&Cartridge; physics 15, 142
Experiments show that biological cells actively change shape to respond to their environment when moving in confined regions.
Movement of cells is essential for embryo development and wound healing. A study of single human cells moving on a microstructured surface reveals some of the basic principles of this movement and shows how cells adapt their shape and behavior to the geometry of their environment [1]. Based on their experimental results, researchers developed a theoretical model that could be used to study and predict cell movement in more complex environments.
The shapes of animal cells are controlled in part by a network of protein filaments called the cytoskeleton, which can be rearranged by the cell to drive movement. For example, a cell can begin to move by creating a protrusion that bulges out from its surface. Such movement depends on the adhesion of the cell to surrounding surfaces and on the formation of an asymmetric arrangement of the cytoskeleton, termed polarity by biologists, that drives the growth of protrusions. Movement is also influenced by the cell’s internal structures, particularly the nucleus, which is less compressible than the fluid cytoplasm.
To understand these different influences, researchers have studied how cells move on micropatterned surfaces with simple, geometric confining structures such as islands, channels and grooves [2]. David Brückner and his collaborators from the Ludwig Maximilian University of Munich (LMU) previously studied a human cancer cell migrating between two “sticky” islands connected by a narrow bridge [3]. They found that the cell develops a thin protrusion that reaches over the constriction and then covers the rest of the cell.
Now the Munich team has expanded this work by taking the shape changes of the entire cell into account. In the previous work, as well as in that of other researchers, only the movement of the nucleus was tracked. To get this broader picture of cell migration, LMU team member Chase Broedersz relied on a machine learning algorithm that tracked the shapes of hundreds of cells over several days as each one migrated back and forth across a bridge. Each bridge connected two 37 square micrometer patches of a surface coated with the adhesive protein fibronectin. The team used machine learning to reliably identify the cell edges in the microscope images.
“By analyzing the full shape dynamics of cells, we were able to unravel how protrusions and the polarity dynamics derived from them are coupled to the movement of the cell nucleus,” says Broedersz. The researchers found that a bridge-crossing protrusion normally allows the cell’s main body to ‘flow’ to the other patch before the nucleus is subsequently pulled across.
A key question was whether cells actively change shape as they move to match the geometry of their environment, or whether they are passively shaped by them, like water taking on the shape of a container. The researchers concluded that cells are actively responding and that bridge crossing involves a sort of switch in the cell’s internal state between a fairly aimless “exploration mode” and a directed “growth mode” dominated by the single ledge along the bridge. It’s as if the cell perceives the constraining shape and decides to change the shape accordingly. “This adaptive response to the constraint has not been recognized before,” says Broedersz.
The team’s model, informed by the experimental data, successfully predicted how motion would change if the bridge width was changed. The researchers now plan to test their model’s predictions for cell migration in more complex environments, such as 3D inclusions or in labyrinths – and perhaps ultimately in living tissue.
“The authors have done an excellent job with their phenomenological approach to the problem,” says biophysicist Herbert Levine of Northeastern University in Boston. “So the novelty lies in the data-driven theoretical treatment, which is more complete and quantitative than in their previous work.”
But Levine warns that the case of cells moving in real tissue in 3D is much more complicated and qualitatively different than moving on a flat surface. Bioengineer David Caballero of the University of Minho in Portugal agrees. The 3D microenvironment in real tissue “elicits cellular responses that are vastly different from those observed in 2D,” he says.
Broedersz answers that cell migration still occurs in living organisms through constraining geometries, for example when immune cells move through the extracellular matrix of tissues or when cancer cells migrate during tumor metastasis. If the adaptation to the constraining geometry observed in the experiments also occurs in these situations, the molecular mechanisms underlying it could potentially provide targets for cancer drugs, he says.
– Phillip Ball
Philip Ball is a freelance science writer based in London. His latest book is The modern myths (University of Chicago Press, 2021).
references
- DB Brueckner et al.“Geometry adaptation of protrusion and polarity dynamics in the migration of confined cells”, physics Rev X 12031041 (2022).
- CD Paul et al.“Engineered Models of Confined Cell Migration”, Annual Rev. Biomed. Closely. 18159 (2016).
- DB Brueckner et al.“Stochastic nonlinear dynamics of confined cell migration in two-state systems”, nat. physics fifteen595 (2019).
