Analyzing protein–protein interactions in the post-interactomic era. Are we ready for the endgame?

Mapping protein–protein interactions in genome-wide scales revealed thousands of novel binding partners in each of the explored model organisms. Organizing these hits in comprehensive ways is becoming increasingly important for systems biology approaches to understand complex cellular processes and diseases. However, proteome wide interaction techniques and their resulting global networks are not revealing the topologies of networks that are truly operating in the cell. In this short review I will discuss which prerequisites have to be fulfilled and which experimental methods might be practicable to translate primary protein interaction data into network presentations that help in understanding cellular processes.     

Fat & fabulous: Bifunctional lipids in the spotlight

Understanding biological processes at the mechanistic level requires a systematic charting of the physical and functional links between all cellular components. While protein–protein and protein–nucleic acid networks have been subject to many global surveys, other critical cellular components such as membrane lipids have rarely been studied in large-scale interaction screens. Here, we review the development of photoactivatable and clickable lipid analogues–so-called bifunctional lipids–as novel chemical tools that enable a global profiling of lipid–protein interactions in biological membranes. Recent studies indicate that bifunctional lipids hold great promise in systematic efforts to dissect the elaborate crosstalk between proteins and lipids in live cells and organisms. This article is part of a Special Issue entitled Tools to study lipid functions.     

Force spectroscopy studies on protein–ligand interactions: A single protein mechanics perspective

Protein–ligand interactions are ubiquitous and play important roles in almost every biological process. The direct elucidation of the thermodynamic, structural and functional consequences of protein–ligand interactions is thus of critical importance to decipher the mechanism underlying these biological processes. A toolbox containing a variety of powerful techniques has been developed to quantitatively study protein–ligand interactions in vitro as well as in living systems. The development of atomic force microscopy-based single molecule force spectroscopy techniques has expanded this toolbox and made it possible to directly probe the mechanical consequence of ligand binding on proteins. Many recent experiments have revealed how ligand binding affects the mechanical stability and mechanical unfolding dynamics of proteins, and provided mechanistic understanding on these effects. The enhancement effect of mechanical stability by ligand binding has been used to help tune the mechanical stability of proteins in a rational manner and develop novel functional binding assays for protein–ligand interactions. Single molecule force spectroscopy studies have started to shed new lights on the structural and functional consequence of ligand binding on proteins that bear force under their biological settings.     

The protein–protein interaction network of the human Sirtuin family

Protein–protein interaction networks are useful for studying human diseases and to look for possible health care through a holistic approach. Networks are playing an increasing and important role in the understanding of physiological processes such as homeostasis, signaling, spatial and temporal organizations, and pathological conditions. In this article we show the complex system of interactions determined by human Sirtuins (Sirt) largely involved in many metabolic processes as well as in different diseases. The Sirtuin family consists of seven homologous Sirt-s having structurally similar cores but different terminal segments, being rather variable in length and/or intrinsically disordered. Many studies have determined their cellular location as well as biological functions although molecular mechanisms through which they act are actually little known therefore, the aim of this work was to define, explore and understand the Sirtuin-related human interactome. As a first step, we have integrated the experimentally determined protein–protein interactions of the Sirtuin-family as well as their first and second neighbors to a Sirtuin-related sub-interactome. Our data showed that the second-neighbor network of Sirtuins encompasses 25% of the entire human interactome, and exhibits a scale-free degree distribution and interconnectedness among top degree nodes. Moreover, the Sirtuin sub interactome showed a modular structure around the core comprising mixed functions. Finally, we extracted from the Sirtuin sub-interactome subnets related to cancer, aging and post-translational modifications for information on key nodes and topological space of the subnets in the Sirt family network.     

Protein and lysate array technologies in cancer research

Capturing quantitative proteomic information provides new insights for enhancing the understanding of cancer biology. There have been several protein microarray formats, and each has an advantage depending on what is being detected. However, in contrast to nucleotide printing, the production of protein arrays generally requires the capability of handling viscous solutions, and the mishandling of various factors, such as temperature and humidity, adversely affect protein status. The requirement for such specifications is critical when increasing the throughput for monitoring a large number of samples for rigorous quantitation. In particular, a new solid pin arrayer has been extremely powerful when highly viscous cell lysates printed for high-density, "reverse-phase" protein arrays, and acquired data allows for theoretical models of protein signaling networks to be constructed. In this review, applications of currently available protein microarray technology to cancer research are discussed including the advantages of the new solid pin architecture for opening up powerful proteomic applications.     

