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Registration and Visualization of Correlative Super-Resolution Microscopy Data.

Sebastian Reinhard1, Sarah Aufmkolk2, Markus Sauer1

  • 1Department of Biotechnology and Biophysics, University of Würzburg, Biocenter, Am Hubland, Würzburg, Germany.

Biophysical Journal
|May 20, 2019
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Summary

We developed an automated method and software for correlating super-resolution microscopy images from different techniques, enabling precise visualization of synaptic proteins like bassoon.

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Area of Science:

  • Microscopy
  • Neuroscience
  • Biophysics

Background:

  • Correlating super-resolution microscopy images from different techniques is challenging.
  • Accurate registration is crucial for understanding nanoscale biological structures.

Purpose of the Study:

  • To introduce an automated method for registration and visualization of correlative super-resolution microscopy images.
  • To develop a software tool for applying this algorithm to images from structured illumination microscopy (SIM) and direct stochastic optical reconstruction microscopy (dSTORM).

Main Methods:

  • An automated registration procedure based on the generalized Hough transform was established.
  • A software tool was developed to implement the algorithm.
  • Super-resolution correlator was demonstrated using presynaptic protein bassoon in mouse cerebellum synapses, correlating SIM and dSTORM images without artificial fiducial markers.

Main Results:

  • Successful registration and visualization of correlative super-resolution microscopy images were achieved.
  • The distribution of the presynaptic protein bassoon in active zones of synapses was visualized.
  • Multicolor SIM images were recorded and registered with higher-resolution dSTORM images.

Conclusions:

  • The developed method and software enable accurate registration and visualization of correlative super-resolution microscopy data.
  • This approach facilitates the study of nanoscale protein distributions in biological systems.
  • The super-resolution correlator has potential for advancing neuroscience and cell biology research.