Quantification of amyloid fibril polymorphism by nano-morphometry reveals the individuality of filament assembly.

Autor: Aubrey LD; Kent Fungal Group, School of Biosciences, University of Kent, Canterbury, CT2 7NJ, UK., Blakeman BJF; Kent Fungal Group, School of Biosciences, University of Kent, Canterbury, CT2 7NJ, UK., Lutter L; Kent Fungal Group, School of Biosciences, University of Kent, Canterbury, CT2 7NJ, UK., Serpell CJ; School of Physical Sciences, University of Kent, Canterbury, CT2 7NH, UK., Tuite MF; Kent Fungal Group, School of Biosciences, University of Kent, Canterbury, CT2 7NJ, UK., Serpell LC; Sussex Neuroscience, School of Life Sciences, University of Sussex, Falmer, Brighton, BN1 9QG, UK., Xue WF; Kent Fungal Group, School of Biosciences, University of Kent, Canterbury, CT2 7NJ, UK. W.F.Xue@kent.ac.uk.
Jazyk: angličtina
Zdroj: Communications chemistry [Commun Chem] 2020 Sep 11; Vol. 3 (1), pp. 125. Date of Electronic Publication: 2020 Sep 11.
DOI: 10.1038/s42004-020-00372-3
Abstrakt: Amyloid fibrils are highly polymorphic structures formed by many different proteins. They provide biological function but also abnormally accumulate in numerous human diseases. The physicochemical principles of amyloid polymorphism are not understood due to lack of structural insights at the single-fibril level. To identify and classify different fibril polymorphs and to quantify the level of heterogeneity is essential to decipher the precise links between amyloid structures and their functional and disease associated properties such as toxicity, strains, propagation and spreading. Employing gentle, force-distance curve-based AFM, we produce detailed images, from which the 3D reconstruction of individual filaments in heterogeneous amyloid samples is achieved. Distinctive fibril polymorphs are then classified by hierarchical clustering, and sample heterogeneity is objectively quantified. These data demonstrate the polymorphic nature of fibril populations, provide important information regarding the energy landscape of amyloid self-assembly, and offer quantitative insights into the structural basis of polymorphism in amyloid populations.
(© 2020. The Author(s).)
Databáze: MEDLINE
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