Purification of a-synuclein containing inclusions from human post mortem brain tissue

Amellia Mccormack, Nusha Chegeni Farahani, Fariba Chegini, Alexander Colella, John Power, Damien Keating, Timothy Chataway

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    9 Citations (Scopus)

    Abstract

    Comparison with existing methods. Background: Neurodegenerative disorders affect a large proportion of the elderly population. A group of disorders, known as the α-synucleinopathies, are characterised by the presence of α-synuclein-containing protein inclusions, such as Lewy Bodies (LBs) found in neurons from Parkinson's Disease (PD) and Dementia with Lewy Bodies (DLB), and Glial Cytoplasmic Inclusions (GCIs) found in oligodendrocytes from Multiple System Atrophy (MSA). The analysis of the protein composition of inclusions has been hindered by limitations of methods for isolating the inclusions from the surrounding tissue. Method: Four modifications were made to the published method for GCI purification by Gai et al. (1999) which were: collecting the entire inclusion-containing part of the Percoll gradient; lysis of nuclei prior to DNAse digestion; limited tryptic digestion to release inclusions from the cytoskeletal meshwork; and increased antibody and magnetic bead concentrations/volumes to capture the larger amounts of inclusions. Results: The optimised method gave a 28-fold increase in yield compared to the published method of Gai et al. (1999). A 2D-DIGE comparison revealed a 3.8-fold increase in α-synuclein enrichment and a corresponding 5.2-fold reduction in tubulin contamination. This method was also successfully adapted to the purification of LBs from DLB tissue.A 2D-DIGE comparison of purified GCIs (n = 2) revealed that GCIs consist of 11.7% α-synuclein, 1.9% α-β-crystallin and 2.3% 14-3-3 proteins compared to 8.5%, 2.0% and 1.5% in LBs, respectively. Conclusions: This study has generated an improved method for the purification of α-synuclein-containing inclusions with a yield sufficient for multiple forms of analysis.

    Original languageEnglish
    Pages (from-to)141-150
    Number of pages10
    JournalJournal of Neuroscience Methods
    Volume266
    DOIs
    Publication statusPublished - 2016

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