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Single molecule tracking and analysis framework including theory-predicted parameter settings
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...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8096815/ https://www.ncbi.nlm.nih.gov/pubmed/33947895 http://dx.doi.org/10.1038/s41598-021-88802-7 |
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author | Kuhn, Timo Hettich, Johannes Davtyan, Rubina Gebhardt, J. Christof M. |
author_facet | Kuhn, Timo Hettich, Johannes Davtyan, Rubina Gebhardt, J. Christof M. |
author_sort | Kuhn, Timo |
collection | PubMed |
description | 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 | Online Article Text |
id | pubmed-8096815 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-80968152021-05-05 Single molecule tracking and analysis framework including theory-predicted parameter settings Kuhn, Timo Hettich, Johannes Davtyan, Rubina Gebhardt, J. Christof M. Sci Rep Article 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. Nature Publishing Group UK 2021-05-04 /pmc/articles/PMC8096815/ /pubmed/33947895 http://dx.doi.org/10.1038/s41598-021-88802-7 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Kuhn, Timo Hettich, Johannes Davtyan, Rubina Gebhardt, J. Christof M. Single molecule tracking and analysis framework including theory-predicted parameter settings |
title | 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_short | Single molecule tracking and analysis framework including theory-predicted parameter settings |
title_sort | single molecule tracking and analysis framework including theory-predicted parameter settings |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8096815/ https://www.ncbi.nlm.nih.gov/pubmed/33947895 http://dx.doi.org/10.1038/s41598-021-88802-7 |
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