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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-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 maS3TORM (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.

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Metadaten
Author:Maja KlevanskiORCiDGND, Frank HerrmannsdörferGND, Varun VenkataramaniORCiDGND, Steffen SaßORCiDGND, Mike HeilemannORCiDGND, Thomas KunerORCiDGND
URN:urn:nbn:de:hebis:30:3-742298
DOI:https://doi.org/10.1038/s41467-020-15362-1
ISSN:2041-1723
Parent Title (German):Nature Communications
Publisher:Nature Publishing Group UK
Place of publication:London
Document Type:Article
Language:English
Date of Publication (online):2020/03/25
Date of first Publication:2020/03/25
Publishing Institution:Universitätsbibliothek Johann Christian Senckenberg
Release Date:2023/06/14
Volume:11
Issue:Article number: 1552
Page Number:11
HeBIS-PPN:510056237
Institutes:Biochemie, Chemie und Pharmazie / Biochemie und Chemie
Dewey Decimal Classification:5 Naturwissenschaften und Mathematik / 57 Biowissenschaften; Biologie / 570 Biowissenschaften; Biologie
Sammlungen:Universitätspublikationen
Licence (German):License LogoCreative Commons - Namensnennung 4.0