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Sökning: WFRF:(Ruepp MD)

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1.
  • Jutzi, D, et al. (författare)
  • Aberrant interaction of FUS with the U1 snRNA provides a molecular mechanism of FUS induced amyotrophic lateral sclerosis
  • 2020
  • Ingår i: Nature communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 11:1, s. 6341-
  • Tidskriftsartikel (refereegranskat)abstract
    • Mutations in the RNA-binding protein Fused in Sarcoma (FUS) cause early-onset amyotrophic lateral sclerosis (ALS). However, a detailed understanding of central RNA targets of FUS and their implications for disease remain elusive. Here, we use a unique blend of crosslinking and immunoprecipitation (CLIP) and NMR spectroscopy to identify and characterise physiological and pathological RNA targets of FUS. We find that U1 snRNA is the primary RNA target of FUS via its interaction with stem-loop 3 and provide atomic details of this RNA-mediated mode of interaction with the U1 snRNP. Furthermore, we show that ALS-associated FUS aberrantly contacts U1 snRNA at the Sm site with its zinc finger and traps snRNP biogenesis intermediates in human and murine motor neurons. Altogether, we present molecular insights into a FUS toxic gain-of-function involving direct and aberrant RNA-binding and strengthen the link between two motor neuron diseases, ALS and spinal muscular atrophy (SMA).
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2.
  • Ostaszewski, Marek, et al. (författare)
  • COVID19 Disease Map, a computational knowledge repository of virus-host interaction mechanisms
  • 2021
  • Ingår i: Molecular Systems Biology. - : John Wiley & Sons. - 1744-4292 .- 1744-4292. ; 17:10
  • Tidskriftsartikel (refereegranskat)abstract
    • We need to effectively combine the knowledge from surging literature with complex datasets to propose mechanistic models of SARS-CoV-2 infection, improving data interpretation and predicting key targets of intervention. Here, we describe a large-scale community effort to build an open access, interoperable and computable repository of COVID-19 molecular mechanisms. The COVID-19 Disease Map (C19DMap) is a graphical, interactive representation of disease-relevant molecular mechanisms linking many knowledge sources. Notably, it is a computational resource for graph-based analyses and disease modelling. To this end, we established a framework of tools, platforms and guidelines necessary for a multifaceted community of biocurators, domain experts, bioinformaticians and computational biologists. The diagrams of the C19DMap, curated from the literature, are integrated with relevant interaction and text mining databases. We demonstrate the application of network analysis and modelling approaches by concrete examples to highlight new testable hypotheses. This framework helps to find signatures of SARS-CoV-2 predisposition, treatment response or prioritisation of drug candidates. Such an approach may help deal with new waves of COVID-19 or similar pandemics in the long-term perspective.
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