Explorable:
How adhesion dynamics affect cell motility

The following explorable contains an interactive computational model of cell migration. You can adjust the model parameters using the sliders under "simulation parameters" to explore how adhesion alters motility dynamics.

Model summary

The model is described in detail in the paper, but briefly, it is a cellular Potts model (CPM) based on the following rules:

• When a cell successfully protrudes and gains a new pixel, that pixel gains an activity for some time that makes it more likely that this pixel will protrude again (positive feedback, activity indicated by red-yellow color below). The duration of the "activity memory" is governed by max_act, the strength of the positive feedback by λ_act;
• In the protrusive region where local activities are >0.75 x max_act, adhesive sites can spawn with probability p_s. Such adhesive sites (dark pixels in the simulation below) are harder for the cell to detach if it wants to retract, so copy attempts into an adhesion get penalty λ_adh;
• Adhesive patches can also expand and decay independently, at rates governed by the parameters p_e and p_d, respectively;
• Adhesion to the surface determines how well the cell can translate protrusive force at the front into actual motion, because higher adhesion prevents "slipping" and staying in place. The fraction of the cell surface occupied by adhesive sites therefore modifies λ_act: the effective λ_act starts from a baseline fraction b of its value when there are no adhesions at all, and reaches its full value only when at least a fraction s of the cell surface is adhered to the substrate.

Try it yourself

You can use the parameter sliders in the dropdown menu below ("simulation parameters") to explore how changing them affects cell motility. Yellow to red colors indicate active pixels with protrusive feedback. Dark patches are adhesions, and the blue line shows the trajectory of the cell's center of mass over time.

Suggestions of things to try:

• When either λ_act or max_act is zero, cells should stop moving because there is no "protrusive feedback" or "activity memory".
• When λ_adh is very high, cells should stop moving because their adhesions are anchored so firmly that they are impossible to detach.
• The number of adhesion patches can be controlled by p_s, p_e, and p_d. Higher p_s/p_e should lead to more adhesive patches because of higher formation rates, and lowering p_d has the same effect by making existing patches more stable.
• p_s and p_e also control the spatial distribution of adhesions: when only p_s > 0, patches are smaller and more evenly distributed because existing patches cannot expand. By contrast, when p_s is lower and p_e is very high, patches tend to be larger and can accumulate at the rear of the cell, slowing it down and/or making it "pivot" and turn.
• When b = 1 and s = 0 (the default), the cell does not slip on the surface regardless the number of adhesions. Fixing b = 0 and s = 1 should make the cell dependent on adhesions for motion: at these values, setting p_s/p_e to zero and p_d to high values will stop motion.

See also

This simulation implements the model from the paper:

Steijn et al (2021). Computational Modelling of Cell Motility Modes Emerging from Cell-Matrix Adhesion Dynamics. bioRxiv.
Note: As of January 2022 in press at PLOS Computational Biology; this link will be updated upon publication.

This model builds on the Act-CPM, which was first published in:

Niculescu et al (2015). Crawling and Gliding: A Computational Model for Shape-Driven Cell Migration. PLoS Computational Biology.

and later further characterised in:

Wortel et al (2021). Local Actin Dynamics Couple Speed and Persistence in a Cellular Potts Model of Cell Migration. Biophysical Journal.

If you are new to the (Act-)CPM, you can explore how they work in the following interactive simulations:

Explorable: Introduction to the CPM

Explorable: Act-model

All these interactive simulations were made using Artistoo, which you can read more about here:

Wortel and Textor (2021). Artistoo, a Library to Build, Share, and Explore Simulations of Cells and Tissues in the Web Browser. eLife.