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PubMed2004

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.

Computer Simulation↗
PubMed2005

Probabilistic model of the human protein-protein interaction network.

A catalog of all human protein-protein interactions would provide scientists with a framework to study protein deregulation in complex diseases such as cancer. Here we demonstrate that a probabilistic analysis integrating model organism interactome data, protein domain data, genome-wide gene expression data and functional annotation data predicts nearly 40,000 protein-protein interactions in humans-a result comparable to those obtained with experimental and computational approaches in model organisms. We validated the accuracy of the predictive model on an independent test set of known interactions and also experimentally confirmed two predicted interactions relevant to human cancer, implicating uncharacterized proteins into definitive pathways. We also applied the human interactome network to cancer genomics data and identified several interaction subnetworks activated in cancer. This integrative analysis provides a comprehensive framework for exploring the human protein interaction network.

Chromosome Mapping↗
PubMed2005

Algorithms for protein interaction networks.

The functional characterization of all genes and their gene products is the main challenge of the postgenomic era. Recent experimental and computational techniques have enabled the study of interactions among all proteins on a large scale. In this paper, approaches will be presented to exploit interaction information for the inference of protein structure, function, signalling pathways and ultimately entire interactomes. Interaction networks can be modelled as graphs, showing the operation of gene function in terms of protein interactions. Since the architecture of biological networks differs distinctly from random networks, these functional maps contain a signal that can be used for predictive purposes. Protein function and structure can be predicted by matching interaction patterns, without the requirement of sequence similarity. Moving on to a higher level definition of protein function, the question arises how to decompose complex networks into meaningful subsets. An algorithm will be demonstrated, which extracts whole signal-transduction pathways from noisy graphs derived from text-mining the biological literature. Finally, an algorithmic strategy is formulated that enables the proteomics community to build a reliable scaffold of the interactome in a fraction of the time compared with uncoordinated efforts.

Algorithms↗
PubMed2004

Biochemical characterization of protein complexes from the Helicobacter pylori protein interaction map: strategies for complex formation and evidence for novel interactions within type IV secretion systems.

We have investigated a large set of interactions from the Helicobacter pylori protein interaction map previously identified by high-throughput yeast two-hybrid (htY2H)-based methods. This study had two aims: i) to validate htY2H as a source of protein-protein interaction complexes for high-throughput biochemical and structural studies of the H. pylori interactome; and ii) to validate biochemically interactions shown by htY2H to involve components of the H. pylori type IV secretion systems. Thus, 17 interactions involving 31 proteins and protein fragments were studied, and a general strategy was designed to produce protein-interacting partners for biochemical and structural characterization. We show that htY2H is a valid source of protein-protein complexes for high-throughput proteome-scale characterization of the H. pylori interactome, because 76% of the interactions tested were confirmed biochemically. Of the interactions involving type IV secretion proteins, three could be confirmed. One interaction is between two components of the type IV secretion apparatus, ComB10 and ComB4, which are VirB10 and VirB4 homologs, respectively. Another interaction is between a type IV component (HP0525, a VirB11 homolog) and a non-type IV secretion protein (HP01451), indicating that proteins other than the core VirB (1-11)-VirD4 proteins may play a role in type IV secretion. Finally, a third interaction was biochemically confirmed between CagA, a virulence factor secreted by the type IV secretion system encoded by the Cag pathogenicity island, and a non-type IV secretion protein, HP0496.

Bacterial Proteins↗
PubMed2006

The DFNB31 gene product whirlin connects to the Usher protein network in the cochlea and retina by direct association with USH2A and VLGR1.