Proteomics of proteasome complexes and ubiquitinated proteins

Ubiquitin-proteasome-mediated protein degradation is central to the regulation of many important biological processes, including cell cycle progression, apoptosis and DNA repair. Recognition and degradation of ubiquitinated substrates by the 26S proteasome is tightly regulated to maintain normal cell growth. Disruption of the proteasomal degradation pathway has been implicated in a wide range of human diseases. Although the ubiquitin-proteasome system has been intensively investigated, many key questions remain unanswered in regard to its components and regulation of its activities. A key step towards a full understanding of the pathway is to investigate the proteasome complex subunit composition, heterogeneity, post-translational modifications, assembly, proteasome interaction networks and degradation substrates. Mass spectrometry-based proteomic approaches have been successfully applied for unraveling the details of the proteasome complexes and their substrates in an unprecedented fashion. An overview of the current knowledge of the proteasomal degradation pathway based on mass spectrometry approaches is presented.     

Proteome scanning to predict PDZ domain interactions using support vector machines

Background  

PDZ domains mediate protein-protein interactions involved in important biological processes through the recognition of short linear motifs in their target proteins. Two recent independent studies have used protein microarray or phage display technology to detect PDZ domain interactions with peptide ligands on a large scale. Several computational predictors of PDZ domain interactions have been developed, however they are trained using only protein microarray data and focus on limited subsets of PDZ domains. An accurate predictor of genomic PDZ domain interactions would allow the proteomes of organisms to be scanned for potential binders. Such an application would require an accurate and precise predictor to avoid generating too many false positive hits given the large amount of possible interactors in a given proteome. Once validated these predictions will help to increase the coverage of current PDZ domain interaction networks and further our understanding of the roles that PDZ domains play in a variety of biological processes.     

Global Network Analysis of Lipid-Raft-Related Proteins Reveals Their Centrality in the Network and Their Roles in Multiple Biological Processes

Lipid rafts are specialized cholesterol-enriched microdomains in the cell membrane. They have been known as a platform for protein-protein interactions and to take part in multiple biological processes. Nevertheless, how lipid rafts influence protein properties at the proteomic level is still an open question for researchers using traditional biochemical approaches. Here, by annotating the lipid raft localization of proteins in human protein-protein interaction networks, we performed a systematic analysis of the function of proteins related to lipid rafts. Our results demonstrated that lipid raft proteins and their interactions were critical for the structure and stability of the whole network, and that the interactions between them were significantly enriched. Furthermore, for each protein in the network, we calculated its “lipid raft dependency (LRD),” which indicates how close it is topologically associated with lipid rafts, and we then uncovered the connection between LRD and protein functions. Proteins with high LRD tended to be essential for mammalian development, and malfunction of these proteins was inclined to cause human diseases. Coordinated with their neighbors, high-LRD proteins participated in multiple biological processes and targeted many pathways in diseases pathogenesis. High-LRD proteins were also found to have tissue specificity of expression. In summary, our network-based analysis denotes that lipid raft proteins have higher centrality in the network, and that lipid-raft-related proteins have multiple functions and are probably concerned with many biological processes in disease development.     

CANVS: an easy-to-use application for the analysis and visualization of mass spectrometry–based protein–protein interaction/association data

The elucidation of a protein’s interaction/association network is important for defining its biological function. Mass spectrometry–based proteomic approaches have emerged as powerful tools for identifying protein–protein interactions (PPIs) and protein–protein associations (PPAs). However, interactome/association experiments are difficult to interpret, considering the complexity and abundance of data that are generated. Although tools have been developed to identify protein interactions/associations quantitatively, there is still a pressing need for easy-to-use tools that allow users to contextualize their results. To address this, we developed CANVS, a computational pipeline that cleans, analyzes, and visualizes mass spectrometry–based interactome/association data. CANVS is wrapped as an interactive Shiny dashboard with simple requirements, allowing users to interface easily with the pipeline, analyze complex experimental data, and create PPI/A networks. The application integrates systems biology databases such as BioGRID and CORUM to contextualize the results. Furthermore, CANVS features a Gene Ontology tool that allows users to identify relevant GO terms in their results and create visual networks with proteins associated with relevant GO terms. Overall, CANVS is an easy-to-use application that benefits all researchers, especially those who lack an established bioinformatic pipeline and are interested in studying interactome/association data.     

