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Automated highly multiplexed super-resolution imaging of protein nano-architecture in cells and tissues
Understanding the nano-architecture of protein machines in diverse subcellular compartments remains a challenge despite rapid progress in super-resolution microscopy. While single-molecule localization microscopy techniques allow the visualization and identification of cellular structures with near-...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7096454/ https://www.ncbi.nlm.nih.gov/pubmed/32214101 http://dx.doi.org/10.1038/s41467-020-15362-1 |
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author | Klevanski, Maja Herrmannsdoerfer, Frank Sass, Steffen Venkataramani, Varun Heilemann, Mike Kuner, Thomas |
author_facet | Klevanski, Maja Herrmannsdoerfer, Frank Sass, Steffen Venkataramani, Varun Heilemann, Mike Kuner, Thomas |
author_sort | Klevanski, Maja |
collection | PubMed |
description | Understanding the nano-architecture of protein machines in diverse subcellular compartments remains a challenge despite rapid progress in super-resolution microscopy. While single-molecule localization microscopy techniques allow the visualization and identification of cellular structures with near-molecular resolution, multiplex-labeling of tens of target proteins within the same sample has not yet been achieved routinely. However, single sample multiplexing is essential to detect patterns that threaten to get lost in multi-sample averaging. Here, we report maS(3)TORM (multiplexed automated serial staining stochastic optical reconstruction microscopy), a microscopy approach capable of fully automated 3D direct STORM (dSTORM) imaging and solution exchange employing a re-staining protocol to achieve highly multiplexed protein localization within individual biological samples. We demonstrate 3D super-resolution images of 15 targets in single cultured cells and 16 targets in individual neuronal tissue samples with <10 nm localization precision, allowing us to define distinct nano-architectural features of protein distribution within the presynaptic nerve terminal. |
format | Online Article Text |
id | pubmed-7096454 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-70964542020-03-27 Automated highly multiplexed super-resolution imaging of protein nano-architecture in cells and tissues Klevanski, Maja Herrmannsdoerfer, Frank Sass, Steffen Venkataramani, Varun Heilemann, Mike Kuner, Thomas Nat Commun Article Understanding the nano-architecture of protein machines in diverse subcellular compartments remains a challenge despite rapid progress in super-resolution microscopy. While single-molecule localization microscopy techniques allow the visualization and identification of cellular structures with near-molecular resolution, multiplex-labeling of tens of target proteins within the same sample has not yet been achieved routinely. However, single sample multiplexing is essential to detect patterns that threaten to get lost in multi-sample averaging. Here, we report maS(3)TORM (multiplexed automated serial staining stochastic optical reconstruction microscopy), a microscopy approach capable of fully automated 3D direct STORM (dSTORM) imaging and solution exchange employing a re-staining protocol to achieve highly multiplexed protein localization within individual biological samples. We demonstrate 3D super-resolution images of 15 targets in single cultured cells and 16 targets in individual neuronal tissue samples with <10 nm localization precision, allowing us to define distinct nano-architectural features of protein distribution within the presynaptic nerve terminal. Nature Publishing Group UK 2020-03-25 /pmc/articles/PMC7096454/ /pubmed/32214101 http://dx.doi.org/10.1038/s41467-020-15362-1 Text en © The Author(s) 2020 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/. |
spellingShingle | Article Klevanski, Maja Herrmannsdoerfer, Frank Sass, Steffen Venkataramani, Varun Heilemann, Mike Kuner, Thomas Automated highly multiplexed super-resolution imaging of protein nano-architecture in cells and tissues |
title | Automated highly multiplexed super-resolution imaging of protein nano-architecture in cells and tissues |
title_full | Automated highly multiplexed super-resolution imaging of protein nano-architecture in cells and tissues |
title_fullStr | Automated highly multiplexed super-resolution imaging of protein nano-architecture in cells and tissues |
title_full_unstemmed | Automated highly multiplexed super-resolution imaging of protein nano-architecture in cells and tissues |
title_short | Automated highly multiplexed super-resolution imaging of protein nano-architecture in cells and tissues |
title_sort | automated highly multiplexed super-resolution imaging of protein nano-architecture in cells and tissues |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7096454/ https://www.ncbi.nlm.nih.gov/pubmed/32214101 http://dx.doi.org/10.1038/s41467-020-15362-1 |
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