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KERA: analysis tool for multi-process, multi-state single-molecule data

Molecular machines within cells dynamically assemble, disassemble and reorganize. Molecular interactions between their components can be observed at the single-molecule level and quantified using colocalization single-molecule spectroscopy, in which individual labeled molecules are seen transiently...

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Autores principales: Tibbs, Joseph, Ghoneim, Mohamed, Caldwell, Colleen C, Buzynski, Troy, Bowie, Wayne, Boehm, Elizabeth M, Washington, M Todd, Tabei, S M Ali, Spies, Maria
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8136784/
https://www.ncbi.nlm.nih.gov/pubmed/33660771
http://dx.doi.org/10.1093/nar/gkab087
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author Tibbs, Joseph
Ghoneim, Mohamed
Caldwell, Colleen C
Buzynski, Troy
Bowie, Wayne
Boehm, Elizabeth M
Washington, M Todd
Tabei, S M Ali
Spies, Maria
author_facet Tibbs, Joseph
Ghoneim, Mohamed
Caldwell, Colleen C
Buzynski, Troy
Bowie, Wayne
Boehm, Elizabeth M
Washington, M Todd
Tabei, S M Ali
Spies, Maria
author_sort Tibbs, Joseph
collection PubMed
description Molecular machines within cells dynamically assemble, disassemble and reorganize. Molecular interactions between their components can be observed at the single-molecule level and quantified using colocalization single-molecule spectroscopy, in which individual labeled molecules are seen transiently associating with a surface-tethered partner, or other total internal reflection fluorescence microscopy approaches in which the interactions elicit changes in fluorescence in the labeled surface-tethered partner. When multiple interacting partners can form ternary, quaternary and higher order complexes, the types of spatial and temporal organization of these complexes can be deduced from the order of appearance and reorganization of the components. Time evolution of complex architectures can be followed by changes in the fluorescence behavior in multiple channels. Here, we describe the kinetic event resolving algorithm (KERA), a software tool for organizing and sorting the discretized fluorescent trajectories from a range of single-molecule experiments. KERA organizes the data in groups by transition patterns, and displays exhaustive dwell time data for each interaction sequence. Enumerating and quantifying sequences of molecular interactions provides important information regarding the underlying mechanism of the assembly, dynamics and architecture of the macromolecular complexes. We demonstrate KERA’s utility by analyzing conformational dynamics of two DNA binding proteins: replication protein A and xeroderma pigmentosum complementation group D helicase.
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spelling pubmed-81367842021-05-25 KERA: analysis tool for multi-process, multi-state single-molecule data Tibbs, Joseph Ghoneim, Mohamed Caldwell, Colleen C Buzynski, Troy Bowie, Wayne Boehm, Elizabeth M Washington, M Todd Tabei, S M Ali Spies, Maria Nucleic Acids Res Methods Online Molecular machines within cells dynamically assemble, disassemble and reorganize. Molecular interactions between their components can be observed at the single-molecule level and quantified using colocalization single-molecule spectroscopy, in which individual labeled molecules are seen transiently associating with a surface-tethered partner, or other total internal reflection fluorescence microscopy approaches in which the interactions elicit changes in fluorescence in the labeled surface-tethered partner. When multiple interacting partners can form ternary, quaternary and higher order complexes, the types of spatial and temporal organization of these complexes can be deduced from the order of appearance and reorganization of the components. Time evolution of complex architectures can be followed by changes in the fluorescence behavior in multiple channels. Here, we describe the kinetic event resolving algorithm (KERA), a software tool for organizing and sorting the discretized fluorescent trajectories from a range of single-molecule experiments. KERA organizes the data in groups by transition patterns, and displays exhaustive dwell time data for each interaction sequence. Enumerating and quantifying sequences of molecular interactions provides important information regarding the underlying mechanism of the assembly, dynamics and architecture of the macromolecular complexes. We demonstrate KERA’s utility by analyzing conformational dynamics of two DNA binding proteins: replication protein A and xeroderma pigmentosum complementation group D helicase. Oxford University Press 2021-02-28 /pmc/articles/PMC8136784/ /pubmed/33660771 http://dx.doi.org/10.1093/nar/gkab087 Text en © The Author(s) 2021. Published by Oxford University Press on behalf of Nucleic Acids Research. https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) ), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Methods Online
Tibbs, Joseph
Ghoneim, Mohamed
Caldwell, Colleen C
Buzynski, Troy
Bowie, Wayne
Boehm, Elizabeth M
Washington, M Todd
Tabei, S M Ali
Spies, Maria
KERA: analysis tool for multi-process, multi-state single-molecule data
title KERA: analysis tool for multi-process, multi-state single-molecule data
title_full KERA: analysis tool for multi-process, multi-state single-molecule data
title_fullStr KERA: analysis tool for multi-process, multi-state single-molecule data
title_full_unstemmed KERA: analysis tool for multi-process, multi-state single-molecule data
title_short KERA: analysis tool for multi-process, multi-state single-molecule data
title_sort kera: analysis tool for multi-process, multi-state single-molecule data
topic Methods Online
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8136784/
https://www.ncbi.nlm.nih.gov/pubmed/33660771
http://dx.doi.org/10.1093/nar/gkab087
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