Quantifying the impact of electric fields on single-cell motility.

Area of Science:

• Cellular and Molecular Biology
• Biophysics
• Mathematical Modeling in Biology

Background:

• Cell motility is fundamental to multicellular organism development and is influenced by environmental cues.
• Electric fields (EFs) induce electrotaxis, a cellular migration process vital for wound healing and other biological functions.
• The precise mechanisms underlying electrotaxis are complex, likely involving multiple cellular responses to EFs.

Purpose of the Study:

• To mathematically model and parameterize hypothetical mechanisms of cell motility response to electric fields.
• To quantitatively predict cellular behavior under externally applied electric fields for controlled electrotaxis.
• To identify the specific mechanisms through which EFs influence cell motility.

Main Methods:

• Development of a mathematical model describing potential cellular responses to electric fields.
• Calibration of the model using synthetic likelihoods and Bayesian sequential learning techniques.
• Analysis of observed data to determine the most plausible mechanism of EF-induced cell motility.

Main Results:

• The study identified a single, dominant mechanism responsible for electric field-biased cellular motility.
• The developed model accurately predicts cellular responses to various electric field configurations.
• Demonstrated the capability to make quantitative predictions of cell motility under different EF conditions.

Conclusions:

• Electric fields bias cell motility through a specific, identified mechanism, not a combination of effects.
• The validated model provides a foundation for designing targeted electric fields to control cell migration.
• This work paves the way for future data-driven, model-based feedback control strategies using electric actuation.