Single-photon smFRET: II. Application to continuous illumination

Ayush Saurabh; Matthew Safar; Mohamadreza Fazel; Ioannis Sgouralis; Steve Pressé

doi:10.1016/j.bpr.2022.100087

Single-photon smFRET: II. Application to continuous illumination

Biophys Rep (N Y). 2022 Dec 2;3(1):100087. doi: 10.1016/j.bpr.2022.100087. eCollection 2023 Mar 8.

Authors

Ayush Saurabh^{1

2}, Matthew Safar^{1

3}, Mohamadreza Fazel^{1

2}, Ioannis Sgouralis⁴, Steve Pressé^{1

2

5}

Affiliations

¹ Center for Biological Physics, Arizona State University, Tempe, Arizona.
² Department of Physics, Arizona State University, Tempe, Arizona.
³ Department of Mathematics and Statistical Science, Arizona State University, Tempe, Arizona.
⁴ Department of Mathematics, University of Tennessee Knoxville, Knoxville, Tennessee.
⁵ School of Molecular Sciences, Arizona State University, Tempe, Arizona.

Abstract

Here we adapt the Bayesian nonparametrics (BNP) framework presented in the first companion article to analyze kinetics from single-photon, single-molecule Förster resonance energy transfer (smFRET) traces generated under continuous illumination. Using our sampler, BNP-FRET, we learn the escape rates and the number of system states given a photon trace. We benchmark our method by analyzing a range of synthetic and experimental data. Particularly, we apply our method to simultaneously learn the number of system states and the corresponding kinetics for intrinsically disordered proteins using two-color FRET under varying chemical conditions. Moreover, using synthetic data, we show that our method can deduce the number of system states even when kinetics occur at timescales of interphoton intervals.