Extraction of rapid kinetics from smFRET measurements using integrative detectors

Zeliha Kilic, Ioannis Sgouralis, Wooseok Heo, Kunihiko Ishii, Tahei Tahara, Steve Pressé

Research output: Contribution to journalArticlepeer-review

Abstract

Hidden Markov models (HMMs) are used to learn single-molecule kinetics across a range of experimental techniques. By their construction, HMMs assume that single-molecule events occur on slower timescales than those of data acquisition. To move beyond that HMM limitation and allow for single-molecule events to occur on any timescale, we must treat single-molecule events in continuous time as they occur in nature. We propose a method to learn kinetic rates from single-molecule Förster resonance energy transfer (smFRET) data collected by integrative detectors, even if those rates exceed data acquisition rates. To achieve that, we exploit our recently proposed “hidden Markov jump process” (HMJP), with which we learn transition kinetics from parallel measurements in donor and acceptor channels. HMJPs generalize the HMM paradigm in two critical ways: (1) they deal with physical smFRET systems as they switch between conformational states in continuous time, and (2) they estimate transition rates between conformational states directly without having recourse to transition probabilities or assuming slow dynamics. Our continuous-time treatment learns the transition kinetics and photon emission rates for dynamic regimes that are inaccessible to HMMs, which treat system kinetics in discrete time. We validate our framework's robustness on simulated data and demonstrate its performance on experimental data from FRET-labeled Holliday junctions.

Original languageEnglish (US)
Article number100409
JournalCell Reports Physical Science
Volume2
Issue number5
DOIs
StatePublished - May 19 2021

Keywords

  • fluorescence
  • hidden Markov jump process
  • single molecule data analysis
  • smFRET

ASJC Scopus subject areas

  • Physics and Astronomy(all)
  • Materials Science(all)
  • Chemistry(all)
  • Energy(all)
  • Engineering(all)

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