Single-Molecule Two-Color Coincidence Detection of Unlabeled alpha-Synuclein Aggregates.
Aggregation or Oligomerization
Fluorescence
Microscopy
Proteins
Single-Molecule
Journal
Angewandte Chemie (Weinheim an der Bergstrasse, Germany)
ISSN: 0044-8249
Titre abrégé: Angew Chem Weinheim Bergstr Ger
Pays: Germany
ID NLM: 100955692
Informations de publication
Date de publication:
03 Apr 2023
03 Apr 2023
Historique:
received:
14
11
2022
medline:
22
3
2024
pubmed:
22
3
2024
entrez:
22
3
2024
Statut:
ppublish
Résumé
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. 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.
Autres résumés
Type: Publisher
(ger)
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.
Identifiants
pubmed: 38516037
doi: 10.1002/ange.202216771
pii: ANGE202216771
pmc: PMC10952349
doi:
Types de publication
Journal Article
Langues
eng
Pagination
e202216771Informations de copyright
© 2023 The Authors. Angewandte Chemie published by Wiley-VCH GmbH.
Déclaration de conflit d'intérêts
The authors declare no conflict of interest.