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Time-resolved burst variance analysis
Quantifying biomolecular dynamics has become a major task of single-molecule fluorescence spectroscopy methods. In single-molecule Förster resonance energy transfer (smFRET), kinetic information is extracted from the stream of photons emitted by attached donor and acceptor fluorophores. Here, we des...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10406964/ https://www.ncbi.nlm.nih.gov/pubmed/37559939 http://dx.doi.org/10.1016/j.bpr.2023.100116 |
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author | Terterov, Ivan Nettels, Daniel Makarov, Dmitrii E. Hofmann, Hagen |
author_facet | Terterov, Ivan Nettels, Daniel Makarov, Dmitrii E. Hofmann, Hagen |
author_sort | Terterov, Ivan |
collection | PubMed |
description | Quantifying biomolecular dynamics has become a major task of single-molecule fluorescence spectroscopy methods. In single-molecule Förster resonance energy transfer (smFRET), kinetic information is extracted from the stream of photons emitted by attached donor and acceptor fluorophores. Here, we describe a time-resolved version of burst variance analysis that can quantify kinetic rates at microsecond to millisecond timescales in smFRET experiments of diffusing molecules. Bursts are partitioned into segments with a fixed number of photons. The FRET variance is computed from these segments and compared with the variance expected from shot noise. By systematically varying the segment size, dynamics at different timescales can be captured. We provide a theoretical framework to extract kinetic rates from the decay of the FRET variance with increasing segment size. Compared to other methods such as filtered fluorescence correlation spectroscopy, recurrence analysis of single particles, and two-dimensional lifetime correlation spectroscopy, fewer photons are needed to obtain reliable timescale estimates, which reduces the required measurement time. |
format | Online Article Text |
id | pubmed-10406964 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-104069642023-08-09 Time-resolved burst variance analysis Terterov, Ivan Nettels, Daniel Makarov, Dmitrii E. Hofmann, Hagen Biophys Rep (N Y) Article Quantifying biomolecular dynamics has become a major task of single-molecule fluorescence spectroscopy methods. In single-molecule Förster resonance energy transfer (smFRET), kinetic information is extracted from the stream of photons emitted by attached donor and acceptor fluorophores. Here, we describe a time-resolved version of burst variance analysis that can quantify kinetic rates at microsecond to millisecond timescales in smFRET experiments of diffusing molecules. Bursts are partitioned into segments with a fixed number of photons. The FRET variance is computed from these segments and compared with the variance expected from shot noise. By systematically varying the segment size, dynamics at different timescales can be captured. We provide a theoretical framework to extract kinetic rates from the decay of the FRET variance with increasing segment size. Compared to other methods such as filtered fluorescence correlation spectroscopy, recurrence analysis of single particles, and two-dimensional lifetime correlation spectroscopy, fewer photons are needed to obtain reliable timescale estimates, which reduces the required measurement time. Elsevier 2023-07-07 /pmc/articles/PMC10406964/ /pubmed/37559939 http://dx.doi.org/10.1016/j.bpr.2023.100116 Text en © 2023 The Authors https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Terterov, Ivan Nettels, Daniel Makarov, Dmitrii E. Hofmann, Hagen Time-resolved burst variance analysis |
title | Time-resolved burst variance analysis |
title_full | Time-resolved burst variance analysis |
title_fullStr | Time-resolved burst variance analysis |
title_full_unstemmed | Time-resolved burst variance analysis |
title_short | Time-resolved burst variance analysis |
title_sort | time-resolved burst variance analysis |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10406964/ https://www.ncbi.nlm.nih.gov/pubmed/37559939 http://dx.doi.org/10.1016/j.bpr.2023.100116 |
work_keys_str_mv | AT terterovivan timeresolvedburstvarianceanalysis AT nettelsdaniel timeresolvedburstvarianceanalysis AT makarovdmitriie timeresolvedburstvarianceanalysis AT hofmannhagen timeresolvedburstvarianceanalysis |