Bowhead: Bayesian modelling of cell velocity during concerted cell migration.

Area of Science:

• Cell Biology
• Cancer Research
• Bioinformatics

Background:

• Cell migration is crucial for biological processes and implicated in cancer metastasis.
• Traditional wound healing assays analyze wound area, neglecting shape changes and leading to flawed interpretations.
• Accurate quantification of cell migration is vital for understanding both normal cell behavior and disease progression.

Purpose of the Study:

• To develop and present a novel software package for analyzing concerted cell velocity in wound healing assays.
• To provide a more robust and accurate method for quantifying cell migration compared to conventional techniques.
• To enable researchers to quantitatively analyze live cell migratory processes across various biological fields.

Main Methods:

• Developed a novel software package employing a wound detection algorithm based on cell confluency thresholding.
• Utilized a Bayesian approach to estimate concerted cell velocity with associated likelihood.
• Applied the method to analyze the effect of siRNA knockdown on breast cancer cell line migration.

Main Results:

• Demonstrated that the software quantifies cell velocity, tracking wound healing independently of wound shape.
• Achieved more robust quantification with significantly higher signal-to-noise ratios than conventional wound area analyses.
• Successfully applied the method to study siRNA knockdown effects on breast cancer cell migration.

Conclusions:

• The novel software provides a superior method for analyzing cell migration in wound healing assays.
• This tool enhances the quantitative analysis of live cell migratory processes, impacting cancer research and basic cell biology.
• The software is freely available, promoting wider adoption and advancing the study of cell migration.