Towards a Proteome-scale Map of the Human Protein-Protein Interaction Network
Center for Cancer Systems Biology and Department of Cancer Biology, Dana-Farber Cancer Institute, Harvard Medical School, 44 Binney Street, Boston, Massachusetts 02115, USA. Nature
(Impact Factor: 41.46).
11/2005; 437(7062):1173-8. DOI: 10.1038/nature04209
Systematic mapping of protein-protein interactions, or 'interactome' mapping, was initiated in model organisms, starting with defined biological processes and then expanding to the scale of the proteome. Although far from complete, such maps have revealed global topological and dynamic features of interactome networks that relate to known biological properties, suggesting that a human interactome map will provide insight into development and disease mechanisms at a systems level. Here we describe an initial version of a proteome-scale map of human binary protein-protein interactions. Using a stringent, high-throughput yeast two-hybrid system, we tested pairwise interactions among the products of approximately 8,100 currently available Gateway-cloned open reading frames and detected approximately 2,800 interactions. This data set, called CCSB-HI1, has a verification rate of approximately 78% as revealed by an independent co-affinity purification assay, and correlates significantly with other biological attributes. The CCSB-HI1 data set increases by approximately 70% the set of available binary interactions within the tested space and reveals more than 300 new connections to over 100 disease-associated proteins. This work represents an important step towards a systematic and comprehensive human interactome project.
Available from: Chenggang Yu
- "High-and low-throughput experimental assays are available to screen physical interactions among proteins within and between species (Rual et al., 2005; Konig et al., 2008). For interpretation and analysis, these interactions are often represented as PPI networks, in which network nodes correspond to proteins and edges between nodes represent the observed protein interactions. "
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ABSTRACT: The multifactorial nature of traumatic brain injury (TBI), especially the complex secondary tissue injury involving intertwined networks of molecular pathways that mediate cellular behavior, has confounded attempts to elucidate the pathology underlying the progression of TBI. Here, systems biology strategies are exploited to identify novel molecular mechanisms and protein indicators of brain injury. To this end, we performed a meta-analysis of four distinct high-throughput gene expression studies involving different animal models of TBI. By using canonical pathways and a large human protein-interaction network as a scaffold, we separately overlaid the gene expression data from each study to identify molecular signatures that were conserved across the different studies. At 24 hr after injury, the significantly activated molecular signatures were nonspecific to TBI, whereas the significantly suppressed molecular signatures were specific to the nervous system. In particular, we identified a suppressed subnetwork consisting of 58 highly interacting, coregulated proteins associated with synaptic function. We selected three proteins from this subnetwork, postsynaptic density protein 95, nitric oxide synthase 1, and disrupted in schizophrenia 1, and hypothesized that their abundance would be significantly reduced after TBI. In a penetrating ballistic-like brain injury rat model of severe TBI, Western blot analysis confirmed our hypothesis. In addition, our analysis recovered 12 previously identified protein biomarkers of TBI. The results suggest that systems biology may provide an efficient, high-yield approach to generate testable hypotheses that can be experimentally validated to identify novel mechanisms of action and molecular indicators of TBI. © 2014 Wiley Periodicals, Inc.
Available from: PubMed Central
- "For example, affinity purification coupled to mass spectrometry (AP-MS) [3, 4] and luminescence-based mammalian interactome mapping (LUMIER)  provide information on complexes, and yeast-two-hybrid (Y2H) experiments give insights into binary PPIs , as summarized in Table 1. Despite the significant advances being made the last decade, the human interactome is still largely uncharted and the accumulated knowledge is biased towards well-studied proteins [1, 6]. "
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ABSTRACT: Phage display is a powerful technique for profiling specificities of peptide binding domains. The method is suited for the identification of high-affinity ligands with inhibitor potential when using highly diverse combinatorial peptide phage libraries. Such experiments further provide consensus motifs for genome-wide scanning of ligands of potential biological relevance. A complementary but considerably less explored approach is to display expression products of genomic DNA, cDNA, open reading frames (ORFs), or oligonucleotide libraries designed to encode defined regions of a target proteome on phage particles. One of the main applications of such proteomic libraries has been the elucidation of antibody epitopes. This review is focused on the use of proteomic phage display to uncover protein-protein interactions of potential relevance for cellular function. The method is particularly suited for the discovery of interactions between peptide binding domains and their targets. We discuss the largely unexplored potential of this method in the discovery of domain-motif interactions of potential biological relevance.
Available from: Lu-Lu Zheng
- "A thorough analysis of virus-host interactomes may reveal insights into viral infection and pathogenic strategies and help identify novel drug targets  and decipher the molecular aetiology of some complex diseases . With the help of high-throughput experiments    such as yeast-two hybrid screens or literature mining, researchers have collected many virus-host PPIs, generating invaluable virus-host PPI databases   and tried to provide a global view of human cellular processes controlled "
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ABSTRACT: Viral infections result in millions of deaths in the world today. A thorough analysis of virus-host interactomes may reveal insights into viral infection and pathogenic strategies. In this study, we presented a landscape of virus-host interactomes based on protein domain interaction. Compared to the analysis at protein level, this domain-domain interactome provided a unique abstraction of protein-protein interactome. Through comparisons among DNA, RNA, and retrotranscribing viruses, we identified a core of human domains, that viruses used to hijack the cellular machinery and evade the immune system, which might be promising antiviral drug targets. We showed that viruses preferentially interacted with host hub and bottleneck domains, and the degree and betweenness centrality among three categories of viruses are significantly different. Further analysis at functional level highlighted that different viruses perturbed the host cellular molecular network by common and unique strategies. Most importantly, we creatively proposed a viral disease network among viral domains, human domains and the corresponding diseases, which uncovered several unknown virus-disease relationships that needed further verification. Overall, it is expected that the findings will help to deeply understand the viral infection and contribute to the development of antiviral therapy.
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