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Unterauer, E.M.* ; Schentarra, E.M.* ; Jevdokimenko, K.* ; Shetab Boushehri, S. ; Marr, C. ; Opazo, F.* ; Fornasiero, E.F.* ; Jungmann, R.*

Protocol for SUM-PAINT spatial proteomic imaging generating neuronal architecture maps in rat hippocampal neurons.

STAR Protoc. 6:103637 (2025)
Verlagsversion Forschungsdaten DOI PMC
Open Access Gold
Creative Commons Lizenzvertrag
To unravel the complexity of biological processes, it is necessary to resolve the underlying protein organization down to single proteins. Here, we present a protocol for secondary label-based unlimited multiplexed DNA-PAINT (SUM-PAINT), a DNA-PAINT-based super-resolution microscopy technique that is capable of resolving virtually unlimited protein species with single-protein resolution. We describe the steps to prepare neuronal cultures, troubleshoot and conduct SUM-PAINT experiments, and analyze the resulting feature-rich neuronal cell atlases using unsupervised machine learning approaches. For complete details on the use and execution of this protocol, please refer to Unterauer et al.1.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Korrespondenzautor
Schlagwörter Cell Biology ; Cell Culture ; Microscopy ; Neuroscience; Microscopy
e-ISSN 2666-1667
Zeitschrift STAR Protocols
Quellenangaben Band: 6, Heft: 1, Seiten: , Artikelnummer: 103637 Supplement: ,
Verlag Elsevier
Verlagsort Radarweg 29, 1043 Nx Amsterdam, Netherlands
Nichtpatentliteratur Publikationen
Begutachtungsstatus Peer reviewed
Institut(e) Institute of AI for Health (AIH)
Förderungen BMBF
Max Planck Foundation
Max Planck Society
IMPRS-ML graduate school
Deutsche Forschungsgemeinschaft (DFG)
CZI collaborative pair grant
Collaborative Research Center 1286 on Quantitative Synaptologie , Gottingen, Germany
F. Hoffmann-La Roche LTD
European Research Council (ERC) under the European Union's Horizon 2020 research and innovation program
Helmholtz Association under the joint research school "Munich School for Data Science-MUDS"

European Research Council through an ERC Consolidator Grant (ReceptorPAINT)