Mutations in the DFNB31 gene encoding the PDZ scaffold protein whirlin are causative for hearing loss in man and mouse. Whirlin is known to be essential for the elongation process of the stereocilia of sensory hair cells in the inner ear, though its complete spatial and temporal expression patterns remained elusive. Here, we demonstrate that, in embryonic development, the gene is not only expressed in the inner ear, but also in the developing brain and the retina. Various isoforms of whirlin are widely and differentially expressed, and we provide evidence that whirlin directly associates with USH2A isoform b and VLGR1b, two proteins that we previously reported to be part of the Usher protein interactome. These proteins co-localize with whirlin at the synaptic regions of both photoreceptor cells and outer hair cells in the cochlea. These findings indicate that whirlin is part of a macromolecular PDZ protein scaffold that functions in the organization of the pre- and/or postsynaptic side of photoreceptor and hair cell synapses. Whirlin might be involved in synaptic adhesion through interaction with USH2A and VLGR1b as well as in synaptic development as suggested by its spatial and temporal expression patterns. In addition, we demonstrate that whirlin, USH2A and Vlgr1b co-localize at the connecting cilium and the outer limiting membrane of photoreceptor cells and in spiral ganglion neurons of the inner ear. Our data show that whirlin is connected to the dynamic Usher protein interactome and indicate that whirlin has a pleiotropic function in both the retina and the inner ear.

Animals↗
PubMed2006

Global phylogeny determined by the combination of protein domains in proteomes.

The majority of proteins consist of multiple domains that are either repeated or combined in defined order. In this study, we survey the combination of protein domains defined at fold and fold superfamily levels in 185 genomes belonging to organisms that have been fully sequenced and introduce a method that reconstructs rooted phylogenomic trees from the content and arrangement of domains in proteins at a genomic level. We find that the majority of domain combinations were unique to Archaea, Bacteria, or Eukarya, suggesting most combinations originated after life had diversified. Domain repeat and domain repeat within multidomain proteins increased notably in eukaryotes, mainly at the expense of single-domain and domain-pair proteins. This increase was mostly confined to Metazoa. We also find an unbalanced sharing of domain combinations which suggests that Eukarya is more closely related to Bacteria than to Archaea, an observation that challenges the widely assumed eukaryote-archaebacterial sisterhood relationship. The occurrence and abundance of the molecular repertoire (interactome) of domain combinations was used to generate phylogenomic trees. These global interactome-based phylogenies described organismal histories satisfactorily, revealing the tripartite nature of life, and supporting controversial evolutionary patterns, such as the Coelomata hypothesis, the grouping of plants and animals, and the Gram-positive origin of bacteria. Results suggest strongly that the process of domain combination is not random but curved by evolution, rejecting the null hypothesis of domain modules combining in the absence of natural selection or an optimality criterion.

Animals↗
PubMed2021

A full-proteome, interaction-specific characterization of mutational hotspots across human cancers.

Rapid accumulation of cancer genomic data has led to the identification of an increasing number of mutational hotspots with uncharacterized significance. Here we present a biologically informed computational framework that characterizes the functional relevance of all 1107 published mutational hotspots identified in approximately 25,000 tumor samples across 41 cancer types in the context of a human 3D interactome network, in which the interface of each interaction is mapped at residue resolution. Hotspots reside in network hub proteins and are enriched on protein interaction interfaces, suggesting that alteration of specific protein-protein interactions is critical for the oncogenicity of many hotspot mutations. Our framework enables, for the first time, systematic identification of specific protein interactions affected by hotspot mutations at the full proteome scale. Furthermore, by constructing a hotspot-affected network that connects all hotspot-affected interactions throughout the whole-human interactome, we uncover genome-wide relationships among hotspots and implicate novel cancer proteins that do not harbor hotspot mutations themselves. Moreover, applying our network-based framework to specific cancer types identifies clinically significant hotspots that can be used for prognosis and therapy targets. Overall, we show that our framework bridges the gap between the statistical significance of mutational hotspots and their biological and clinical significance in human cancers.

Genomics↗
PubMed2005

Herpesviral protein networks and their interaction with the human proteome.

