Parameter-free molecular super-structures quantification in single-molecule localization microscopy

Understanding biological function requires the identification and characterization of complex patterns of molecules. Single-molecule localization microscopy (SMLM) can quantitatively measure molecular components and interactions at resolutions far beyond the diffraction limit, but this information i...

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Bibliographic Details
Published in:The Journal of cell biology 2021-05, Vol.220 (5), p.1
Main Authors: Marenda, Mattia, Lazarova, Elena, van de Linde, Sebastian, Gilbert, Nick, Michieletto, Davide
Format: Article
Language:English
Subjects:
Algorithms
Biophysics
Clusters
Diffraction patterns
DNA biology
Genomes
Information processing
Localization
Microscopy
Parameters
Proteins
RNA biology
Superstructures
Systems and Computational Biology
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Summary:Understanding biological function requires the identification and characterization of complex patterns of molecules. Single-molecule localization microscopy (SMLM) can quantitatively measure molecular components and interactions at resolutions far beyond the diffraction limit, but this information is only useful if these patterns can be quantified and interpreted. We provide a new approach for the analysis of SMLM data that develops the concept of structures and super-structures formed by interconnected elements, such as smaller protein clusters. Using a formal framework and a parameter-free algorithm, (super-)structures formed from smaller components are found to be abundant in classes of nuclear proteins, such as heterogeneous nuclear ribonucleoprotein particles (hnRNPs), but are absent from ceramides located in the plasma membrane. We suggest that mesoscopic structures formed by interconnected protein clusters are common within the nucleus and have an important role in the organization and function of the genome. Our algorithm, SuperStructure, can be used to analyze and explore complex SMLM data and extract functionally relevant information.
ISSN:0021-9525
1540-8140
DOI:10.1083/jcb.202010003