open access

https://hdl.handle.net/2115/73900

Two-detector number and brightness analysis reveals spatio-temporal oligomerization of proteins in living cells

英語

Dimerization

2018-05-01

Elsevier

Methods

140

161-171

Number and brightness analysis (N&B) is a useful tool for the simultaneous visualization of protein oligomers and their localization, with single-molecule sensitivity. N&B determines particle brightness (fluorescence intensity per particle) and maps the spatial distribution of fluorescently labeled proteins by performing statistical analyses of the image series obtained using laser scanning microscopy. The brightness map reveals presence of the oligomers of the targeted protein and their distribution in living cells. However, even when corrections are applied, conventional N&B is affected by afterpulsing, shot noise, thermal noise, dead time, and overestimation of particle brightness when the concentration of the fluorescent particles changes during measurement. The drawbacks of conventional N&B can be circumvented by using two detectors, a novel approach that we henceforth call two-detector number and brightness analysis (TD-N&B), and introducing a linear regression of fluorescence intensity. This statistically eliminates the effect of noise from the detectors, and ensures that the correct particle brightness is obtained. Our method was theoretically assessed by numerical simulations and experimentally validated using a dilution series of purified enhanced green fluorescent protein (EGFP), EGFP tandem oligomers in cell lysate, and EGFP tandem oligomers in living cells. Furthermore, this method was used to characterize the complex process of ligand-induced glucocorticoid receptor dimerization and their translocation to the cell nucleus in live cells. Our method can be applied to other oligomer-forming proteins in cell signaling, or to aggregations of proteins such as those that cause neurodegenerative diseases. (C) 2018 Elsevier Inc. All rights reserved.

学術雑誌論文

Accepted Manuscript

Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International

©2018. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/

1046-2023