4.7 Review

Monitoring α-synuclein aggregation

Journal

NEUROBIOLOGY OF DISEASE
Volume 176, Issue -, Pages -

Publisher

ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.nbd.2022.105966

Keywords

Synucleinopathy; Parkinson?s disease; ?-Synuclein; Oligomerization; Fibril; Amyloid; Fluorescence; Polymorphism; Structural techniques

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Synucleinopathies are a group of diseases characterized by the misfolding and aggregation of alpha-synuclein, leading to the formation of Lewy bodies. Studying the aggregation of alpha-synuclein is crucial for understanding these diseases, and recent breakthroughs have provided new insights into their mechanisms.
Synucleinopathies, including Parkinson's disease (PD), dementia with Lewy Bodies (DLB), and multiple system atrophy (MSA), are characterized by the misfolding and subsequent aggregation of alpha-synuclein (alpha-syn) that accumulates in cytoplasmic inclusions bodies in the cells of affected brain regions. Since the seminal report of likely-aggregated alpha-syn presence within the Lewy bodies by Spillantini et al. in 1997, the keyword synuclein aggregation has appeared in over 6000 papers (Source: PubMed October 2022). Studying, observing, describing, and quantifying alpha-syn aggregation is therefore of paramount importance, whether it happens in tubo, in vitro, in post-mortem samples, or in vivo. The past few years have witnessed tremendous progress in understanding ag-gregation mechanisms and identifying various polymorphs. In this context of growing complexity, it is of utmost importance to understand what tools we possess, what exact information they provide, and in what context they may be applied. Nonetheless, it is also crucial to rationalize the relevance of the information and the limitations of these methods for gauging the final result. In this review, we present the main techniques that have shaped the current views about alpha-syn structure and dynamics, with particular emphasis on the recent breakthroughs that may change our understanding of synucleinopathies.

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