Browsing by Author "Schnoegl, Sigrid"
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- Systematic interaction network filtering identifies CRMP1 as a novel suppressor of huntingtin misfolding and neurotoxicityPublication . Stroedicke, Martin; Bounab, Yacine; Strempel, Nadine; Klockmeier, Konrad; Yigit, Sargon; Friedrich, Ralf P.; Chaurasia, Gautam; Li, Shuang; Hesse, Franziska; Riechers, Sean-Patrick; Russ, Jenny; Nicoletti, Cecilia; Boeddrich, Annett; Wiglenda, Thomas; Haenig, Christian; Schnoegl, Sigrid; Fournier, David; Graham, Rona K.; Hayden, Michael R.; Sigrist, Stephan; Bates, Gillian P.; Priller, Josef; Andrade-Navarro, Miguel A.; Futschik, Matthias E.; Wanker, Erich E.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.
- UniHI 4: new tools for query, analysis and visualization of the human protein-protein interactomePublication . Chaurasia, Gautam; Malhotra, Soniya; Russ, Jenny; Schnoegl, Sigrid; Haenig, Christian; Wanker, Erich; Futschik, Matthias E.Human protein interaction maps have become important tools of biomedical research for the elucidation of molecular mechanisms and the identification of new modulators of disease processes. The Unified Human Interactome database (UniHI, http://www.unihi.org) provides researchers with a comprehensive platform to query and access human protein-protein interaction (PPI) data. Since its first release, UniHI has considerably increased in size. The latest update of UniHI includes over 250 000 interactions between similar to 22 300 unique proteins collected from 14 major PPI sources. However, this wealth of data also poses new challenges for researchers due to the complexity of interaction networks retrieved from the database. We therefore developed several new tools to query, analyze and visualize human PPI networks. Most importantly, UniHI allows now the construction of tissue-specific interaction networks and focused querying of canonical pathways. This will enable researchers to target their analysis and to prioritize candidate proteins for follow-up studies.