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Citation
Llavero Hurtado, M., Fuller, H.R., Wong, A.M.S., Eaton, S.L., Gillingwater, T.H., Pennetta, G., Cooper, J.D., Wishart, T.M. (2017). Proteomic mapping of differentially vulnerable pre-synaptic populations identifies regulators of neuronal stability in vivo.  Sci. Rep. 7(1): 12412.
FlyBase ID
FBrf0236800
Publication Type
Research paper
Abstract
Synapses are an early pathological target in many neurodegenerative diseases ranging from well-known adult onset conditions such as Alzheimer and Parkinson disease to neurodegenerative conditions of childhood such as spinal muscular atrophy (SMA) and neuronal ceroid lipofuscinosis (NCLs). However, the reasons why synapses are particularly vulnerable to such a broad range of neurodegeneration inducing stimuli remains unknown. To identify molecular modulators of synaptic stability and degeneration, we have used the Cln3 (-/-) mouse model of a juvenile form of NCL. We profiled and compared the molecular composition of anatomically-distinct, differentially-affected pre-synaptic populations from the Cln3 (-/-) mouse brain using proteomics followed by bioinformatic analyses. Identified protein candidates were then tested using a Drosophila CLN3 model to study their ability to modify the CLN3-neurodegenerative phenotype in vivo. We identified differential perturbations in a range of molecular cascades correlating with synaptic vulnerability, including valine catabolism and rho signalling pathways. Genetic and pharmacological targeting of key 'hub' proteins in such pathways was sufficient to modulate phenotypic presentation in a Drosophila CLN3 model. We propose that such a workflow provides a target rich method for the identification of novel disease regulators which could be applicable to the study of other conditions where appropriate models exist.
PubMed ID
PubMed Central ID
PMC5622084 (PMC) (EuropePMC)
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    Language of Publication
    English
    Additional Languages of Abstract
    Parent Publication
    Publication Type
    Journal
    Abbreviation
    Sci. Rep.
    Title
    Scientific reports
    ISBN/ISSN
    2045-2322
    Data From Reference
    Alleles (6)
    Genes (5)
    Human Disease Models (1)
    Transgenic Constructs (6)