The comprehensive yeast two-hybrid analysis of intraviral protein interactions in two members of the herpesvirus family, Kaposi sarcoma-associated herpesvirus (KSHV) and varicella-zoster virus (VZV), revealed 123 and 173 interactions, respectively. Viral protein interaction networks resemble single, highly coupled modules, whereas cellular networks are organized in separate functional submodules. Predicted and experimentally verified interactions between KSHV and human proteins were used to connect the viral interactome into a prototypical human interactome and to simulate infection. The analysis of the combined system showed that the viral network adopts cellular network features and that protein networks of herpesviruses and possibly other intracellular pathogens have distinguishing topologies.

Cell Line↗
PubMed2005

Non-linear mapping for exploratory data analysis in functional genomics.

BACKGROUND: Several supervised and unsupervised learning tools are available to classify functional genomics data. However, relatively less attention has been given to exploratory, visualisation-driven approaches. Such approaches should satisfy the following factors: Support for intuitive cluster visualisation, user-friendly and robust application, computational efficiency and generation of biologically meaningful outcomes. This research assesses a relaxation method for non-linear mapping that addresses these concerns. Its applications to gene expression and protein-protein interaction data analyses are investigated. RESULTS: Publicly available expression data originating from leukaemia, round blue-cell tumours and Parkinson disease studies were analysed. The method distinguished relevant clusters and critical analysis areas. The system does not require assumptions about the inherent class structure of the data, its mapping process is controlled by only one parameter and the resulting transformations offer intuitive, meaningful visual displays. Comparisons with traditional mapping models are presented. As a way of promoting potential, alternative applications of the methodology presented, an example of exploratory data analysis of interactome networks is illustrated. Data from the C. elegans interactome were analysed. Results suggest that this method might represent an effective solution for detecting key network hubs and for clustering biologically meaningful groups of proteins. CONCLUSION: A relaxation method for non-linear mapping provided the basis for visualisation-driven analyses using different types of data. This study indicates that such a system may represent a user-friendly and robust approach to exploratory data analysis. It may allow users to gain better insights into the underlying data structure, detect potential outliers and assess assumptions about the cluster composition of the data.

Algorithms↗
PubMed2005

HomoMINT: an inferred human network based on orthology mapping of protein interactions discovered in model organisms.

BACKGROUND: The application of high throughput approaches to the identification of protein interactions has offered for the first time a glimpse of the global interactome of some model organisms. Until now, however, such genome-wide approaches have not been applied to the human proteome. RESULTS: In order to fill this gap we have assembled an inferred human protein interaction network where interactions discovered in model organisms are mapped onto the corresponding human orthologs. In addition to a stringent assignment to orthology classes based on the InParanoid algorithm, we have implemented a string matching algorithm to filter out orthology assignments of proteins whose global domain organization is not conserved. Finally, we have assessed the accuracy of our own, and related, inferred networks by benchmarking them against i) an assembled experimental interactome, ii) a network derived by mining of the scientific literature and iii) by measuring the enrichment of interacting protein pairs sharing common Gene Ontology annotation. CONCLUSION: The resulting networks are named HomoMINT and HomoMINT_filtered, the latter being based on the orthology table filtered by the domain architecture matching algorithm. They contains 9749 and 5203 interactions respectively and can be analyzed and viewed in the context of the experimentally verified interactions between human proteins stored in the MINT database. HomoMINT is constantly updated to take into account the growing information in the MINT database.

Algorithms↗
PubMed2026

Phenotyping of post-fertilization sperm mitophagy determinants discovered in a mammalian gamete-based cell-free system.