The intracellular antibody capture technology: towards the high-throughput selection of functional intracellular antibodies for target validation

Several approaches have been developed over the past decade to study the complex interactions that occur in biological system. The ability to carry out a comprehensive genetic analysis of an organism becomes more limited and difficult as the complexity of the organism increases because complex organisms are likely to have not only more genes than simple organisms but also more elaborate networks of interactions among those genes. The development of technologies to systematically disrupt protein networks at the genomic scale would greatly accelerate the comprehensive understanding of the cell as molecular machinery. Intracellular antibodies (intrabodies) can be targeted to different intracellular compartments to specifically interfere with function of selected intracellular gene products in mammalian cells. This technique should prove important for studies of mammalian cells, where genetic approaches are more difficult. In the context of large-scale protein interaction mapping projects, intracellular antibodies (ICAbs) promise to be an important tool to knocking out protein function inside the cell. In this context, however, the need for speed and high throughput requires the development of simple and robust methods to derive antibodies which function within cells, without the need for optimization of each individual ICAb. The successful inhibition of biological processes by intrabodies has been demonstrated in a number of different cells. The performance of antibodies that are intracellularly expressed is, however, somewhat unpredictable, because the reducing environment of the cell cytoplasm in which they are forced to work prevents some antibodies, but not others, to fold properly. For this reason, we have developed an in vivo selection procedure named Intracellular Antibody Capture Technology (IACT) that allows the isolation of functional intrabodies. The IAC technology has been used for the rapid identification of antigen-antibody pairs in intracellular compartments and for the in vivo identification of epitopes recognized by the selected intracellular antibodies. Several optimizations of the IAC technology for protein knock-out have been developed so far. This system offers a powerful and versatile proteomic tool to dissect diverse functional properties of cellular proteins in different cell lines.     

Yeast ABC transporters-- a tale of sex, stress, drugs and aging

Yeast ATP-binding cassette (ABC) proteins are implicated in many biological phenomena, often acting at crossroads of vital cellular processes. Their functions encompass peptide pheromone secretion, regulation of mitochondrial function, vacuolar detoxification, as well as pleiotropic drug resistance and stress adaptation. Because yeast harbors several homologues of mammalian ABC proteins with medical importance, understanding their molecular mechanisms, substrate interaction and three-dimensional structure of yeast ABC proteins might help identifying new approaches aimed at combating drug resistance or other ABC-mediated diseases. This review provides a comprehensive discussion on the functions of the ABC protein family in the yeast Saccharomyces cerevisiae.     

Spotlight: Assembly of protein complexes by integrating graph clustering methods

As is generally assumed, clusters in protein–protein interaction (PPI) networks perform specific, crucial functions in biological systems. Various network community detection methods have been developed to exploit PPI networks in order to identify protein complexes and functional modules. Due to the potential role of various regulatory modes in biological networks, a single method may just apply a single graph property and neglect communities highlighted by other network properties.     

Analysis of protein tyrosine phosphatase interactions with microarrayed phosphopeptide substrates using imaging mass spectrometry

Microarrays of peptide and recombinant protein libraries are routinely used for high-throughput studies of protein–protein interactions and enzymatic activities. Imaging mass spectrometry (IMS) is currently applied as a method to localize analytes on thin tissue sections and other surfaces. Here, we have applied IMS as a label-free means to analyze protein–peptide interactions in a microarray-based phosphatase assay. This IMS strategy visualizes the entire microarray in one composite image by collecting a predefined raster of matrix-assisted laser desorption/ionization time-of-flight (MALDI–TOF) mass spectrometry spectra over the surface of the chip. Examining the bacterial tyrosine phosphatase YopH, we used IMS as a label-free means to visualize enzyme binding and activity with a microarrayed phosphopeptide library printed on chips coated with either gold or indium–tin oxide. Furthermore, we demonstrate that microarray-based IMS can be coupled with surface plasmon resonance imaging to add kinetic analyses to measured binding interactions. The method described here is within the capabilities of many modern MALDI–TOF instruments and has general utility for the label-free analysis of microarray assays.     

