Fast DNA-PAINT imaging using a deep neural network.


Journal

Nature communications
ISSN: 2041-1723
Titre abrégé: Nat Commun
Pays: England
ID NLM: 101528555

Informations de publication

Date de publication:
27 08 2022
Historique:
received: 08 12 2021
accepted: 09 08 2022
entrez: 27 8 2022
pubmed: 28 8 2022
medline: 31 8 2022
Statut: epublish

Résumé

DNA points accumulation for imaging in nanoscale topography (DNA-PAINT) is a super-resolution technique with relatively easy-to-implement multi-target imaging. However, image acquisition is slow as sufficient statistical data has to be generated from spatio-temporally isolated single emitters. Here, we train the neural network (NN) DeepSTORM to predict fluorophore positions from high emitter density DNA-PAINT data. This achieves image acquisition in one minute. We demonstrate multi-colour super-resolution imaging of structure-conserved semi-thin neuronal tissue and imaging of large samples. This improvement can be integrated into any single-molecule imaging modality to enable fast single-molecule super-resolution microscopy.

Identifiants

pubmed: 36030338
doi: 10.1038/s41467-022-32626-0
pii: 10.1038/s41467-022-32626-0
pmc: PMC9420107
doi:

Substances chimiques

Fluorescent Dyes 0
DNA 9007-49-2

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

5047

Informations de copyright

© 2022. The Author(s).

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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.

Johanna V Rahm (JV)

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

Siddharth Tourani (S)

Computer Vision and Learning Lab, Heidelberg University, Heidelberg, Germany.

Mike Heilemann (M)

Department of Functional Neuroanatomy, Institute for Anatomy and Cell Biology, Heidelberg University, Heidelberg, Germany. heileman@chemie.uni-frankfurt.de.
Institute of Physical and Theoretical Chemistry, Goethe University Frankfurt, Frankfurt, Germany. heileman@chemie.uni-frankfurt.de.

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Classifications MeSH