Spatial and stoichiometric in situ analysis of biomolecular oligomerization at single-protein resolution

Luciano A. Masullo (), Rafal Kowalewski, Monique Honsa, Larissa Heinze, Shuhan Xu, Philipp R. Steen, Heinrich Grabmayr, Isabelle Pachmayr, Susanne C. M. Reinhardt, Ana Perovic, Jisoo Kwon, Ethan P. Oxley, Ross A. Dickins, Maartje M. C. Bastings, Ian A. Parish and Ralf Jungmann ()
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Luciano A. Masullo: Max Planck Institute of Biochemistry
Rafal Kowalewski: Max Planck Institute of Biochemistry
Monique Honsa: Max Planck Institute of Biochemistry
Larissa Heinze: Max Planck Institute of Biochemistry
Shuhan Xu: Max Planck Institute of Biochemistry
Philipp R. Steen: Max Planck Institute of Biochemistry
Heinrich Grabmayr: Max Planck Institute of Biochemistry
Isabelle Pachmayr: Max Planck Institute of Biochemistry
Susanne C. M. Reinhardt: Max Planck Institute of Biochemistry
Ana Perovic: Max Planck Institute of Biochemistry
Jisoo Kwon: Max Planck Institute of Biochemistry
Ethan P. Oxley: Monash University
Ross A. Dickins: Monash University
Maartje M. C. Bastings: École Polytechnique Fédérale de Lausanne
Ian A. Parish: Peter MacCallum Cancer Centre
Ralf Jungmann: Max Planck Institute of Biochemistry

Nature Communications, 2025, vol. 16, issue 1, 1-11

Abstract: Abstract Latest advances in super-resolution microscopy allow the study of subcellular features at the level of single proteins, which could lead to discoveries in fundamental biological processes, specifically in cell signaling mediated by membrane receptors. Despite these advances, accurately extracting quantitative information on molecular arrangements of proteins at the 1–20 nm scale through rigorous image analysis remains a significant challenge. Here, we present SPINNA (Single-Protein Investigation via Nearest-Neighbor Analysis): an analysis framework that compares nearest-neighbor distances from experimental single-protein position data with those obtained from realistic simulations based on a user-defined model of protein oligomerization states. We demonstrate SPINNA in silico, in vitro, and in cells. In particular, we quantitatively assess the oligomerization of the epidermal growth factor receptor (EGFR) upon EGF treatment and investigate the dimerization of CD80 and PD-L1, key surface ligands involved in immune cell signaling. Importantly, we offer an open-source Python implementation and a GUI to facilitate SPINNA’s widespread use in the scientific community.

Date: 2025
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DOI: 10.1038/s41467-025-59500-z

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