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

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.

Allostery through DNA drives phenotype switching

“…FRET histograms for ComK-binding experiments were fitted with a combination of two Gaussian distributions 64 , since all constructs used in these experiments had FRET values close to 0.5, thus showing no skewing. The width and position of these FRET peaks were fixed to the values obtained for the FRET distribution in the absence of ComK and in the presence of saturating amounts of ComK, which minimized the number of free fitting parameters.…”

Diffusion of the disordered E-cadherin tail on β-catenin

“…FRET histograms were fitted with a combination of empirical log-normal and Gaussian distributions 69 . For binding experiments with unlabelled β-cat, the width and position of the FRET-peaks were fixed to minimize the number of free fitting parameters and the area under the fitted histogram curve for each subpopulation was determined using numerical integration.…”

Slow Escape from a Helical Misfolded State of the Pore-Forming Toxin Cytolysin A

“…To extract mean transfer efficiencies, the resulting histograms for the measurements in 4 M GdmCl ( Figure 3 a, left column) were fitted with a Gaussian peak function for symmetric peaks (variants T2C/Q56C and A187C/K290C) and a four-parameter log-normal peak function for asymmetric peaks (variants Q56C/E252C, T2C/E252C, and T2C/V303C). 54 Measurements in the microfluidic device were all fitted with log-normal peak functions ( Figure 3 a, right column). Manual mixing data for refolding of the monomer were globally fitted with two Gaussian peak functions ( Figure S2 ).…”

“… 17 Single-molecule Förster resonance energy transfer (FRET) can be used to investigate time scales from nanoseconds to hours 23 , 24 and has helped to elucidate, e.g., interdomain misfolding in tandem repeat proteins 25 , 26 and complex folding kinetics. 27 , 28 Furthermore, single-molecule FRET is especially well suited for investigating the dimensions and dynamics of non-native states. 29 − 32 Here, we take advantage of the combination of single-molecule FRET with microfluidic mixing, 33 a versatile tool for the investigation of nonequilibrium dynamics from milliseconds to minutes.…”