Presynaptic alpha-synuclein aggregation in a mouse model of Parkinson's disease

Kateri J. Spinelli, Jonathan K. Taylor, Valerie R. Osterberg, Madeline J. Churchill, Eden Pollock, Cynthia Moore, Charles K. Meshul, Vivek K. Unni

Research output: Contribution to journalArticlepeer-review

112 Scopus citations

Abstract

Parkinson's disease and dementia with Lewy bodies are associated with abnormal neuronal aggregation of α-synuclein. However, the mechanisms of aggregation and their relationship to disease are poorly understood. We developed an in vivo multiphoton imaging paradigm to study α-synuclein aggregation in mouse cortex with subcellular resolution. We used a green fluorescent protein-tagged human α-synuclein mouse line that has moderate overexpression levels mimicking human disease. Fluorescence recovery after photobleaching (FRAP) of labeled protein demonstrated that somatic α-synuclein existed primarily in an unbound, soluble pool. In contrast, α-synuclein in presynaptic terminals was in at least three different pools: (1) as unbound, soluble protein; (2) bound to presynaptic vesicles; and (3) as microaggregates. Serial imaging of microaggregates over 1 week demonstrated a heterogeneous population with differing α-synuclein exchange rates. The microaggregate species were resistant to proteinase K, phosphorylated at serine-129, oxidized, and associated with a decrease in the presynaptic vesicle protein synapsin and glutamate immunogold labeling. Multiphoton FRAP provided the specific binding constants for α-synuclein's binding to synaptic vesicles and its effective diffusion coefficient in the soma and axon, setting the stage for future studies targeting synuclein modifications and their effects. Our in vivo results suggest that, under moderate overexpression conditions, α-synuclein aggregates are selectively found in presynaptic terminals.

Original languageEnglish (US)
Pages (from-to)2037-2050
Number of pages14
JournalJournal of Neuroscience
Volume34
Issue number6
DOIs
StatePublished - 2014

ASJC Scopus subject areas

  • General Neuroscience

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