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Three-Dimensional Surface Rendering of ESCRT Proteins Microscopy Data Using UCSF Chimera Software.

Romain Le Bars1, Michele W Bianchi2,3, Christophe Lefebvre2

  • 1Institute for Integrative Biology of the Cell (I2BC), CEA, CNRS, Université Paris-Sud, Université Paris-Saclay, Gif-sur-Yvette, France. romain.lebars@i2bc.paris-saclay.fr.

Methods in Molecular Biology (Clifton, N.J.)
|June 29, 2019
PubMed
Summary
This summary is machine-generated.

This study presents a protocol for 3D surface rendering of microscopy data using UCSF-Chimera software. This method aids in visualizing Endosomal Sorting Complexes Required for Transport (ESCRT) protein localization and interactions within cells.

Keywords:
3D animation3D fluorescence confocal microscopyESCRTSurface renderingUCSF Chimera

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Area of Science:

  • Cell Biology
  • Microscopy
  • Structural Biology

Background:

  • Understanding Endosomal Sorting Complexes Required for Transport (ESCRT) protein function requires visualizing their subcellular localization and interactions.
  • High-throughput 3D fluorescence microscopy generates large datasets that can be challenging to analyze and visualize.

Purpose of the Study:

  • To provide a detailed protocol for 3D surface rendering of confocal microscopy data.
  • To facilitate the analysis and presentation of subcellular localization data for ESCRT proteins.

Main Methods:

  • Utilized UCSF-Chimera, a free software, for 3D surface rendering.
  • Applied the protocol to confocal microscopy acquisitions.
  • Generated 3D snapshots and animations for data visualization.

Main Results:

  • Successfully generated 3D surface renderings of cellular compartments.
  • Created visualizations that clearly depict ESCRT protein localization.
  • Produced animations that illustrate protein dynamics and interactions.

Conclusions:

  • The described protocol effectively aids in the visualization of subcellular localization data.
  • UCSF-Chimera is a valuable tool for analyzing complex 3D microscopy datasets.
  • This approach enhances the understanding of ESCRT protein function through improved data presentation.