Fluorescence Self-Quenching from Reporter Dyes Informs on the Structural Properties of Amyloid Clusters Formed in Vitro and in Cells
American Chemical Society
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Chen, W., Young, L., Lu, M., Zaccone, A., Ströhl, F., Yu, N., Kaminski, G., & et al. (2017). Fluorescence Self-Quenching from Reporter Dyes Informs on the Structural Properties of Amyloid Clusters Formed in Vitro and in Cells. Nano Letters, 17 (1), 143-149. https://doi.org/10.1021/acs.nanolett.6b03686
The characterization of the aggregation kinetics of protein amyloids and the structural properties of the ensuing aggregates are vital in the study of the pathogenesis of many neurodegenerative diseases and the discovery of therapeutic targets. In this article, we show that the fluorescence lifetime of synthetic dyes covalently attached to amyloid proteins informs on the structural properties of amyloid clusters formed both in vitro and in cells. We demonstrate that the mechanism behind such a "lifetime sensor" of protein aggregation is based on fluorescence self-quenching and that it offers a good dynamic range to report on various stages of aggregation without significantly perturbing the process under investigation. We show that the sensor informs on the structural density of amyloid clusters in a high-throughput and quantitative manner and in these aspects the sensor outperforms super-resolution imaging techniques. We demonstrate the power and speed of the method, offering capabilities, for example, in therapeutic screenings that monitor biological self-assembly. We investigate the mechanism and advantages of the lifetime sensor in studies of the K18 protein fragment of the Alzheimer's disease related protein tau and its amyloid aggregates formed in vitro. Finally, we demonstrate the sensor in the study of aggregates of polyglutamine protein, a model used in studies related to Huntington's disease, by performing correlative fluorescence lifetime imaging microscopy and structured-illumination microscopy experiments in cells.
FLIM, SIM, Self-quenching, amyloid aggregation, super-resolution
This work was supported by grants from the Leverhulme Trust; the Engineering and Physical Sciences Research Council, UK [EP/H018301/1]; the Medical Research Council [MR/ K015850/1, and MR/K02292X/1]; the Wellcome Trust [089703/Z/09/Z]; and the Alzheimer’s Research UK [ARUK-EG2012A-1]. WeiYue Chen is funded by China Scholarship Council; and Cambridge Commonwealth, European and International Trust for her PhD.
Alzheimer's Research UK (ARUK-PG2013-14)
Wellcome Trust (089703/Z/09/Z)
External DOI: https://doi.org/10.1021/acs.nanolett.6b03686
This record's URL: https://www.repository.cam.ac.uk/handle/1810/262771