The targeted, substrate-specific degradation of paternal mitochondria inside the zygote, known as post-fertilization sperm mitophagy, is a crucial and evolutionarily conserved early embryonic event. It ensures the exclusive maternal inheritance of the mitochondrial genome. Post-fertilization sperm mitophagy was initially thought to only be achieved via the ubiquitin-proteasome system. Until pro-autophagic receptor proteins such as SQSTM1, GABARAP, as well as the proteasome-interacting ubiquitinated protein dislocase VCP, were identified as contributors to the degradation of the sperm mitochondria early after mammalian fertilization. This synergy of proteasomal and autophagic pathways ensures a timely degradation of sperm mitochondria shortly after fertilization. The discovery of these autophagic receptors lead researchers to believe there might be other autophagic receptors and determinants necessary for proper post-fertilization sperm mitophagy. Based on the established inventory of proteins from mass spectrometry trials of boar spermatozoa exposed to porcine oocyte extracts in an intra-specific porcine cell-free system (CFS), five candidate mitophagy determinants were further investigated in this study, namely LACTB, PRDX3, PSMA8, TOMM34, and FUNDC1. These proteins of interest were studied and validated by using in vitro fertilization (IVF) protocols, cell imaging of spermatids, spermatozoa, oocytes and zygotes, protein interactome analysis, and the porcine CFS. The proteins PSMA8 and TOMM34 behaved in accordance with our proteomic study predictions. The PSMA8 labeling increased after exposure to CFS; in agreement with the classification PSMA8 was given from the mass spectrometry findings. TOMM34 underwent a visible decrease in labeling after exposure to CFS, which also agreed with its proteomic classification; this labeling persisted in IVF zygotes. Except for LACTB, the examined proteins showed mutual interactions as well as interactions with previously identified sperm mitophagy factors in the STRING interactome analysis. Results from this study validate the novel porcine CFS as a valuable tool for the exploration of early fertilization events at a molecular level. Future phenotyping and functional studies using porcine CFS will advance the understanding of mitochondrial inheritance and zygotic development and potentially shed light on the origins of certain mitochondrial diseases arising from the failure of post-fertilization sperm mitophagy.

Animals↗
PubMed2004

Protein interaction networks by proteome peptide scanning.

A substantial proportion of protein interactions relies on small domains binding to short peptides in the partner proteins. Many of these interactions are relatively low affinity and transient, and they impact on signal transduction. However, neither the number of potential interactions mediated by each domain nor the degree of promiscuity at a whole proteome level has been investigated. We have used a combination of phage display and SPOT synthesis to discover all the peptides in the yeast proteome that have the potential to bind to eight SH3 domains. We first identified the peptides that match a relaxed consensus, as deduced from peptides selected by phage display experiments. Next, we synthesized all the matching peptides at high density on a cellulose membrane, and we probed them directly with the SH3 domains. The domains that we have studied were grouped by this approach into five classes with partially overlapping specificity. Within the classes, however, the domains display a high promiscuity and bind to a large number of common targets with comparable affinity. We estimate that the yeast proteome contains as few as six peptides that bind to the Abp1 SH3 domain with a dissociation constant lower than 100 microM, while it contains as many as 50-80 peptides with corresponding affinity for the SH3 domain of Yfr024c. All the targets of the Abp1 SH3 domain, identified by this approach, bind to the native protein in vivo, as shown by coimmunoprecipitation experiments. Finally, we demonstrate that this strategy can be extended to the analysis of the entire human proteome. We have developed an approach, named WISE (whole interactome scanning experiment), that permits rapid and reliable identification of the partners of any peptide recognition module by peptide scanning of a proteome. Since the SPOT synthesis approach is semiquantitative and provides an approximation of the dissociation constants of the several thousands of interactions that are simultaneously analyzed in an array format, the likelihood of each interaction occurring in any given physiological settings can be evaluated. WISE can be easily extended to a variety of protein interaction domains, including those binding to modified peptides, thereby offering a powerful proteomic tool to help completing a full description of the cell interactome.

