Single‐Molecule Two‐Color Coincidence Detection of Unlabeled alpha‐Synuclein Aggregates. (28th February 2023)

• Record Type: Journal Article
• Authors: Chappard, Alexandre; Leighton, Craig; Saleeb, Rebecca S.; Jeacock, Kiani; Ball, Sarah R.; Morris, Katie; Kantelberg, Owen; Lee, Ji‐Eun; Zacco, Elsa; Pastore, Annalisa; Sunde, Margaret; Clarke, David J.; Downey, Patrick; Kunath, Tilo; Horrocks, Mathew H.
• Is Part Of: Angewandte Chemie. Volume 135:Number 15(2023)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2023-02-28
• Subjects: Aggregation or Oligomerization -- Fluorescence -- Microscopy -- Proteins -- Single-Molecule; Chemistry -- Periodicals; 540
• DOI: 10.1002/ange.202216771
• Languages: English
• ISSNs: 0044-8249

Abstract

Abstract: Protein misfolding and aggregation into oligomeric and fibrillar structures is a common feature of many neurogenerative disorders. Single‐molecule techniques have enabled characterization of these lowly abundant, highly heterogeneous protein aggregates, previously inaccessible using ensemble averaging techniques. However, they usually rely on the use of recombinantly‐expressed labeled protein, or on the addition of amyloid stains that are not protein‐specific. To circumvent these challenges, we have made use of a high affinity antibody labeled with orthogonal fluorophores combined with fast‐flow microfluidics and single‐molecule confocal microscopy to specifically detect α‐synuclein, the protein associated with Parkinson's disease. We used this approach to determine the number and size of α‐synuclein aggregates down to picomolar concentrations in biologically relevant samples. Abstract : Pathological protein aggregates in neurodegenerative disorders are difficult to characterise using current methods. We present a novel single‐molecule detection method to specifically detect and characterise α‐synuclein aggregates at picomolar concentrations. We demonstrate the ability to detect aggregates in biologically relevant samples.