4.6 Article

Transgenic Mice Expressing Human α-Synuclein 1-103 Fragment as a Novel Model of Parkinson's Disease

期刊

FRONTIERS IN AGING NEUROSCIENCE
卷 13, 期 -, 页码 -

出版社

FRONTIERS MEDIA SA
DOI: 10.3389/fnagi.2021.760781

关键词

Parkinson's disease; alpha-synuclein; asparagine endopeptidase; mouse model; neurodegenerative disease

资金

  1. National Natural Science Foundation of China [81771382, 81822016, 81901090, 81901291]

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Parkinson's disease (PD) is a common neurodegenerative disorder with unclear cellular and molecular mechanisms, lacking appropriate animal models mimicking its pathogenesis. The newly designed N103 mouse model exhibits PD-like features, including pathological protein accumulation, neuron loss, and behavioral impairments. Transcriptomics analysis suggests that this mouse model may offer new insights into PD research.
Parkinson's disease (PD) is one of the most common neurodegenerative disorders. However, its cellular and molecular mechanisms still wrap in the mist. This is partially caused by the absence of appropriate animal models mimicking sporadic PD that constitutes the majority of cases. Previously, we reported that a cysteine protease, asparagine endopeptidase (AEP), is activated in an age-dependent manner, and cleaves alpha-synuclein in the brain of sporadic PD patients. The AEP-derived alpha-synuclein 1-103 fragment is required for the pathogenesis of PD. Thus, we designed and characterized a novel transgenic mouse line expressing alpha-synuclein 1-103 (designated N103 mice). This model shows an abundant accumulation of pathological alpha-synuclein in the central nervous system, loss of dopaminergic neurons in the substantia nigra, and progressive striatal synaptic degeneration. The N103 mice also manifest age-dependent PD-like behavioral impairments. Notably, the mice show weight loss and constipation, which are the common non-motor symptoms in PD. The RNA-sequencing analysis found that the transcriptomics pattern was extensively altered in N103 mice. In conclusion, the N103 mouse line, as a brand-new tool, might provide new insights into PD research.

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