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ShapeSpaceExplorer: Analysis of morphological transitions in migrating cells using similarity-based shape space

Samuel D R Jefferyes1,2, Roswitha Gostner1, Laura Cooper1

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Summary

We developed ShapeSpaceExplorer, a software for analyzing 2D shape changes, particularly cell morphology during migration. This tool uses machine learning to map cell shape dynamics and predict migration behavior.

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Area of Science:

  • Computational biology
  • Biophysics
  • Image analysis

Background:

  • Cell migration is crucial for physiological and pathological processes.
  • Cell shape dynamics are emergent properties of the forces driving cell migration.
  • Understanding cell shape-migration relationships is key to studying cellular behavior.

Purpose of the Study:

  • To introduce ShapeSpaceExplorer, an interactive software for analyzing complex 2D shape series.
  • To demonstrate the software's application in analyzing cell morphology changes during cell migration.
  • To develop a machine learning approach for understanding cell shape dynamics and migration behavior.

Main Methods:

  • Developed ShapeSpaceExplorer software for interactive extraction, visualization, and analysis of 2D shape series.
  • Implemented a machine learning algorithm to analyze cell shape from time-lapse images and learn the intrinsic low-dimensional structure of cell shape space.
  • Introduced a novel, rapid, and landmark-free shape difference measure for unbiased analysis of diverse cell morphologies.

Main Results:

  • The software enables visualization of cell shape distribution differences after perturbation experiments.
  • Quantitative relationships between cell shape and migration behavior were analyzed.
  • The method successfully predicted cell turning based on dynamic cell shape information.

Conclusions:

  • ShapeSpaceExplorer provides a powerful tool for visualizing and analyzing cell morphology changes.
  • The machine learning approach effectively maps cell shape dynamics and predicts migration behavior.
  • The software has broad applicability to various biological and inanimate object shape analyses.