Model-free photon analysis of diffusion-based single-molecule FRET experiments
Abstract Photon-by-photon analysis tools for diffusion-based single-molecule Förster resonance energy transfer (smFRET) experiments often describe protein dynamics with Markov models. However, FRET efficiencies are only projections of the conformational space such that the measured dynamics can appe...
Saved in:
| Main Authors: | , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-07-01
|
| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-025-60764-8 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849238358239215616 |
|---|---|
| author | Ivan Terterov Daniel Nettels Tanya Lastiza-Male Kim Bartels Christian Löw Renee Vancraenenbroeck Itay Carmel Gabriel Rosenblum Hagen Hofmann |
| author_facet | Ivan Terterov Daniel Nettels Tanya Lastiza-Male Kim Bartels Christian Löw Renee Vancraenenbroeck Itay Carmel Gabriel Rosenblum Hagen Hofmann |
| author_sort | Ivan Terterov |
| collection | DOAJ |
| description | Abstract Photon-by-photon analysis tools for diffusion-based single-molecule Förster resonance energy transfer (smFRET) experiments often describe protein dynamics with Markov models. However, FRET efficiencies are only projections of the conformational space such that the measured dynamics can appear non-Markovian. Model-free methods to quantify FRET efficiency fluctuations would be desirable in this case. Here, we present such an approach. We determine FRET efficiency correlation functions free of artifacts from the finite length of photon trajectories or the diffusion of molecules through the confocal volume. We show that these functions capture the dynamics of proteins from nano- to milliseconds both in simulation and experiment, which provides a rigorous validation of current model-based analysis approaches. |
| format | Article |
| id | doaj-art-5fdbdb46fb5246108073f033d75f7b15 |
| institution | Kabale University |
| issn | 2041-1723 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Nature Communications |
| spelling | doaj-art-5fdbdb46fb5246108073f033d75f7b152025-08-20T04:01:40ZengNature PortfolioNature Communications2041-17232025-07-0116111610.1038/s41467-025-60764-8Model-free photon analysis of diffusion-based single-molecule FRET experimentsIvan Terterov0Daniel Nettels1Tanya Lastiza-Male2Kim Bartels3Christian Löw4Renee Vancraenenbroeck5Itay Carmel6Gabriel Rosenblum7Hagen Hofmann8Department of Chemical and Structural Biology, Weizmann Institute of ScienceDepartment of Biochemistry, University of ZurichDepartment of Chemical and Structural Biology, Weizmann Institute of ScienceCentre for Structural Systems Biology (CSSB) DESYCentre for Structural Systems Biology (CSSB) DESYDepartment of Chemical and Structural Biology, Weizmann Institute of ScienceDepartment of Chemical and Structural Biology, Weizmann Institute of ScienceDepartment of Chemical and Structural Biology, Weizmann Institute of ScienceDepartment of Chemical and Structural Biology, Weizmann Institute of ScienceAbstract Photon-by-photon analysis tools for diffusion-based single-molecule Förster resonance energy transfer (smFRET) experiments often describe protein dynamics with Markov models. However, FRET efficiencies are only projections of the conformational space such that the measured dynamics can appear non-Markovian. Model-free methods to quantify FRET efficiency fluctuations would be desirable in this case. Here, we present such an approach. We determine FRET efficiency correlation functions free of artifacts from the finite length of photon trajectories or the diffusion of molecules through the confocal volume. We show that these functions capture the dynamics of proteins from nano- to milliseconds both in simulation and experiment, which provides a rigorous validation of current model-based analysis approaches.https://doi.org/10.1038/s41467-025-60764-8 |
| spellingShingle | Ivan Terterov Daniel Nettels Tanya Lastiza-Male Kim Bartels Christian Löw Renee Vancraenenbroeck Itay Carmel Gabriel Rosenblum Hagen Hofmann Model-free photon analysis of diffusion-based single-molecule FRET experiments Nature Communications |
| title | Model-free photon analysis of diffusion-based single-molecule FRET experiments |
| title_full | Model-free photon analysis of diffusion-based single-molecule FRET experiments |
| title_fullStr | Model-free photon analysis of diffusion-based single-molecule FRET experiments |
| title_full_unstemmed | Model-free photon analysis of diffusion-based single-molecule FRET experiments |
| title_short | Model-free photon analysis of diffusion-based single-molecule FRET experiments |
| title_sort | model free photon analysis of diffusion based single molecule fret experiments |
| url | https://doi.org/10.1038/s41467-025-60764-8 |
| work_keys_str_mv | AT ivanterterov modelfreephotonanalysisofdiffusionbasedsinglemoleculefretexperiments AT danielnettels modelfreephotonanalysisofdiffusionbasedsinglemoleculefretexperiments AT tanyalastizamale modelfreephotonanalysisofdiffusionbasedsinglemoleculefretexperiments AT kimbartels modelfreephotonanalysisofdiffusionbasedsinglemoleculefretexperiments AT christianlow modelfreephotonanalysisofdiffusionbasedsinglemoleculefretexperiments AT reneevancraenenbroeck modelfreephotonanalysisofdiffusionbasedsinglemoleculefretexperiments AT itaycarmel modelfreephotonanalysisofdiffusionbasedsinglemoleculefretexperiments AT gabrielrosenblum modelfreephotonanalysisofdiffusionbasedsinglemoleculefretexperiments AT hagenhofmann modelfreephotonanalysisofdiffusionbasedsinglemoleculefretexperiments |