Multi-parameter photon-by-photon hidden Markov modeling

Paul David Harris (), Alessandra Narducci, Christian Gebhardt, Thorben Cordes, Shimon Weiss and Eitan Lerner ()
Additional contact information
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
Eitan Lerner: The Hebrew University of Jerusalem

Nature Communications, 2022, vol. 13, issue 1, 1-12

Abstract: 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.

Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
https://www.nature.com/articles/s41467-022-28632-x Abstract (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-28632-x

Ordering information: This journal article can be ordered from
https://www.nature.com/ncomms/

DOI: 10.1038/s41467-022-28632-x

Access Statistics for this article

Nature Communications is currently edited by Nathalie Le Bot, Enda Bergin and Fiona Gillespie

More articles in Nature Communications from Nature
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().