Details

Autor(en) / Beteiligte

• Harris, Paul David
• Narducci, Alessandra
• Gebhardt, Christian
• Cordes, Thorben
• Weiss, Shimon
• Lerner, Eitan

Titel

Multi-parameter photon-by-photon hidden Markov modeling

Ist Teil von

• Nature communications, 2022-02, Vol.13 (1), p.1000-1000, Article 1000

Ort / Verlag

England: Nature Publishing Group

Erscheinungsjahr

2022

Link zum Volltext

Quelle

Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals

Beschreibungen/Notizen

• Single molecule Förster resonance energy transfer (smFRET) is a unique biophysical approach for studying conformational dynamics in biomacromolecules. Photon-by-photon hidden Markov modeling (H MM) 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 H MM (mpH MM), which assists in identifying FRET dynamics based on simultaneous observation of multiple experimentally-derived parameters. We show the importance of using mpH 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 MM facilitates the identification and quantification of biomolecular sub-populations and their origin.