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Stochastic optical reconstruction microscopy–based relative localization analysis (STORM-RLA) for quantitative nanoscale assessment of spatial protein organization

The spatial association between proteins is crucial to understanding how they function in biological systems. Colocalization analysis of fluorescence microscopy images is widely used to assess this. However, colocalization analysis performed on two-dimensional images with diffraction-limited resolut...

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Detalles Bibliográficos
Autores principales: Veeraraghavan, Rengasayee, Gourdie, Robert G.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The American Society for Cell Biology 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5221590/
https://www.ncbi.nlm.nih.gov/pubmed/27307586
http://dx.doi.org/10.1091/mbc.E16-02-0125
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author Veeraraghavan, Rengasayee
Gourdie, Robert G.
author_facet Veeraraghavan, Rengasayee
Gourdie, Robert G.
author_sort Veeraraghavan, Rengasayee
collection PubMed
description The spatial association between proteins is crucial to understanding how they function in biological systems. Colocalization analysis of fluorescence microscopy images is widely used to assess this. However, colocalization analysis performed on two-dimensional images with diffraction-limited resolution merely indicates that the proteins are within 200–300 nm of each other in the xy-plane and within 500–700 nm of each other along the z-axis. Here we demonstrate a novel three-dimensional quantitative analysis applicable to single-molecule positional data: stochastic optical reconstruction microscopy–based relative localization analysis (STORM-RLA). This method offers significant advantages: 1) STORM imaging affords 20-nm resolution in the xy-plane and <50 nm along the z-axis; 2) STORM-RLA provides a quantitative assessment of the frequency and degree of overlap between clusters of colabeled proteins; and 3) STORM-RLA also calculates the precise distances between both overlapping and nonoverlapping clusters in three dimensions. Thus STORM-RLA represents a significant advance in the high-throughput quantitative assessment of the spatial organization of proteins.
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spelling pubmed-52215902017-01-22 Stochastic optical reconstruction microscopy–based relative localization analysis (STORM-RLA) for quantitative nanoscale assessment of spatial protein organization Veeraraghavan, Rengasayee Gourdie, Robert G. Mol Biol Cell Articles The spatial association between proteins is crucial to understanding how they function in biological systems. Colocalization analysis of fluorescence microscopy images is widely used to assess this. However, colocalization analysis performed on two-dimensional images with diffraction-limited resolution merely indicates that the proteins are within 200–300 nm of each other in the xy-plane and within 500–700 nm of each other along the z-axis. Here we demonstrate a novel three-dimensional quantitative analysis applicable to single-molecule positional data: stochastic optical reconstruction microscopy–based relative localization analysis (STORM-RLA). This method offers significant advantages: 1) STORM imaging affords 20-nm resolution in the xy-plane and <50 nm along the z-axis; 2) STORM-RLA provides a quantitative assessment of the frequency and degree of overlap between clusters of colabeled proteins; and 3) STORM-RLA also calculates the precise distances between both overlapping and nonoverlapping clusters in three dimensions. Thus STORM-RLA represents a significant advance in the high-throughput quantitative assessment of the spatial organization of proteins. The American Society for Cell Biology 2016-11-07 /pmc/articles/PMC5221590/ /pubmed/27307586 http://dx.doi.org/10.1091/mbc.E16-02-0125 Text en © 2016 Veeraraghavan and Gourdie. This article is distributed by The American Society for Cell Biology under license from the author(s). Two months after publication it is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0). “ASCB®,” “The American Society for Cell Biology®,” and “Molecular Biology of the Cell®” are registered trademarks of The American Society for Cell Biology.
spellingShingle Articles
Veeraraghavan, Rengasayee
Gourdie, Robert G.
Stochastic optical reconstruction microscopy–based relative localization analysis (STORM-RLA) for quantitative nanoscale assessment of spatial protein organization
title Stochastic optical reconstruction microscopy–based relative localization analysis (STORM-RLA) for quantitative nanoscale assessment of spatial protein organization
title_full Stochastic optical reconstruction microscopy–based relative localization analysis (STORM-RLA) for quantitative nanoscale assessment of spatial protein organization
title_fullStr Stochastic optical reconstruction microscopy–based relative localization analysis (STORM-RLA) for quantitative nanoscale assessment of spatial protein organization
title_full_unstemmed Stochastic optical reconstruction microscopy–based relative localization analysis (STORM-RLA) for quantitative nanoscale assessment of spatial protein organization
title_short Stochastic optical reconstruction microscopy–based relative localization analysis (STORM-RLA) for quantitative nanoscale assessment of spatial protein organization
title_sort stochastic optical reconstruction microscopy–based relative localization analysis (storm-rla) for quantitative nanoscale assessment of spatial protein organization
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5221590/
https://www.ncbi.nlm.nih.gov/pubmed/27307586
http://dx.doi.org/10.1091/mbc.E16-02-0125
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