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Quantification of amyloid fibril polymorphism by nano-morphometry reveals the individuality of filament assembly
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-...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9814634/ https://www.ncbi.nlm.nih.gov/pubmed/36703355 http://dx.doi.org/10.1038/s42004-020-00372-3 |
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author | Aubrey, Liam D. Blakeman, Ben J. F. Lutter, Liisa Serpell, Christopher J. Tuite, Mick F. Serpell, Louise C. Xue, Wei-Feng |
author_facet | Aubrey, Liam D. Blakeman, Ben J. F. Lutter, Liisa Serpell, Christopher J. Tuite, Mick F. Serpell, Louise C. Xue, Wei-Feng |
author_sort | Aubrey, Liam D. |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-9814634 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-98146342023-01-10 Quantification of amyloid fibril polymorphism by nano-morphometry reveals the individuality of filament assembly Aubrey, Liam D. Blakeman, Ben J. F. Lutter, Liisa Serpell, Christopher J. Tuite, Mick F. Serpell, Louise C. Xue, Wei-Feng Commun Chem Article 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. Nature Publishing Group UK 2020-09-11 /pmc/articles/PMC9814634/ /pubmed/36703355 http://dx.doi.org/10.1038/s42004-020-00372-3 Text en © The Author(s) 2020 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Aubrey, Liam D. Blakeman, Ben J. F. Lutter, Liisa Serpell, Christopher J. Tuite, Mick F. Serpell, Louise C. Xue, Wei-Feng Quantification of amyloid fibril polymorphism by nano-morphometry reveals the individuality of filament assembly |
title | Quantification of amyloid fibril polymorphism by nano-morphometry reveals the individuality of filament assembly |
title_full | Quantification of amyloid fibril polymorphism by nano-morphometry reveals the individuality of filament assembly |
title_fullStr | Quantification of amyloid fibril polymorphism by nano-morphometry reveals the individuality of filament assembly |
title_full_unstemmed | Quantification of amyloid fibril polymorphism by nano-morphometry reveals the individuality of filament assembly |
title_short | Quantification of amyloid fibril polymorphism by nano-morphometry reveals the individuality of filament assembly |
title_sort | quantification of amyloid fibril polymorphism by nano-morphometry reveals the individuality of filament assembly |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9814634/ https://www.ncbi.nlm.nih.gov/pubmed/36703355 http://dx.doi.org/10.1038/s42004-020-00372-3 |
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