Single-photon SmFRET. I: Theory and Conceptual Basis
Overview
Affiliations
We present a unified conceptual framework and the associated software package for single-molecule Förster resonance energy transfer (smFRET) analysis from single-photon arrivals leveraging Bayesian nonparametrics, BNP-FRET. This unified framework addresses the following key physical complexities of a single-photon smFRET experiment, including: 1) fluorophore photophysics; 2) continuous time kinetics of the labeled system with large timescale separations between photophysical phenomena such as excited photophysical state lifetimes and events such as transition between system states; 3) unavoidable detector artefacts; 4) background emissions; 5) unknown number of system states; and 6) both continuous and pulsed illumination. These physical features necessarily demand a novel framework that extends beyond existing tools. In particular, the theory naturally brings us to a hidden Markov model with a second-order structure and Bayesian nonparametrics on account of items 1, 2, and 5 on the list. In the second and third companion articles, we discuss the direct effects of these key complexities on the inference of parameters for continuous and pulsed illumination, respectively.
Bayesian Inference of Binding Kinetics from Fluorescence Time Series.
Bryan 4th J, Bryan J, Tashev S, Fazel M, Scheckenbach M, Tinnefeld P bioRxiv. 2025; .
PMID: 39975252 PMC: 11838460. DOI: 10.1101/2025.02.03.636267.
Frost D, Cook K, Sanabria H ArXiv. 2024; .
PMID: 38699162 PMC: 11065046.
Avoiding matrix exponentials for large transition rate matrices.
Pessoa P, Schweiger M, Presse S J Chem Phys. 2024; 160(9).
PMID: 38436441 PMC: 10919955. DOI: 10.1063/5.0190527.
Building Fluorescence Lifetime Maps Photon-by-Photon by Leveraging Spatial Correlations.
Fazel M, Jazani S, Scipioni L, Vallmitjana A, Zhu S, Gratton E ACS Photonics. 2024; 10(10):3558-3569.
PMID: 38406580 PMC: 10890823. DOI: 10.1021/acsphotonics.3c00595.
Time-resolved burst variance analysis.
Terterov I, Nettels D, Makarov D, Hofmann H Biophys Rep (N Y). 2023; 3(3):100116.
PMID: 37559939 PMC: 10406964. DOI: 10.1016/j.bpr.2023.100116.