Animals↗
PubMed2006

p53 and breast cancer, an update.

p53 plays a key role in mediating cell response to various stresses, mainly by inducing or repressing a number of genes involved in cell cycle arrest, senescence, apoptosis, DNA repair, and angiogenesis. According to this important function, p53 activity is controlled in a very complex manner, including several auto-regulatory loops, through the intervention of dozens of modulator proteins (the 'p53 interactome'). p53 mutations are observed in a significant minority of breast tumours. In the remaining cases, alterations of interactome components or target genes could contribute, to some extent, to reduce the ability of p53 to efficiently manage stress events. While the prognostic and predictive value of p53 is still debated, there is an increasing interest for p53-based therapies. The present paper aims to provide updated information on p53 regulation and function, with specific interest on its role in breast cancer.

Apoptosis↗
PubMed2002

Protein interaction domain mapping for the selection of validated targets and lead compounds in the anti-infectious area.

Despite considerable progress in the analysis of microbial genomes, the number of validated targets suitable for the development of drugs acting on agents causing infectious diseases remains modest. The diversity of new chemical entities specific for such targets has almost not increased over the last years, while resistance to anti-infectious drugs has, in contrast, become a real threat in certain surroundings. New strategies are thus needed for selecting novel validated targets. We discuss here a combined approach which uses protein interaction mapping as the basic strategy to identify interacting domains which then serve to validate newly identified targets. The interactome of Helicobacter pylori is used as model to successively describe high-throughput protein interaction mapping, use of the H. pylori data to predict the interactome from other bacteria, analysis of interacting domains, and evaluation of the capacity of one such domain to block synthesis of flagella. The general applicability of this approach to target identification and validation, and to development of novel compounds is also discussed.

Bacterial Proteins↗
PubMed2026

ChromID: A Protocol for Mapping Protein Chromatin Interactions in Living Cells.

Chromatin modifications regulate genome function by recruiting proteins that control transcription, genome organization, and DNA repair. Identifying the proteins associated with specific chromatin modifications is therefore essential for understanding how these regulatory processes operate. Traditional approaches, including chromatin immunoprecipitation and affinity purification coupled to mass spectrometry, have uncovered many chromatin-associated proteins. However, they often rely on crosslinking and chromatin fragmentation, which can disrupt native chromatin architecture and limit the detection of transient interactions. Here, we describe a proximity-labeling protocol for identifying the chromatin-dependent protein interactome associated with specific chromatin marks, termed ChromID. ChromID uses engineered chromatin readers (eCRs) fused to a promiscuous biotin ligase, which labels proteins in the immediate vicinity of the targeted chromatin mark. The protocol includes in vivo biotin labeling, nuclear extract preparation, streptavidin-based enrichment, and tryptic digestion for downstream LC-MS/MS analysis. The protocol has been validated across multiple cell types and chromatin contexts and can be extended to other chromatin-associated proteins, providing a versatile approach to profile chromatin-associated proteomes within their native cellular environment. Key features • Maps proteins associated with different chromatin modifications in living cells using engineered chromatin readers fused to TurboID, BASU, or other promiscuous biotin ligases. • Preserves native chromatin organization and captures transient chromatin-associated interactions that are often lost during conventional affinity purification workflows. • Validated across multiple chromatin contexts, including histone modifications, DNA methylation, transcription factors, RNA polymerase II, and DNA damage-associated chromatin states. • Applicable to diverse cell types and organisms and adaptable to other chromatin-associated proteins, including transcription factors and chromatin regulators.

Biotin proximity labeling↗
PubMed2006

Detection and analysis of protein-protein interactions in organellar and prokaryotic proteomes by native gel electrophoresis: (Membrane) protein complexes and supercomplexes.

