Single molecule tracking and analysis framework including theory-predicted parameter settings

Abstract Imaging, tracking and analyzing individual biomolecules in living systems is a powerful technology to obtain quantitative kinetic and spatial information such as reaction rates, diffusion coefficients and localization maps. Common tracking tools often operate on single movies and require ad...

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Autores principales:	Timo Kuhn, Johannes Hettich, Rubina Davtyan, J. Christof M. Gebhardt
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/e322431a14bd43cda465d8be9e63666c
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spelling	oai:doaj.org-article:e322431a14bd43cda465d8be9e63666c2021-12-02T14:29:09ZSingle molecule tracking and analysis framework including theory-predicted parameter settings10.1038/s41598-021-88802-72045-2322https://doaj.org/article/e322431a14bd43cda465d8be9e63666c2021-05-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-88802-7https://doaj.org/toc/2045-2322Abstract Imaging, tracking and analyzing individual biomolecules in living systems is a powerful technology to obtain quantitative kinetic and spatial information such as reaction rates, diffusion coefficients and localization maps. Common tracking tools often operate on single movies and require additional manual steps to analyze whole data sets or to compare different experimental conditions. We report a fast and comprehensive single molecule tracking and analysis framework (TrackIt) to simultaneously process several multi-movie data sets. A user-friendly GUI offers convenient tracking visualization, multiple state-of-the-art analysis procedures, display of results, and data im- and export at different levels to utilize external software tools. We applied our framework to quantify dissociation rates of a transcription factor in the nucleus and found that tracking errors, similar to fluorophore photobleaching, have to be considered for reliable analysis. Accordingly, we developed an algorithm, which accounts for both tracking losses and suggests optimized tracking parameters when evaluating reaction rates. Our versatile and extensible framework facilitates quantitative analysis of single molecule experiments at different experimental conditions.Timo KuhnJohannes HettichRubina DavtyanJ. Christof M. GebhardtNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-12 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Timo Kuhn Johannes Hettich Rubina Davtyan J. Christof M. Gebhardt Single molecule tracking and analysis framework including theory-predicted parameter settings
description	Abstract Imaging, tracking and analyzing individual biomolecules in living systems is a powerful technology to obtain quantitative kinetic and spatial information such as reaction rates, diffusion coefficients and localization maps. Common tracking tools often operate on single movies and require additional manual steps to analyze whole data sets or to compare different experimental conditions. We report a fast and comprehensive single molecule tracking and analysis framework (TrackIt) to simultaneously process several multi-movie data sets. A user-friendly GUI offers convenient tracking visualization, multiple state-of-the-art analysis procedures, display of results, and data im- and export at different levels to utilize external software tools. We applied our framework to quantify dissociation rates of a transcription factor in the nucleus and found that tracking errors, similar to fluorophore photobleaching, have to be considered for reliable analysis. Accordingly, we developed an algorithm, which accounts for both tracking losses and suggests optimized tracking parameters when evaluating reaction rates. Our versatile and extensible framework facilitates quantitative analysis of single molecule experiments at different experimental conditions.
format	article
author	Timo Kuhn Johannes Hettich Rubina Davtyan J. Christof M. Gebhardt
author_facet	Timo Kuhn Johannes Hettich Rubina Davtyan J. Christof M. Gebhardt
author_sort	Timo Kuhn
title	Single molecule tracking and analysis framework including theory-predicted parameter settings
title_short	Single molecule tracking and analysis framework including theory-predicted parameter settings
title_full	Single molecule tracking and analysis framework including theory-predicted parameter settings
title_fullStr	Single molecule tracking and analysis framework including theory-predicted parameter settings
title_full_unstemmed	Single molecule tracking and analysis framework including theory-predicted parameter settings
title_sort	single molecule tracking and analysis framework including theory-predicted parameter settings
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/e322431a14bd43cda465d8be9e63666c
work_keys_str_mv	AT timokuhn singlemoleculetrackingandanalysisframeworkincludingtheorypredictedparametersettings AT johanneshettich singlemoleculetrackingandanalysisframeworkincludingtheorypredictedparametersettings AT rubinadavtyan singlemoleculetrackingandanalysisframeworkincludingtheorypredictedparametersettings AT jchristofmgebhardt singlemoleculetrackingandanalysisframeworkincludingtheorypredictedparametersettings
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Single molecule tracking and analysis framework including theory-predicted parameter settings

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