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Related Experiment Video

Updated: Jun 29, 2025

Characterization of Neuronal Lysosome Interactome with Proximity Labeling Proteomics

Characterization of Neuronal Lysosome Interactome with Proximity Labeling Proteomics

Published on: June 23, 2022

Spatial proteomics in neurons at single-protein resolution.

Eduard M Unterauer¹, Sayedali Shetab Boushehri², Kristina Jevdokimenko³

¹Max Planck Institute of Biochemistry, Planegg, Germany; Faculty of Physics and Center for NanoScience, Ludwig-Maximilians-Universität, Munich, Germany.

|March 29, 2024

Summary

We developed SUM-PAINT, a novel imaging technique enabling virtually unlimited multiplexing for spatial proteomics. This method achieves high resolution, revealing cellular complexity and discovering a new synapse type in neurons.

Keywords:

DNA-PAINT excitatory synapses inhibitory synapses multiplexing neuron atlas neuron imaging proteomics spatial-omics super-resolution microscopy synapse synapse diversity synaptic proteins

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Last Updated: Jun 29, 2025

Characterization of Neuronal Lysosome Interactome with Proximity Labeling Proteomics

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Published on: June 23, 2022

In Vivo Single-Molecule Tracking at the Drosophila Presynaptic Motor Nerve Terminal

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Published on: January 14, 2018

Super-Resolution Imaging to Study Co-Localization of Proteins and Synaptic Markers in Primary Neurons

Super-Resolution Imaging to Study Co-Localization of Proteins and Synaptic Markers in Primary Neurons

Published on: October 31, 2020

Area of Science:

Molecular biology
Cellular imaging
Proteomics

Background:

Understanding cellular heterogeneity requires mapping biomolecule location and interactions.
Super-resolution microscopy has advanced imaging but lacks the multiplexing capacity of proteomics.
High-throughput spatial proteomics is crucial for detailed biological process analysis.

Purpose of the Study:

Introduce a novel high-throughput imaging method for virtually unlimited multiplexing.
Achieve high-resolution (better than 15 nm) spatial proteomics.
Enable comprehensive analysis of molecular heterogeneity in cells.

Main Methods:

Developed secondary label-based unlimited multiplexed DNA-PAINT (SUM-PAINT).
Generated 30-plex single-molecule resolved datasets in neurons.
Adapted omics-inspired analysis for data exploration.

Main Results:

SUM-PAINT achieves virtually unlimited multiplexing at better than 15 nm resolution.
30-plex datasets revealed synaptic heterogeneity complexity in neurons.
Discovered a distinct synapse type through spatial proteomics analysis.

Conclusions:

SUM-PAINT offers a powerful tool for high-throughput spatial proteomics.
The integrated workflow facilitates comprehensive analysis of spatial proteomes.
Enables discovery of novel cellular structures and heterogeneity.