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Norway

PMID:25609609  

A53T human α-synuclein overexpression in transgenic mice induces pervasive mitochondria macroautophagy defects preceding dopamine neuron degeneration.

Linan Chen | Zhiguo Xie | Susie Turkson | Xiaoxi Zhuang
The Journal of neuroscience : the official journal of the Society for Neuroscience | 2015

In vitro evidence suggests that the inefficient removal of damaged mitochondria by macroautophagy contributes to Parkinson's disease (PD). Using a tissue-specific gene amplification strategy, we generated a transgenic mouse line with human α-synuclein A53T overexpression specifically in dopamine (DA) neurons. Transgenic mice showed profound early-onset mitochondria abnormalities, characterized by macroautophagy marker-positive cytoplasmic inclusions containing mainly mitochondrial remnants, which preceded the degeneration of DA neurons. Genetic deletion of either parkin or PINK1 in these transgenic mice significantly worsened mitochondrial pathologies, including drastically enlarged inclusions and loss of total mitochondria contents. These data suggest that mitochondria are the main targets of α-synuclein and their defective autophagic clearance plays a significant role during pathogenesis. Moreover, endogenous PINK1 or parkin is indispensable for the proper autophagic removal of damaged mitochondria. Our data for the first time establish an essential link between mitochondria macroautophagy impairments and DA neuron degeneration in an in vivo model based on known PD genetics. The model, its well-defined pathologies, and the demonstration of a main pathogenesis pathway in the present study have set the stage and direction of emphasis for future studies.

Pubmed ID: 25609609

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Associated grants

  • Agency: NCRR NIH HHS, United States
    Id: UL1 RR024999
  • Agency: NCATS NIH HHS, United States
    Id: UL1 TR000430
  • Agency: NCRR NIH HHS, United States
    Id: UL1RR024999

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Gene Expression Omnibus (GEO) (tool)

RRID:SCR_005012

Functional genomics data repository supporting MIAME-compliant data submissions. Includes microarray-based experiments measuring the abundance of mRNA, genomic DNA, and protein molecules, as well as non-array-based technologies such as serial analysis of gene expression (SAGE) and mass spectrometry proteomic technology. Array- and sequence-based data are accepted. Collection of curated gene expression DataSets, as well as original Series and Platform records. The database can be searched using keywords, organism, DataSet type and authors. DataSet records contain additional resources including cluster tools and differential expression queries.

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