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Quantitative structured illumination microscopy via a physical model-based background filtering algorithm reveals actin dynamics

Despite the prevalence of superresolution (SR) microscopy, quantitative live-cell SR imaging that maintains the completeness of delicate structures and the linearity of fluorescence signals remains an uncharted territory. Structured illumination microscopy (SIM) is the ideal tool for live-cell SR im...

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Autores principales: Mo, Yanquan, Wang, Kunhao, Li, Liuju, Xing, Shijia, Ye, Shouhua, Wen, Jiayuan, Duan, Xinxin, Luo, Ziying, Gou, Wen, Chen, Tongsheng, Zhang, Yu-Hui, Guo, Changliang, Fan, Junchao, Chen, Liangyi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10227022/
https://www.ncbi.nlm.nih.gov/pubmed/37248215
http://dx.doi.org/10.1038/s41467-023-38808-8
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author Mo, Yanquan
Wang, Kunhao
Li, Liuju
Xing, Shijia
Ye, Shouhua
Wen, Jiayuan
Duan, Xinxin
Luo, Ziying
Gou, Wen
Chen, Tongsheng
Zhang, Yu-Hui
Guo, Changliang
Fan, Junchao
Chen, Liangyi
author_facet Mo, Yanquan
Wang, Kunhao
Li, Liuju
Xing, Shijia
Ye, Shouhua
Wen, Jiayuan
Duan, Xinxin
Luo, Ziying
Gou, Wen
Chen, Tongsheng
Zhang, Yu-Hui
Guo, Changliang
Fan, Junchao
Chen, Liangyi
author_sort Mo, Yanquan
collection PubMed
description Despite the prevalence of superresolution (SR) microscopy, quantitative live-cell SR imaging that maintains the completeness of delicate structures and the linearity of fluorescence signals remains an uncharted territory. Structured illumination microscopy (SIM) is the ideal tool for live-cell SR imaging. However, it suffers from an out-of-focus background that leads to reconstruction artifacts. Previous post hoc background suppression methods are prone to human bias, fail at densely labeled structures, and are nonlinear. Here, we propose a physical model-based Background Filtering method for living cell SR imaging combined with the 2D-SIM reconstruction procedure (BF-SIM). BF-SIM helps preserve intricate and weak structures down to sub-70 nm resolution while maintaining signal linearity, which allows for the discovery of dynamic actin structures that, to the best of our knowledge, have not been previously monitored.
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spelling pubmed-102270222023-05-31 Quantitative structured illumination microscopy via a physical model-based background filtering algorithm reveals actin dynamics Mo, Yanquan Wang, Kunhao Li, Liuju Xing, Shijia Ye, Shouhua Wen, Jiayuan Duan, Xinxin Luo, Ziying Gou, Wen Chen, Tongsheng Zhang, Yu-Hui Guo, Changliang Fan, Junchao Chen, Liangyi Nat Commun Article Despite the prevalence of superresolution (SR) microscopy, quantitative live-cell SR imaging that maintains the completeness of delicate structures and the linearity of fluorescence signals remains an uncharted territory. Structured illumination microscopy (SIM) is the ideal tool for live-cell SR imaging. However, it suffers from an out-of-focus background that leads to reconstruction artifacts. Previous post hoc background suppression methods are prone to human bias, fail at densely labeled structures, and are nonlinear. Here, we propose a physical model-based Background Filtering method for living cell SR imaging combined with the 2D-SIM reconstruction procedure (BF-SIM). BF-SIM helps preserve intricate and weak structures down to sub-70 nm resolution while maintaining signal linearity, which allows for the discovery of dynamic actin structures that, to the best of our knowledge, have not been previously monitored. Nature Publishing Group UK 2023-05-29 /pmc/articles/PMC10227022/ /pubmed/37248215 http://dx.doi.org/10.1038/s41467-023-38808-8 Text en © The Author(s) 2023 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Mo, Yanquan
Wang, Kunhao
Li, Liuju
Xing, Shijia
Ye, Shouhua
Wen, Jiayuan
Duan, Xinxin
Luo, Ziying
Gou, Wen
Chen, Tongsheng
Zhang, Yu-Hui
Guo, Changliang
Fan, Junchao
Chen, Liangyi
Quantitative structured illumination microscopy via a physical model-based background filtering algorithm reveals actin dynamics
title Quantitative structured illumination microscopy via a physical model-based background filtering algorithm reveals actin dynamics
title_full Quantitative structured illumination microscopy via a physical model-based background filtering algorithm reveals actin dynamics
title_fullStr Quantitative structured illumination microscopy via a physical model-based background filtering algorithm reveals actin dynamics
title_full_unstemmed Quantitative structured illumination microscopy via a physical model-based background filtering algorithm reveals actin dynamics
title_short Quantitative structured illumination microscopy via a physical model-based background filtering algorithm reveals actin dynamics
title_sort quantitative structured illumination microscopy via a physical model-based background filtering algorithm reveals actin dynamics
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10227022/
https://www.ncbi.nlm.nih.gov/pubmed/37248215
http://dx.doi.org/10.1038/s41467-023-38808-8
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