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Quantifying kinetics from time series of single-molecule Förster resonance energy transfer efficiency histograms


Benke, Stephan; Nettels, Daniel; Hofmann, Hagen; Schuler, Benjamin (2017). Quantifying kinetics from time series of single-molecule Förster resonance energy transfer efficiency histograms. Nanotechnology, 28(11):114002.

Abstract

Single-molecule fluorescence spectroscopy is a powerful approach for probing biomolecular structure and dynamics, including protein folding. For the investigation of nonequilibrium kinetics, Förster resonance energy transfer combined with confocal multiparameter detection has proven particularly versatile, owing to the large number of observables and the broad range of accessible timescales, especially in combination with rapid microfluidic mixing. However, a comprehensive kinetic analysis of the resulting time series of transfer efficiency histograms and complementary observables can be challenging owing to the complexity of the data. Here we present and compare three different methods for the analysis of such kinetic data: singular value decomposition, multivariate curve resolution with alternating least square fitting, and model-based peak fitting, where an explicit model of both the transfer efficiency histogram of each species and the kinetic mechanism of the process is employed. While each of these methods has its merits for specific applications, we conclude that model-based peak fitting is most suitable for a quantitative analysis and comparison of kinetic mechanisms.

Abstract

Single-molecule fluorescence spectroscopy is a powerful approach for probing biomolecular structure and dynamics, including protein folding. For the investigation of nonequilibrium kinetics, Förster resonance energy transfer combined with confocal multiparameter detection has proven particularly versatile, owing to the large number of observables and the broad range of accessible timescales, especially in combination with rapid microfluidic mixing. However, a comprehensive kinetic analysis of the resulting time series of transfer efficiency histograms and complementary observables can be challenging owing to the complexity of the data. Here we present and compare three different methods for the analysis of such kinetic data: singular value decomposition, multivariate curve resolution with alternating least square fitting, and model-based peak fitting, where an explicit model of both the transfer efficiency histogram of each species and the kinetic mechanism of the process is employed. While each of these methods has its merits for specific applications, we conclude that model-based peak fitting is most suitable for a quantitative analysis and comparison of kinetic mechanisms.

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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:04 Faculty of Medicine > Department of Biochemistry
07 Faculty of Science > Department of Biochemistry
Dewey Decimal Classification:570 Life sciences; biology
610 Medicine & health
Language:English
Date:17 March 2017
Deposited On:12 Apr 2017 13:01
Last Modified:19 Mar 2018 08:12
Publisher:IOP Publishing
ISSN:0957-4484
OA Status:Green
Free access at:PubMed ID. An embargo period may apply.
Publisher DOI:https://doi.org/10.1088/1361-6528/aa5abd
PubMed ID:28103588

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