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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...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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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. |
format | Online Article Text |
id | pubmed-10227022 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
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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