It is an essential and challenging task to unravel protein-protein interactions in their actual in vivo context. Native gel systems provide a separation platform allowing the analysis of protein complexes on a rather proteome-wide scale in a single experiment. This review focus on blue-native (BN)-PAGE as the most versatile and successful gel-based approach to separate soluble and membrane protein complexes of intricate protein mixtures derived from all biological sources. BN-PAGE is a charge-shift method with a running pH of 7.5 relying on the gentle binding of anionic CBB dye to all membrane and many soluble protein complexes, leading to separation of protein species essentially according to their size and superior resolution than other fractionation techniques can offer. The closely related colorless-native (CN)-PAGE, whose applicability is restricted to protein species with intrinsic negative net charge, proved to provide an especially mild separation capable of preserving weak protein-protein interactions better than BN-PAGE. The essential conditions determining the success of detecting protein-protein interactions are the sample preparations, e.g. the efficiency/mildness of the detergent solubilization of membrane protein complexes. A broad overview about the achievements of BN- and CN-PAGE studies to elucidate protein-protein interactions in organelles and prokaryotes is presented, e.g. the mitochondrial protein import machinery and oxidative phosphorylation supercomplexes. In many cases, solubilization with digitonin was demonstrated to facilitate an efficient and particularly gentle extraction of membrane protein complexes prone to dissociation by treatment with other detergents. In general, analyses of protein interactomes should be carried out by both BN- and CN-PAGE.

Electrophoresis, Polyacrylamide Gel↗
PubMed2025

USP7 Inhibitors Destabilize EBNA1 and Suppress Epstein-Barr Virus Tumorigenesis.

Epstein-Barr virus (EBV) is a ubiquitous human ɣ-herpesvirus implicated in various malignancies, including Burkitt's lymphoma and gastric carcinomas. In most EBV-associated cancers, the viral genome is maintained as an extrachromosomal episome by the EBV nuclear antigen-1 (EBNA1). EBNA1 is considered to be a highly stable protein that interacts with the ubiquitin-specific protease 7 (USP7). Here, we show that pharmacological inhibitors and small interfering RNA (siRNA) targeting USP7 reduce EBNA1 protein levels in a proteosome-dependent manner. Proteomic analysis revealed that USP7 inhibitor GNE6776 altered the EBNA1 protein interactome, including disrupting USP7 association with EBNA1. GNE6776 also inhibited EBNA1 binding to EBV oriP DNA and reduced viral episome copy number. Transcriptomic studies revealed that USP7 inhibition affected chromosome segregation and mitotic cell division pathways in EBV+ cells. Finally, we show that GNE6776 selectively inhibited EBV+ gastric and lymphoid cell proliferation in cell culture and slowed EBV+ tumor growth in mouse xenograft models. These findings suggest that USP7 inhibitors perturb EBNA1 stability and function and may be exploited to treat EBV latent infection and tumorigenesis.

Ubiquitin-Specific Peptidase 7↗
PubMed2005

Immunoaffinity separation of plasma proteins by IgY microbeads: meeting the needs of proteomic sample preparation and analysis.

Separation of complex protein mixtures that have a wide dynamic range of concentration, such as plasma or serum, is a challenge for proteomic analysis. Sample preparation to remove high-abundant proteins is essential for proteomics analysis. Immunoglobulin yolk (IgY) antibodies have unique and advantageous features that enable specific protein removal to aid in the detection of low-abundant proteins and biomarker discovery. This report describes the efficiency and effectiveness of IgY microbeads in separating 12 abundant proteins from plasma with an immunoaffinity spin column or LC column. The protein separation and sample preparation process was monitored via SDS-PAGE, 2-DE, LC-MS/MS, or clinical protein assays. The data demonstrate the high specificity of the protein separation, with removal of 95-99.5% of the abundant proteins. IgY microbeads against human proteins can also selectively remove orthologous proteins of other mammals such as mouse, rat, etc. Besides the specificity and reproducibility of the IgY microbeads, the report discusses the factors that may cause potential variations in protein separation such as protein-protein interactions (known as "Interactome"), binding and washing conditions of immunoaffinity reagents, etc. A novel concept of Seppromics is introduced to address methodologies and science of protein separation in a context of proteomics.

Albumins↗