Multi-parameter photon-by-photon hidden Markov modeling

Harris, Paul David; Narducci, Alessandra; Gebhardt, Christian; Cordes, Thorben; Weiss, Shimon und Lerner, Eitan (2022): Multi-parameter photon-by-photon hidden Markov modeling. In: Nature Communications, Bd. 13, Nr. 1, 1000

Abstract

In this work, the authors demonstrate the application of multi-parameter photon-by-photon hidden Markov modeling (mpH(2)MM) on alternating laser excitation (ALEX)-based smFRET measurements. The utility of mpH(2)MM in identifying and quantifying dynamic biomolecular sub-populations is demonstrated in three different systems. Single molecule Forster resonance energy transfer (smFRET) is a unique biophysical approach for studying conformational dynamics in biomacromolecules. Photon-by-photon hidden Markov modeling ((HMM)-M-2) is an analysis tool that can quantify FRET dynamics of single biomolecules, even if they occur on the sub-millisecond timescale. However, dye photophysical transitions intertwined with FRET dynamics may cause artifacts. Here, we introduce multi-parameter (HMM)-M-2 (mpH(2)MM), which assists in identifying FRET dynamics based on simultaneous observation of multiple experimentally-derived parameters. We show the importance of using mpH(2)MM to decouple FRET dynamics caused by conformational changes from photophysical transitions in confocal-based smFRET measurements of a DNA hairpin, the maltose binding protein, MalE, and the type-III secretion system effector, YopO, from Yersinia species, all exhibiting conformational dynamics ranging from the sub-second to microsecond timescales. Overall, we show that using mpH(2)MM facilitates the identification and quantification of biomolecular sub-populations and their origin.

• Dokumententyp: Zeitschriftenartikel
• Fakultät: Biologie
• Themengebiete: 500 Naturwissenschaften und Mathematik > 570 Biowissenschaften; Biologie
• Sprache: Englisch