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Methodology for Quantitative Characterization of Fluorophore Photoswitching to Predict Superresolution Microscopy Image Quality

Single-molecule localization microscopy (SMLM) image quality and resolution strongly depend on the photoswitching properties of fluorophores used for sample labeling. Development of fluorophores with optimized photoswitching will considerably improve SMLM spatial and spectral resolution. Currently,...

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Autores principales: Bittel, Amy M., Nickerson, Andrew, Saldivar, Isaac S., Dolman, Nick J., Nan, Xiaolin, Gibbs, Summer L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4944197/
https://www.ncbi.nlm.nih.gov/pubmed/27412307
http://dx.doi.org/10.1038/srep29687
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author Bittel, Amy M.
Nickerson, Andrew
Saldivar, Isaac S.
Dolman, Nick J.
Nan, Xiaolin
Gibbs, Summer L.
author_facet Bittel, Amy M.
Nickerson, Andrew
Saldivar, Isaac S.
Dolman, Nick J.
Nan, Xiaolin
Gibbs, Summer L.
author_sort Bittel, Amy M.
collection PubMed
description Single-molecule localization microscopy (SMLM) image quality and resolution strongly depend on the photoswitching properties of fluorophores used for sample labeling. Development of fluorophores with optimized photoswitching will considerably improve SMLM spatial and spectral resolution. Currently, evaluating fluorophore photoswitching requires protein-conjugation before assessment mandating specific fluorophore functionality, which is a major hurdle for systematic characterization. Herein, we validated polyvinyl alcohol (PVA) as a single-molecule environment to efficiently quantify the photoswitching properties of fluorophores and identified photoswitching properties predictive of quality SMLM images. We demonstrated that the same fluorophore photoswitching properties measured in PVA films and using antibody adsorption, a protein-conjugation environment analogous to labeled cells, were significantly correlated to microtubule width and continuity, surrogate measures of SMLM image quality. Defining PVA as a fluorophore photoswitching screening platform will facilitate SMLM fluorophore development and optimal image buffer assessment through facile and accurate photoswitching property characterization, which translates to SMLM fluorophore imaging performance.
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spelling pubmed-49441972016-07-26 Methodology for Quantitative Characterization of Fluorophore Photoswitching to Predict Superresolution Microscopy Image Quality Bittel, Amy M. Nickerson, Andrew Saldivar, Isaac S. Dolman, Nick J. Nan, Xiaolin Gibbs, Summer L. Sci Rep Article Single-molecule localization microscopy (SMLM) image quality and resolution strongly depend on the photoswitching properties of fluorophores used for sample labeling. Development of fluorophores with optimized photoswitching will considerably improve SMLM spatial and spectral resolution. Currently, evaluating fluorophore photoswitching requires protein-conjugation before assessment mandating specific fluorophore functionality, which is a major hurdle for systematic characterization. Herein, we validated polyvinyl alcohol (PVA) as a single-molecule environment to efficiently quantify the photoswitching properties of fluorophores and identified photoswitching properties predictive of quality SMLM images. We demonstrated that the same fluorophore photoswitching properties measured in PVA films and using antibody adsorption, a protein-conjugation environment analogous to labeled cells, were significantly correlated to microtubule width and continuity, surrogate measures of SMLM image quality. Defining PVA as a fluorophore photoswitching screening platform will facilitate SMLM fluorophore development and optimal image buffer assessment through facile and accurate photoswitching property characterization, which translates to SMLM fluorophore imaging performance. Nature Publishing Group 2016-07-14 /pmc/articles/PMC4944197/ /pubmed/27412307 http://dx.doi.org/10.1038/srep29687 Text en Copyright © 2016, Macmillan Publishers Limited http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/
spellingShingle Article
Bittel, Amy M.
Nickerson, Andrew
Saldivar, Isaac S.
Dolman, Nick J.
Nan, Xiaolin
Gibbs, Summer L.
Methodology for Quantitative Characterization of Fluorophore Photoswitching to Predict Superresolution Microscopy Image Quality
title Methodology for Quantitative Characterization of Fluorophore Photoswitching to Predict Superresolution Microscopy Image Quality
title_full Methodology for Quantitative Characterization of Fluorophore Photoswitching to Predict Superresolution Microscopy Image Quality
title_fullStr Methodology for Quantitative Characterization of Fluorophore Photoswitching to Predict Superresolution Microscopy Image Quality
title_full_unstemmed Methodology for Quantitative Characterization of Fluorophore Photoswitching to Predict Superresolution Microscopy Image Quality
title_short Methodology for Quantitative Characterization of Fluorophore Photoswitching to Predict Superresolution Microscopy Image Quality
title_sort methodology for quantitative characterization of fluorophore photoswitching to predict superresolution microscopy image quality
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4944197/
https://www.ncbi.nlm.nih.gov/pubmed/27412307
http://dx.doi.org/10.1038/srep29687
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