A toolbox to analyze collective cell migration, proliferation and cellular organization simultaneously

Area of Science:

• Cell Biology
• Biophysics
• Quantitative Biology

Background:

• Assessing collective cell migration and orientation in multicellular clusters is crucial for understanding their behavior.
• Existing tools lack the capability to simultaneously analyze collective migration, cellular orientation, and proliferation in phase contrast images.

Purpose of the Study:

• To develop and present a novel computational tool for the comprehensive analysis of collective cell behavior.
• To enable simultaneous quantification of migration, organization, and proliferation from phase contrast microscopy data.

Main Methods:

• Utilized Particle Image Velocimetry (PIV) to compute velocity fields for migration analysis.
• Employed the structure tensor method to determine cellular orientation.
• Developed an artificial neural network to identify and analyze cell division events.

Main Results:

• The tool successfully integrates PIV, structure tensor analysis, and an artificial neural network for multifaceted cell behavior assessment.
• Enabled correlation of migratory and organizational phenomena with cell density and proliferation.

Conclusions:

• The presented tool facilitates the simultaneous analysis of collective cell migration, (self-)organization, and proliferation from phase contrast images.
• Offers a unified approach to studying complex multicellular dynamics.