Single-fibril Förster resonance energy transfer imaging and deep learning reveal concentration dependence of amyloid β 42 aggregation pathways

单纤维Förster共振能量转移成像和深度学习揭示了淀粉样蛋白β42聚集途径的浓度依赖性

阅读:2

Abstract

Amyloid fibril formation is a highly heterogeneous process as evidenced by polymorphism in fibril structure. It has been suggested that different polymorphs are associated with different diseases or disease subtypes. Detailed characterization of this heterogeneity is a key to understanding the aggregation mechanism and, possibly, the disease mechanism. In this work, we develop Förster resonance energy transfer (FRET) imaging of amyloid fibril formation in real time and investigate the concentration-dependent heterogeneous fibril formation of amyloid β 42 (Aβ42). We incubated a mixture of unlabeled and labeled (5% donor and 5% acceptor) Aβ42, followed aggregation, and characterized individual fibrils in terms of FRET efficiency, acceptor fluorescence lifetime, and stoichiometry of the donor- and acceptor-labeled monomers incorporated into the fibrils. By FRET efficiency, we found that there are two distinct species at a relatively low concentration, 2 μM. The high FRET species appears first, but the low FRET species becomes dominant at later times. On the other hand, the high FRET species dominates throughout aggregation at 4 μM. The broad FRET efficiency distributions are consistent with those calculated from various known fibril structures. In addition to the FRET efficiencies, different acceptor lifetimes at the two concentrations and broad acceptor density distributions indicate at least three structurally distinct fibril species exist at each concentration, which also differ between the two different concentrations. The distinct heterogeneity in fibril formation pathways depending on the monomer concentration highlights the importance of understanding heterogeneity in the context of the biologically relevant aggregation environment.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。