Spatial proteomics in neurons at single-protein resolution

Unterauer, EM and Shetab Boushehri, S and Jevdokimenko, K and Masullo, LA and Ganji, M and Sograte-Idrissi, S and Kowalewski, R and Strauss, S and Reinhardt, SCM and Perovic, A and Marr, C and Opazo, F and Fornasiero, EF and Jungmann, R (2024) Spatial proteomics in neurons at single-protein resolution. In: Cell, 187 (7). 1785-1800.e16.

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Abstract

To understand biological processes, it is necessary to reveal the molecular heterogeneity of cells by gaining access to the location and interaction of all biomolecules. Significant advances were achieved by super-resolution microscopy, but such methods are still far from reaching the multiplexing capacity of proteomics. Here, we introduce secondary label-based unlimited multiplexed DNA-PAINT (SUM-PAINT), a high-throughput imaging method that is capable of achieving virtually unlimited multiplexing at better than 15 nm resolution. Using SUM-PAINT, we generated 30-plex single-molecule resolved datasets in neurons and adapted omics-inspired analysis for data exploration. This allowed us to reveal the complexity of synaptic heterogeneity, leading to the discovery of a distinct synapse type. We not only provide a resource for researchers, but also an integrated acquisition and analysis workflow for comprehensive spatial proteomics at single-protein resolution. © 2024 The Author(s)

Item Type:	Journal Article
Publication:	Cell
Publisher:	Elsevier B.V.
Additional Information:	The copyright for this article belongs to authors.
Keywords:	gephyrin; vesicular glutamate transporter 1; vesicular inhibitory amino acid transporter; DNA; protein, adult; animal cell; animal experiment; animal tissue; Article; artificial intelligence; controlled study; DNA barcoding; DNA hybridization; DNA sequence; embryo; feature extraction; female; high throughput imaging; infant; male; molecular docking; nanoanalysis; nonhuman; postsynaptic inhibition; presynaptic nerve; process optimization; protein content; protein expression level; protein structure; proteomics; rat; spatial analysis; synapse; unsupervised machine learning; fluorescence microscopy; nerve cell; procedures, DNA; Microscopy, Fluorescence; Neurons; Proteins; Proteomics
Department/Centre:	Division of Biological Sciences > Biochemistry
Date Deposited:	28 Aug 2024 10:20
Last Modified:	28 Aug 2024 10:20
URI:	http://eprints.iisc.ac.in/id/eprint/84810

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