Identification of human proteins that modify misfolding and proteotoxicity of pathogenic ataxin-1

Proteins with long, pathogenic polyglutamine (polyQ) sequences have an enhanced propensity to spontaneously misfold and self-assemble into insoluble protein aggregates. Here, we have identified 21 human proteins that influence polyQ-induced ataxin-1 misfolding and proteotoxicity in cell model systems. By analyzing the protein sequences of these modifiers, we discovered a recurrent presence of coiled-coil (CC) domains in ataxin-1 toxicity enhancers, while such domains were not present in suppressors. This suggests that CC domains contribute to the aggregation- and toxicity-promoting effects of modifiers in mammalian cells. We found that the ataxin-1–interacting protein MED15, computationally predicted to possess an N-terminal CC domain, enhances spontaneous ataxin-1 aggregation in cell-based assays, while no such effect was observed with the truncated protein MED15ΔCC, lacking such a domain. Studies with recombinant proteins confirmed these results and demonstrated that the N-terminal CC domain of MED15 (MED15CC) per se is sufficient to promote spontaneous ataxin-1 aggregation in vitro. Moreover, we observed that a hybrid Pum1 protein harboring the MED15CC domain promotes ataxin-1 aggregation in cell model systems. In strong contrast, wild-type Pum1 lacking a CC domain did not stimulate ataxin-1 polymerization. These results suggest that proteins with CC domains are potent enhancers of polyQ-mediated protein misfolding and aggregation in vitro and in vivo

Interactome mapping provides a network of neurodegenerative disease proteins and uncovers widespread protein aggregation in affected brains

Interactome maps are valuable resources to elucidate protein function and disease mechanisms. Here, we report on an interactome map that focuses on neurodegenerative disease (ND), connects ∼5,000 human proteins via ∼30,000 candidate interactions and is generated by systematic yeast two-hybrid interaction screening of ∼500 ND-related proteins and integration of literature interactions. This network reveals interconnectivity across diseases and links many known ND-causing proteins, such as α-synuclein, TDP-43, and ATXN1, to a host of proteins previously unrelated to NDs. It facilitates the identification of interacting proteins that significantly influence mutant TDP-43 and HTT toxicity in transgenic flies, as well as of ARF-GEP(100) that controls misfolding and aggregation of multiple ND-causing proteins in experimental model systems. Furthermore, it enables the prediction of ND-specific subnetworks and the identification of proteins, such as ATXN1 and MKL1, that are abnormally aggregated in postmortem brains of Alzheimer's disease patients, suggesting widespread protein aggregation in NDs

HDNetDB: A Molecular Interaction Database for Network-Oriented Investigations into Huntington’s Disease

Huntington's disease (HD) is a progressive and fatal neurodegenerative disorder caused by an expanded CAG repeat in the huntingtin gene. Although HD is monogenic, its molecular manifestation appears highly complex and involves multiple cellular processes. The recent application of high throughput platforms such as microarrays and mass-spectrometry has indicated multiple pathogenic routes. The massive data generated by these techniques together with the complexity of the pathogenesis, however, pose considerable challenges to researchers. Network-based methods can provide valuable tools to consolidate newly generated data with existing knowledge, and to decipher the interwoven molecular mechanisms underlying HD. To facilitate research on HD in a network-oriented manner, we have developed HDNetDB, a database that integrates molecular interactions with many HD-relevant datasets. It allows users to obtain, visualize and prioritize molecular interaction networks using HD-relevant gene expression, phenotypic and other types of data obtained from human samples or model organisms. We illustrated several HDNetDB functionalities through a case study and identified proteins that constitute potential cross-talk between HD and the unfolded protein response (UPR). HDNetDB is publicly accessible at http://hdnetdb.sysbiolab.eu.CHDI Foundation [A-2666]; Portuguese Fundacao para a Ciencia e a Tecnologia [SFRH/BPD/70718/2010, SFRH/BPD/96890/2013, IF/00881/2013, UID/BIM/04773/2013 - CBMR, UID/Multi/04326/2013 - CCMAR]info:eu-repo/semantics/publishedVersio

Disease related protein network [Proteinnetzwerk, das im Zusammenhang mit einer Krankheit steht]

