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Multi-parameter photon-by-photon hidden Markov modeling

Author

Listed:
  • Paul David Harris

    (The Hebrew University of Jerusalem)

  • Alessandra Narducci

    (Ludwig-Maximilians-Universität München)

  • Christian Gebhardt

    (Ludwig-Maximilians-Universität München)

  • Thorben Cordes

    (Ludwig-Maximilians-Universität München)

  • Shimon Weiss

    (University of California
    University of California)

  • Eitan Lerner

    (The Hebrew University of Jerusalem
    The Hebrew University of Jerusalem)

Abstract

Single molecule Förster resonance energy transfer (smFRET) is a unique biophysical approach for studying conformational dynamics in biomacromolecules. Photon-by-photon hidden Markov modeling (H2MM) 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 H2MM (mpH2MM), which assists in identifying FRET dynamics based on simultaneous observation of multiple experimentally-derived parameters. We show the importance of using mpH2MM 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 mpH2MM facilitates the identification and quantification of biomolecular sub-populations and their origin.

Suggested Citation

  • Paul David Harris & Alessandra Narducci & Christian Gebhardt & Thorben Cordes & Shimon Weiss & Eitan Lerner, 2022. "Multi-parameter photon-by-photon hidden Markov modeling," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
    • Handle: RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-28632-x
    DOI: 10.1038/s41467-022-28632-x
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    Cited by:

    1. Martin F. Peter & Christian Gebhardt & Rebecca Mächtel & Gabriel G. Moya Muñoz & Janin Glaenzer & Alessandra Narducci & Gavin H. Thomas & Thorben Cordes & Gregor Hagelueken, 2022. "Cross-validation of distance measurements in proteins by PELDOR/DEER and single-molecule FRET," Nature Communications, Nature, vol. 13(1), pages 1-19, December.
    2. Markus Götz & Anders Barth & Søren S.-R. Bohr & Richard Börner & Jixin Chen & Thorben Cordes & Dorothy A. Erie & Christian Gebhardt & Mélodie C. A. S. Hadzic & George L. Hamilton & Nikos S. Hatzakis &, 2022. "A blind benchmark of analysis tools to infer kinetic rate constants from single-molecule FRET trajectories," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
    3. Hyunju Cho & Yumeng Liu & SangYoon Chung & Sowmya Chandrasekar & Shimon Weiss & Shu-ou Shan, 2024. "Dynamic stability of Sgt2 enables selective and privileged client handover in a chaperone triad," Nature Communications, Nature, vol. 15(1), pages 1-16, December.

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