Literature DB >> 32551615

Detecting Nanoscale Distribution of Protein Pairs by Proximity-Dependent Super-resolution Microscopy.

Alexander H Clowsley1, William T Kaufhold2,3, Tobias Lutz1, Anna Meletiou1, Lorenzo Di Michele2,3, Christian Soeller1.   

Abstract

Interactions between biomolecules such as proteins underlie most cellular processes. It is crucial to visualize these molecular-interaction complexes directly within the cell, to show precisely where these interactions occur and thus improve our understanding of cellular regulation. Currently available proximity-sensitive assays for in situ imaging of such interactions produce diffraction-limited signals and therefore preclude information on the nanometer-scale distribution of interaction complexes. By contrast, optical super-resolution imaging provides information about molecular distributions with nanometer resolution, which has greatly advanced our understanding of cell biology. However, current co-localization analysis of super-resolution fluorescence imaging is prone to false positive signals as the detection of protein proximity is directly dependent on the local optical resolution. Here we present proximity-dependent PAINT (PD-PAINT), a method for subdiffraction imaging of protein pairs, in which proximity detection is decoupled from optical resolution. Proximity is detected via the highly distance-dependent interaction of two DNA constructs anchored to the target species. Labeled protein pairs are then imaged with high-contrast and nanoscale resolution using the super-resolution approach of DNA-PAINT. The mechanisms underlying the new technique are analyzed by means of coarse-grained molecular simulations and experimentally demonstrated by imaging DNA-origami tiles and epitopes of cardiac proteins in isolated cardiomyocytes. We show that PD-PAINT can be straightforwardly integrated in a multiplexed super-resolution imaging protocol and benefits from advantages of DNA-based super-resolution localization microscopy, such as high specificity, high resolution, and the ability to image quantitatively.

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Year:  2020        PMID: 32551615     DOI: 10.1021/jacs.9b03418

Source DB:  PubMed          Journal:  J Am Chem Soc        ISSN: 0002-7863            Impact factor:   15.419


  6 in total

1.  Probing the Mechanical Properties of DNA Nanostructures with Metadynamics.

Authors:  Will T Kaufhold; Wolfgang Pfeifer; Carlos E Castro; Lorenzo Di Michele
Journal:  ACS Nano       Date:  2022-05-17       Impact factor: 18.027

2.  DNA-PAINT Imaging Accelerated by Machine Learning.

Authors:  Min Zhu; Luhao Zhang; Luhong Jin; Jincheng Chen; Yongdeng Zhang; Yingke Xu
Journal:  Front Chem       Date:  2022-05-10       Impact factor: 5.545

Review 3.  Completing the canvas: advances and challenges for DNA-PAINT super-resolution imaging.

Authors:  Raman van Wee; Mike Filius; Chirlmin Joo
Journal:  Trends Biochem Sci       Date:  2021-07-08       Impact factor: 13.807

4.  Cellular macromolecules-tethered DNA walking indexing to explore nanoenvironments of chromatin modifications.

Authors:  Feng Chen; Min Bai; Xiaowen Cao; Jing Xue; Yue Zhao; Na Wu; Lei Wang; Dexin Zhang; Yongxi Zhao
Journal:  Nat Commun       Date:  2021-03-30       Impact factor: 14.919

Review 5.  Amphiphilic DNA nanostructures for bottom-up synthetic biology.

Authors:  Roger Rubio-Sánchez; Giacomo Fabrini; Pietro Cicuta; Lorenzo Di Michele
Journal:  Chem Commun (Camb)       Date:  2021-11-30       Impact factor: 6.222

Review 6.  Microscopic Visualization of Cell-Cell Adhesion Complexes at Micro and Nanoscale.

Authors:  Bieke Vanslembrouck; Jian-Hua Chen; Carolyn Larabell; Jolanda van Hengel
Journal:  Front Cell Dev Biol       Date:  2022-04-20
  6 in total

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