Robust cell tracking in epithelial tissues through identification of maximum common subgraphs

Area of Science:

• Developmental Biology
• Cell Biology
• Biophysics

Background:

• Live-imaging microscopy of epithelial sheets is crucial for understanding embryonic development.
• Accurate cell tracking is essential for studying cell growth, proliferation, intercalation, apoptosis, and morphogenetic processes like tissue invagination and extension.
• Existing cell tracking methods struggle with large morphogenetic deformations and require manual intervention.

Purpose of the Study:

• To develop a novel, robust algorithm for tracking cells in epithelial sheets.
• To overcome limitations of current tracking methods in handling deformations and manual interventions.
• To enable accurate cell tracking in live-imaging microscopy videos of epithelial tissues.

Main Methods:

• Developed a new algorithm based on the graph-theoretic concept of 'maximum common subgraph' for cell tracking.
• The algorithm does not require tissue-specific parameter adjustments.
• The method scales in sub-quadratic time with tissue size and does not rely on precise positional information.

Main Results:

• Successfully tracked cells in the *Drosophila* embryonic epidermis.
• The algorithm accommodates large cell movements between frames and low temporal resolution data.
• Demonstrated robustness to experimental constraints like phototoxicity.

Conclusions:

• The novel algorithm provides accurate and robust cell tracking in epithelial sheets.
• It is applicable to various epithelial tissues and overcomes limitations of existing methods.
• The open-source implementation facilitates broader use in developmental and cell biology research.