The present invention relates to a method for generating a network of direct and indirect interaction partners of a disease-related (poly)peptide comprising the steps of (a) contacting a selection of (poly)peptides suspected to contain one or several of said direct or indirect interaction partners with said disease-related (poly)peptides and optionally with known direct or indirect interaction partners of said diseaserelated (poly)peptide under conditions that allow the interaction between interaction partners to occur; (b) detecting (poly)peptides that interact with said disease-related (poly)peptide or with said known direct or indirect interaction partners of said disease-related (poly) peptide; (c) contacting (poly)peptides detected in step (b) with a selection of (poly) peptides suspected to contain one or several (poly)peptides interacting with said (poly)peptides detected in step (b) under conditions that allow the interaction between interaction partners to occur; (d) detecting proteins that interact with said (poly) peptides detected in step (b); (e) contacting said disease related (poly)peptide and optionally said known direct or indirect interaction partners of said disease-related (poly)peptide, said (poly)peptides detected in steps (b) and (d) and a selection of proteins suspected to contain one or several (poly)peptides interacting with any of the afore mentioned (poly)peptides under conditions that allow the interaction between interaction partners to occur; (f) detecting (poly)peptides that interact with said disease-related (poly)peptide and optionally said known direct or indirect interaction partners of said disease-related (poly)peptide or with said (poly)peptides identified in step (b) or (d); and (g) generating a (poly)peptide(poly)peptide interaction network of said disease-related (poly)peptide and optionally said known direct or indirect interaction partners of said disease-related (poly)peptide and said (poly)peptides identified in steps (b), (d) and (f). Moreover, the present invention relates to a protein complex comprising at least two proteins and to methods for identifying compounds interfering with an interaction of said proteins. Finally, the present invention relates to a pharmaceutical composition and to the use of compounds identified by the present invention for the preparation of a pharmaceutical composition for the treatment of Huntington's disease

Method for the identification of protein-protein interactions in disease related protein networks [Verfahren zur Identifizierung von Protein-Protein-Wechselwirkungen in krankheitsbezogenen Proteinnetzwerken]

The present invention relates to a method for identification of a protein-protein interaction of protein interaction partners in a disease-related network of proteins comprising the steps of (a) identifying nucleic acid molecules by at least partial 5'sequencing and, optionally, additionally adding recombinantly cloned and sequenced nucleic acid molecules, wherein said nucleic acid molecules encode a selection of proteins suspected to contain one or several of said interaction partners and wherein said nucleic acid molecules are annotated with a positional information; (b) in frame cloning of the nucleic acid molecules of step (a) into prey and bait vectors, wherein one copy of each nucleic acid molecule is cloned into said prey vector and a second copy of each nucleic acid molecule is cloned into said bait vector; (c) transforming a first suitable host cell with the prey vector obtained in step (b) and a second suitable host cell with the bait vector obtained in step (b), wherein said first and said second host cell have a different genetic constitution and can be mated; (d) mating the first suitable host cell of step (c) with the second suitable host cell of step (c), and expressing the proteins encoded by the nucleic acid molecules obtained in step (b); (e) selecting the mated host cell obtained in step (d) on the basis of a selection advantage which is caused by the protein-protein interaction between the protein interaction partner encoded by the nucleic acid molecule of the prey vector contained in said cell and the protein interaction partner encoded by the nucleic acid molecule of the bait vector contained in said cell; and (f) identifying with the positional information obtained in step (a) the protein interaction partners of step (e) and thereby identifying the protein-protein interaction

The winged-helix transcription factor JUMU regulates development, nucleolus morphology and function, and chromatin organization of Drosophila melanogaster

The PEV-modifying winged-helix/forkhead domain transcription factor JUMU of Drosophila is an essential protein of pleiotropic function. The correct gene dose of jumu is required for nucleolar integrity and correct nucleolus function. Overexpression of jumu results in bloating of euchromatic chromosome arms, displacement of the JUMU protein from the chromocenter and the nucleolus, fragile weak points, and disrupted chromocenter of polytene chromosomes. Overexpression of the acidic C terminus of JUMU alone causes nucleolus disorganization. In addition, euchromatic genes are overexpressed and HP1, which normally accumulates in the pericentric heterochromatin and spreads into euchromatic chromosome arms, although H3-K9 di-methylation remains restricted to the pericentric heterochromatin. The human winged-helix nude gene shows similarities to jumu and its overexpression in Drosophila causes bristle mutations

