essential proteins within the protein interaction network of yeast

Topological analysis of large scale protein-protein interaction networks (PINs) is important for understanding the organizational and functional principles of individual proteins. The number of interactions that a protein has in a PIN has been observed to be correlated with its indispensability. Essential proteins generally have more interactions than the nonessential ones. We show here that the lethality associated with removal of a protein from the yeast proteome correlates with different centrality measures of the nodes in the PIN, such as the closeness of a protein to many other proteins, or the number of pairs of proteins which need a specific protein as an intermediary in their communications, or the participation of a protein in different protein clusters in the PIN. These measures are significantly better than random selection in identifying essential proteins in a PIN. Centrality measures based on graph spectral properties of the network, in particular the subgraph centrality, show the best performance in identifying essential proteins in the yeast PIN. Subgraph centrality gives important structural information about the role of individual proteins, and permits the selection of possible targets for rational drug discovery through the identification of essential proteins in the PIN.     

The phox homology (PX) domain protein interaction network in yeast

The phox homology (PX) domain is a phosphoinositide-binding domain that is conserved from yeast to human. Here we show for the first time by genome-wide two-hybrid screens and in vitro binding assays that the PX domain is a bona fide protein interaction domain. The yeast PX domain-only proteins Grd19p (YOR357C) and Ypt35p (YHR105W), as well as the isolated PX domains from Mvp1p (YMR004W), Snx42p/Cvt20p/Atg20p (YDL113C), Vam7p (YGL212W), and Vps17p (YOR132W), yielded a total of 40 reproducible two-hybrid interactions. Thirty-five interactions were found for the full-length proteins of Bem1p (YBR200W), Snx42p, Snx4p/Cvt13p (YJL036W), Vam7p, Vps5p (YOR069W), and Vps17p, but these appear not to require the PX domain, because these interactions could not be reproduced with PX-only baits. Interactions of Grd19p, Vam7p, Vps5p, Vps17p, and Ypt35p with members of the Yip1p family of proteins were detected consistently and were verified by in vitro binding assays. The N-terminal cytoplasmic domain of Yip1p and Yif1p mediates these interactions with PX domains. A mutation in the lipid-binding pocket of Ypt35p that reduces lipid binding markedly does not affect these PX domain protein interactions, arguing that lipid binding uses a different interaction surface than protein binding.     

An exponential core in the heart of the yeast protein interaction network

Protein interactions in the budding yeast have been shown to form a scale-free network, a feature of other organized networks such as bacterial and archaeal metabolism and the World Wide Web. Here, we study the connections established by yeast proteins and discover a preferential attachment between essential proteins. The essential-essential connections are long ranged and form a subnetwork where the giant component includes 97% of these proteins. Unexpectedly, this subnetwork displays an exponential connectivity distribution, in sharp contrast to the scale-free topology of the complete network. Furthermore, the wide phylogenetic extent of these core proteins and interactions provides evidence that they represent the ancestral state of the yeast protein interaction network. Finally, we propose that this core exponential network may represent a generic scaffold around which organism-specific and taxon-specific proteins and interactions coalesce.     

Topological structure analysis of the protein-protein interaction network in budding yeast

Interaction detection methods have led to the discovery of thousands of interactions between proteins, and discerning relevance within large-scale data sets is important to present-day biology. Here, a spectral method derived from graph theory was introduced to uncover hidden topological structures (i.e. quasi-cliques and quasi-bipartites) of complicated protein-protein interaction networks. Our analyses suggest that these hidden topological structures consist of biologically relevant functional groups. This result motivates a new method to predict the function of uncharacterized proteins based on the classification of known proteins within topological structures. Using this spectral analysis method, 48 quasi-cliques and six quasi-bipartites were isolated from a network involving 11,855 interactions among 2617 proteins in budding yeast, and 76 uncharacterized proteins were assigned functions.     

A scale of functional divergence for yeast duplicated genes revealed from analysis of the protein-protein interaction network

Background  

Studying the evolution of the function of duplicated genes usually implies an estimation of the extent of functional conservation/divergence between duplicates from comparison of actual sequences. This only reveals the possible molecular function of genes without taking into account their cellular function(s). We took into consideration this latter dimension of gene function to approach the functional evolution of duplicated genes by analyzing the protein-protein interaction network in which their products are involved. For this, we derived a functional classification of the proteins using PRODISTIN, a bioinformatics method allowing comparison of protein function. Our work focused on the duplicated yeast genes, remnants of an ancient whole-genome duplication.     

The application of yeast hybrid systems in protein interaction analysis

Yeast hybrid systems have been widely used due to their convenience and low cost. Based on these systems, many methods have been developed to analyze protein–protein, protein–DNA and protein–RNA interactions. In this paper, we are reviewing these different yeast hybrid systems. According to the number of hybrid proteins, yeast hybrid systems can be divided into three categories, yeast one-hybrid, yeast two-hybrid and yeast three-hybrid systems. Alternatively, yeast hybrid systems can be categorized according to the subcellular localization of the protein interaction process in the cell into nuclear protein–protein interactions, cytosol protein–protein interactions and membrane protein–protein interactions. Throughout the review, we focus on the progress and limitations of each yeast hybrid system over the recent years.