Visualizing Synaptic Multi-Protein Patterns of Neuronal Tissue With DNA-Assisted Single-Molecule Localization Microscopy.

DNA-PAINT Exchange PAINT multiplexing neuronal synapse semi-thin brain tissue sections single-molecule localization microscopy super-resolution microscopy tissue imaging

Journal

Frontiers in synaptic neuroscience
ISSN: 1663-3563
Titre abrégé: Front Synaptic Neurosci
Pays: Switzerland
ID NLM: 101548972

Informations de publication

Date de publication:
2021
Historique:
received: 23 02 2021
accepted: 25 05 2021
entrez: 5 7 2021
pubmed: 6 7 2021
medline: 6 7 2021
Statut: epublish

Résumé

The development of super-resolution microscopy (SRM) has widened our understanding of biomolecular structure and function in biological materials. Imaging multiple targets within a single area would elucidate their spatial localization relative to the cell matrix and neighboring biomolecules, revealing multi-protein macromolecular structures and their functional co-dependencies. SRM methods are, however, limited to the number of suitable fluorophores that can be imaged during a single acquisition as well as the loss of antigens during antibody washing and restaining for organic dye multiplexing. We report the visualization of multiple protein targets within the pre- and postsynapse in 350-400 nm thick neuronal tissue sections using DNA-assisted single-molecule localization microscopy (SMLM). In a single labeling step, antibodies conjugated with short DNA oligonucleotides visualized multiple targets by sequential exchange of fluorophore-labeled complementary oligonucleotides present in the imaging buffer. This approach avoids potential effects on structural integrity when using multiple rounds of immunolabeling and eliminates chromatic aberration, because all targets are imaged using a single excitation laser wavelength. This method proved robust for multi-target imaging in semi-thin tissue sections with a lateral resolution better than 25 nm, paving the way toward structural cell biology with single-molecule SRM.

Identifiants

pubmed: 34220481
doi: 10.3389/fnsyn.2021.671288
pmc: PMC8247585
doi:

Types de publication

Journal Article

Langues

eng

Pagination

671288

Informations de copyright

Copyright © 2021 Narayanasamy, Stojic, Li, Sass, Hesse, Deussner-Helfmann, Dietz, Kuner, Klevanski and Heilemann.

Déclaration de conflit d'intérêts

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Auteurs

Kaarjel K Narayanasamy (KK)

Department of Functional Neuroanatomy, Institute for Anatomy and Cell Biology, Heidelberg University, Heidelberg, Germany.
Institute of Physical and Theoretical Chemistry, Goethe-University Frankfurt, Frankfurt, Germany.

Aleksandar Stojic (A)

Department of Functional Neuroanatomy, Institute for Anatomy and Cell Biology, Heidelberg University, Heidelberg, Germany.

Yunqing Li (Y)

Institute of Physical and Theoretical Chemistry, Goethe-University Frankfurt, Frankfurt, Germany.

Steffen Sass (S)

Department of Functional Neuroanatomy, Institute for Anatomy and Cell Biology, Heidelberg University, Heidelberg, Germany.

Marina R Hesse (MR)

Department of Functional Neuroanatomy, Institute for Anatomy and Cell Biology, Heidelberg University, Heidelberg, Germany.

Nina S Deussner-Helfmann (NS)

Institute of Physical and Theoretical Chemistry, Goethe-University Frankfurt, Frankfurt, Germany.

Marina S Dietz (MS)

Institute of Physical and Theoretical Chemistry, Goethe-University Frankfurt, Frankfurt, Germany.

Thomas Kuner (T)

Department of Functional Neuroanatomy, Institute for Anatomy and Cell Biology, Heidelberg University, Heidelberg, Germany.

Maja Klevanski (M)

Department of Functional Neuroanatomy, Institute for Anatomy and Cell Biology, Heidelberg University, Heidelberg, Germany.

Mike Heilemann (M)

Department of Functional Neuroanatomy, Institute for Anatomy and Cell Biology, Heidelberg University, Heidelberg, Germany.
Institute of Physical and Theoretical Chemistry, Goethe-University Frankfurt, Frankfurt, Germany.

Classifications MeSH