Identification of VCP/p97, CHIP and amphiphysin II interaction partners using membrane-based human proteome arrays

Proteins mediate their biological function through interactions with other proteins. Therefore, the systematic identification and characterization of protein-protein interactions have become a powerful proteomic strategy to understand protein function and comprehensive cellular regulatory networks. For the screening of valosin-containing protein, carboxyl terminus of Hsp70-interacting protein (CHIP), and amphiphysin II interaction partners, we utilized a membrane-based array technology that allows the identification of human protein-protein interactions with crude bacterial cell extracts. Many novel interaction pairs such as valosin-containing protein/autocrine motility factor receptor, CHIP/caytaxin, or amphiphysin II/DLP4 were identified and subsequently confirmed by pull-down, two-hybrid and co-immunoprecipitation experiments. In addition, assays were performed to validate the interactions functionally. CHIP e.g. was found to efficiently polyubiquitinate caytaxin in vitro, suggesting that it might influence caytaxin degradation in vivo. Using peptide arrays, we also identified the binding motifs in the proteins DLP4, XRCC4, and fructose-1,6-bisphosphatase, which are crucial for the association with the Src homology 3 domain of amphiphysin II. Together these studies indicate that our human proteome array technology permits the identification of protein-protein interactions that are functionally involved in neurodegenerative disease processes, the degradation of protein substrates, and the transport of membrane vesicles

Mol Cell

Analysis of protein-protein interactions (PPIs) is a valuable approach for characterizing proteins of unknown function. Here, we have developed a strategy combining library and matrix yeast two-hybrid screens to generate a highly connected PPI network for Huntington's disease (HD). The network contains 186 PPIs among 35 bait and 51 prey proteins. It revealed 165 new potential interactions, 32 of which were confirmed by independent binding experiments. The network also permitted the functional annotation of 16 uncharacterized proteins and facilitated the discovery of GIT1, a G protein-coupled receptor kinase-interacting protein, which enhances huntingtin aggregation by recruitment of the protein into membranous vesicles. Coimmunoprecipitations and immunofluorescence studies revealed that GIT1 and huntingtin associate in mammalian cells under physiological conditions. Moreover, GIT1 localizes to neuronal inclusions, and is selectively cleaved in HD brains, indicating that its distribution and function is altered during disease pathogenesis

A human protein-protein interaction network: a resource for annotating the proteome

Protein-protein interaction maps provide a valuable framework for a better understanding of the functional organization of the proteome. To detect interacting pairs of human proteins systematically, a protein matrix of 4456 baits and 5632 preys was screened by automated yeast two-hybrid (Y2H) interaction mating. We identified 3186 mostly novel interactions among 1705 proteins, resulting in a large, highly connected network. Independent pull-down and co-immunoprecipitation assays validated the overall quality of the Y2H interactions. Using topological and GO criteria, a scoring system was developed to define 911 high-confidence interactions among 401 proteins. Furthermore, the network was searched for interactions linking uncharacterized gene products and human disease proteins to regulatory cellular pathways. Two novel Axin-1 interactions were validated experimentally, characterizing ANP32A and CRMP1 as modulators of Wnt signaling. Systematic human protein interaction screens can lead to a more comprehensive understanding of protein function and cellular processes

Systematic interaction network filtering identifies CRMP1 as a novel suppressor of huntingtin misfolding and neurotoxicity

Assemblies of huntingtin (HTT) fragments with expanded polyglutamine (polyQ) tracts are a pathological hallmark of Huntington's disease (HD). The molecular mechanisms by which these structures are formed and cause neuronal dysfunction and toxicity are poorly understood. Here, we utilized available gene expression data sets of selected brain regions of HD patients and controls for systematic interaction network filtering in order to predict disease-relevant, brain region-specific HTT interaction partners. Starting from a large protein-protein interaction (PPI) data set, a step-by-step computational filtering strategy facilitated the generation of a focused PPI network that directly or indirectly connects 13 proteins potentially dysregulated in HD with the disease protein HTT. This network enabled the discovery of the neuron-specific protein CRMP1 that targets aggregation-prone, N-terminal HTT fragments and suppresses their spontaneous self-assembly into proteotoxic structures in various models of HD. Experimental validation indicates that our network filtering procedure provides a simple but powerful strategy to identify disease-relevant proteins that influence misfolding and aggregation of polyQ disease proteins