空間プロテオミクスで新しいタイプのシナプスを発見(New synapse type discovered by spatial proteomics)

2024-03-29

2024-03-28 ミュンヘン大学(LMU)

ラルフ・ユングマン率いる研究者チームが、新しい超解像度高スループット画像化手法を開発しました。この手法を使用して、単一分子分解能で3Dの神経細胞アトラスを作成し、以前知られていなかったシナプスの新しいタイプを発見しました。この手法は、SUM-PAINTと呼ばれ、超解像度顕微鏡で非常に速く大量のタンパク質を視覚化およびマッピングすることが可能です。

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単一タンパク質の分解能でニューロンの空間プロテオミクスを行う Spatial proteomics in neurons at single-protein resolution

Eduard M. Unterauer,Sayedali Shetab Boushehri,Kristina Jevdokimenko,…,Felipe Opazo,Eugenio F. Fornasiero,Ralf Jungmann
Cell Published:March 28, 2024
DOI:https://doi.org/10.1016/j.cell.2024.02.045

Highlights

•Development of SUM-PAINT enables high-throughput DNA-PAINT multiplexing

•30-plex, 3D neuron atlas at single-protein resolution

•AI-guided analysis enables evaluation of high-dimensional SUM-PAINT datasets

•Discovery of a new synapse subtype characterized by VGlut1⁺ and Gephyrin⁺

Summary

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.