RT @MPI_Biochem: Congratulations to Ralf on your election as a new EMBO member:. ❕Original press release from @EMBO: .

@MoniqueHonsa, @PhilippSteen, Larissa Heinze, Shuhan Xu, @heerpa, @IBaudrexel, @SusanneReinhar3, Ana Perovic, Jisoo Kwon, Ethan Oxley, Ross Dickins, @IkbenMaartje, @IanParish_AU.

Big congrats to @l_masu and @rafalkowalew who led the project as well as other co-authors that contributed to this work!!.

To facilitate SPINNA’s widespread use in the scientific community, we offer an open-source Python implementation and a GUI available in the latest version of Picasso (. 7/7

Finally, we investigate the dimerization of CD80 and PD-L1, key surface ligands involved in immune cell signaling. 6/7

We further quantitatively evaluate the oligomerization of the Epidermal Growth Factor Receptor (EGFR) upon binding of its ligand, EGF. 5/7

We demonstrate SPINNA in DNA-origami, showing that it can infer not only the stoichiometry of the oligomers but also different spatial conformations. 4/7

Here, we present SPINNA (Single-Protein Investigation via Nearest Neighbor Analysis): an analysis framework that compares nearest neighbor distances from experimental single-protein data with those from realistic simulations based on a model of protein oligomerization states. 3/7

Latest advances in super-resolution microscopy (DNA-PAINT, MINFLUX, RESI) allow the study of molecular arrangements at the level of single proteins, but extracting quantitative information on the 1–20 nm scale through rigorous image analysis remains a significant challenge. 2/7

Understanding how proteins assemble into complexes (oligomerize) within their native cellular environments is crucial for deciphering cellular signaling pathways 1/7.

Spatial and stoichiometric in situ analysis of biomolecular oligomerization at single-protein resolution. We are excited to present our latest work published in @NatureComms .

A huge thank you to all authors and collaborators whose dedication and teamwork made this protocol possible! @EduardUnterauer @EvaSchentarra @jekriste @MarrCarsten @FelipeOpaz_o @euforna.Let us know if you’re ready to generate your own single-cell spatial proteomics atlases! 🚀.

You encountered issues along the way? We’ve got you covered with a comprehensive troubleshooting section, addressing common problems in sample preparation, imaging, and analysis. 6/7

We also share a detailed breakdown of our analysis workflow — from raw data processing to feature extraction and unsupervised data exploration to best possible mine your high dimensional data set. 5/7

Learn how to set up your custom SUM-PAINT experiment to achieve 3D sub 15-nm resolution imaging of up to 30 different proteins. 4/7

Starting out on how to do primary neuron cell preparation, we describe how to optimally preserve the neural morphology for super-resolution imaging with DNA-PAINT. 3/7

This step-by-step guide walks you through generating high-dimensional neuronal architecture maps in rat hippocampal neurons — achieving up to 30-color DNA-PAINT spatial proteomics at sub-15 nm resolution. 2/7

Are you struggling to achieve high multiplexing at single-protein resolution and the methods section of publications leaves you puzzled? Look no further! We present our SUM-PAINT spatial proteomic imaging protocol, now published in STAR Protocols.

Also big thanks to all co-authors @IBaudrexel @MoniqueHonsa Larissa Heinze Sarah Fritsche @heerpa!.

This has been an amazing collaboration between @LMoeckl Lab and @JungmannLab led by first authors @KarimAlmahayni (left) and @l_masu (right), big congrats!!!