Identifying intermolecular interactions in single-molecule localization microscopy.

Authors

Xingchi Yan, Polly Y Yu, Arvind Srinivasan, Sohaib Abdul Rehman, Surabhi Kottigegollahalli Sreenivas, Jeremy B Conway, Maxim B Prigozhin

Published in

Proceedings of the National Academy of Sciences of the United States of America. Volume 122. Issue 20. Pages e2409426122. May 20, 2025. Epub May 12, 2025.

Abstract

Intermolecular interactions underlie all cellular functions, yet visualizing these interactions at the single-molecule level remains challenging. Single-molecule localization microscopy (SMLM) offers a potential solution. Given a nanoscale map of two putative interaction partners, it should be possible to assign molecules either to the class of coupled pairs or to the class of noncoupled bystanders. Here, we developed a probabilistic algorithm that allows accurate determination of both the absolute number and the proportion of molecules that form coupled pairs. The algorithm calculates interaction probabilities for all possible pairs of localized molecules, selects the most likely interaction set, and corrects for any spurious colocalizations. Benchmarking this approach across a set of simulated molecular localization maps with varying densities (up to ∼55 molecules μm^-2) and localization precisions (1 to 50 nm) showed typical errors in the identification of correct pairs of only a few percent. At molecular densities of ∼5 to 10 molecules μm^-2 and localization precisions of 20 to 30 nm, which are typical parameters for SMLM imaging, the recall was ∼90%. The algorithm was effective at differentiating between noninteracting and coupled molecules both in simulations and experiments. Finally, it correctly inferred the number of coupled pairs over time in a simulated reaction-diffusion system, enabling determination of the underlying rate constants. The proposed approach promises to enable direct visualization and quantification of intermolecular interactions using SMLM.

PMID:
40354526
Bibliographic data and abstract were imported from PubMed on 13 May 2025.

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