2023 article
Investigating Uncertainties in Single-Molecule Localization Microscopy Using Experimentally Informed Monte Carlo Simulation
Yeo, W.-H., Zhang, Y., Neely, A. E., Bao, X., Sun, C., & Zhang, H. F. (2023, July 18). NANO LETTERS.
author keywords: Single-molecule localization microscopy; Monte Carlosimulation; nuclear pore complex; image processing
TL;DR:
A Monte Carlo (MC) simulation based on experimental imaging parameters and geometric information is developed to generate synthetic SMLM images and illustrated using the MC model to generate cellular substructures with different angles of labeling to inform the structural understanding of the images obtained.
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UN Sustainable Development Goal Categories
3. Good Health and Well-being
(Web of Science)
Source: Web Of Science
Added: August 7, 2023
Single-molecule localization microscopy (SMLM) enables the visualization of cellular nanostructures in vitro with sub-20 nm resolution. While substructures can generally be imaged with SMLM, the structural understanding of the images remains elusive. To better understand the link between SMLM images and the underlying structure, we developed a Monte Carlo (MC) simulation based on experimental imaging parameters and geometric information to generate synthetic SMLM images. We chose the nuclear pore complex (NPC), a nanosized channel on the nuclear membrane which gates nucleo-cytoplasmic transport of biomolecules, as a test geometry for testing our MC model. Using the MC model to simulate SMLM images, we first optimized our clustering algorithm to separate >106 molecular localizations of fluorescently labeled NPC proteins into hundreds of individual NPCs in each cell. We then illustrated using our MC model to generate cellular substructures with different angles of labeling to inform our structural understanding through the SMLM images obtained.