Asthma, the ugly duckling of lung disease proteomics?

The human respiratory system represents a vital but vulnerable system. It is a major target for many diseases such as cancer and asthma. The incidence of these diseases has increased dramatically in the last 40-50 years. In the search for possible new therapies, many experimental tools and methods have been developed to study these diseases, ranging from animal models to in vitro studies. In the last decades, genomic and proteomic approaches have gained a lot of attention. After the major scientific breakthroughs in the field of genomics, it is now widely accepted that to understand biological processes, large-scale protein studies through proteomics techniques are required. In the battle against lung cancer, the proteomics approach has already been successfully implemented. Surprisingly, only a few proteomics studies on the ever-increasing global asthma problem have been published so far. And although proteomics also has its limitations and experimental difficulties, in our opinion, proteomics can definitely contribute to the understanding of a complex disease such as asthma. Therefore, the additional values and possibilities of proteomics in asthma research should be thoroughly investigated. A close collaboration between the different scientific disciplines may eventually lead to the development of new therapeutic strategies against asthma.     

Flavonoid–membrane interactions: Involvement of flavonoid–metal complexes in raft signaling

Flavonoids are polyphenolic compounds produced by plants and delivered to the human body through food. Although the epidemiological analyses of large human populations did not reveal a simple correlation between flavonoid consumption and health, laboratory investigations and clinical trials clearly demonstrate the effectiveness of flavonoids in the prevention of cardiovascular, carcinogenic, neurodegenerative and immune diseases, as well as other diseases. At present, the abilities of flavonoids in the regulation of cell metabolism, gene expression, and protection against oxidative stress are well-known, although certain biophysical aspects of their functioning are not yet clear. Most flavonoids are poorly soluble in water and, similar to lipophilic compounds, have a tendency to accumulate in biological membranes, particularly in lipid rafts, where they can interact with different receptors and signal transducers and influence their functioning through modulation of the lipid-phase behavior. In this study, we discuss the enhancement in the lipophilicity and antioxidative activity of flavonoids after their complexation with transient metal cations. We hypothesize that flavonoid–metal complexes are involved in the formation of molecular assemblies due to the facilitation of membrane adhesion and fusion, protein–protein and protein–membrane binding, and other processes responsible for the regulation of cell metabolism and protection against environmental hazards.     

Yeast as a model for studying human neurodegenerative disorders

Protein misfolding and aggregation are central events in many disorders including several neurodegenerative diseases. This suggests that alterations in normal protein homeostasis may contribute to pathogenesis, but the exact molecular mechanisms involved are still poorly understood. The budding yeast Saccharomyces cerevisiae is one of the model systems of choice for studies in molecular medicine. Modeling human neurodegenerative diseases in this simple organism has already shown the incredible power of yeast to unravel the complex mechanisms and pathways underlying these pathologies. Indeed, this work has led to the identification of several potential therapeutic targets and drugs for many diseases, including the neurodegenerative diseases. Several features associated with these diseases, such as formation of protein aggregates, cellular toxicity mediated by misfolded proteins, oxidative stress and hallmarks of apoptosis have been faithfully recapitulated in yeast, enabling researchers to take advantage of this powerful model to rapidly perform genetic and compound screens with the aim of identifying novel candidate therapeutic targets and drugs. Here we review the work undertaken to model human brain disorders in yeast, and how these models provide insight into novel therapeutic approaches for these diseases.     

Systems for the detection and analysis of protein–protein interactions

The analysis of protein–protein interactions is important for developing a better understanding of the functional annotations of proteins that are involved in various biochemical reactions in vivo. The discovery that a protein with an unknown function binds to a protein with a known function could provide a significant clue to the cellular pathway concerning the unknown protein. Therefore, information on protein–protein interactions obtained by the comprehensive analysis of all gene products is available for the construction of interactive networks consisting of individual protein–protein interactions, which, in turn, permit elaborate biological phenomena to be understood. Systems for detecting protein–protein interactions in vitro and in vivo have been developed, and have been modified to compensate for limitations. Using these novel approaches, comprehensive and reliable information on protein–protein interactions can be determined. Systems that permit this to be achieved are described in this review.K. Kuroda, M. Kato and J. Mima contributed equally to this work.