Cargando…
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...
Autores principales: | , |
---|---|
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 |
_version_ | 1782492848007938048 |
---|---|
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. |
format | Online Article Text |
id | pubmed-5221590 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | The American Society for Cell Biology |
record_format | MEDLINE/PubMed |
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 |
work_keys_str_mv | AT veeraraghavanrengasayee stochasticopticalreconstructionmicroscopybasedrelativelocalizationanalysisstormrlaforquantitativenanoscaleassessmentofspatialproteinorganization AT gourdierobertg stochasticopticalreconstructionmicroscopybasedrelativelocalizationanalysisstormrlaforquantitativenanoscaleassessmentofspatialproteinorganization |