Detecting continuous structural heterogeneity in single-molecule localization microscopy data

Journal Article (2023)
Author(s)

Sobhan Haghparast (TU Delft - ImPhys/Rieger group)

Sjoerd Stallinga (TU Delft - ImPhys/Imaging Physics)

Bernd Rieger (TU Delft - ImPhys/Computational Imaging, TU Delft - ImPhys/Rieger group)

Research Group
ImPhys/Rieger group
DOI related publication
https://doi.org/10.1038/s41598-023-46488-z Final published version
More Info
expand_more
Publication Year
2023
Language
English
Research Group
ImPhys/Rieger group
Journal title
Scientific Reports
Issue number
1
Volume number
13
Article number
19800
Downloads counter
193
Collections
Institutional Repository
Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Abstract

Fusion of multiple chemically identical complexes, so-called particles, in localization microscopy, can improve the signal-to-noise ratio and overcome under-labeling. To this end, structural homogeneity of the data must be assumed. Biological heterogeneity, however, could be present in the data originating from distinct conformational variations or (continuous) variations in particle shapes. We present a prior-knowledge-free method for detecting continuous structural variations with localization microscopy. Detecting this heterogeneity leads to more faithful fusions and reconstructions of the localization microscopy data as their heterogeneity is taken into account. In experimental datasets, we show the continuous variation of the height of DNA origami tetrahedrons imaged with 3D PAINT and of the radius of Nuclear Pore Complexes imaged in 2D with STORM. In simulation, we study the impact on the heterogeneity detection pipeline of Degree Of Labeling and of structural variations in the form of two independent modes.