Identifying the mechanism for superdiffusivity in mouse fibroblast motility

Area of Science:

• Cell Biology
• Biophysics
• Quantitative Biology

Background:

• Cell migration is crucial for biological processes.
• Superdiffusive cell motility, where displacements scale faster than t1/2, is observed in various cell types.
• Existing models, including run-and-tumble with Lévy-distributed run times or heterogeneous noise, struggle to fully explain observed cell trajectories.

Purpose of the Study:

• To characterize the super-diffusive motility of mouse fibroblasts on 2D substrates.
• To develop and validate computational tools for distinguishing between proposed models of cell motility.
• To identify the underlying mechanisms governing fibroblast migration.

Main Methods:

• Automated tracking of mouse fibroblast trajectories on 2D substrates.
• Development of an automated toolkit to compare experimental data with model predictions.
• Quantitative analysis of cell displacements, velocity autocorrelation, displacement probability distributions, and turning angle distributions.

Main Results:

• Fibroblast trajectories exhibit super-diffusive behavior.
• Ensemble-averaged quantities fit both run-and-tumble and heterogeneous noise models equally well.
• Neither existing model accurately captured short-timescale behaviors, such as displacement and turning angle distributions.
• A novel hybrid model incorporating run-and-tumble dynamics and heterogeneous noise during runs accurately matched all observed behaviors.

Conclusions:

• Mouse fibroblast motility on 2D substrates is complex and not fully explained by existing simple models.
• The developed hybrid model provides a more accurate description of fibroblast migration dynamics.
• Fibroblast run times are not Lévy distributed, challenging previous hypotheses.
• The analysis toolkit offers a valuable resource for future studies on cell motility mechanisms.