Collective motion of cells: from experiments to models

TL;DR

This paper reviews experimental and computational studies on cellular collective motion, highlighting its biological significance, underlying principles, and the role of cell adhesion, with insights into modeling and interpretation.

Contribution

It provides a comprehensive overview of cellular collective motion, integrating experimental results with computational models to interpret the phenomena quantitatively.

Findings

Cell collective motion is crucial in processes like embryogenesis and wound healing.

Adhesion between cells is key to their coordinated movement.

Models help interpret cellular behavior at a quantitative level.

Abstract

Swarming or collective motion of living entities is one of the most common and spectacular manifestations of living systems having been extensively studied in recent years. A number of general principles have been established. The interactions at the level of cells are quite different from those among individual animals therefore the study of collective motion of cells is likely to reveal some specific important features which are overviewed in this paper. In addition to presenting the most appealing results from the quickly growing related literature we also deliver a critical discussion of the emerging picture and summarize our present understanding of collective motion at the cellular level. Collective motion of cells plays an essential role in a number of experimental and real-life situations. In most cases the coordinated motion is a helpful aspect of the given phenomenon and results in making a related process more efficient (e.g., embryogenesis or wound healing), while in the case of tumor cell invasion it appears to speed up the progression of the disease. In these mechanisms cells both have to be motile and adhere to one another, the adherence feature being the most specific to this sort of collective behavior. One of the central aims of this review is both presenting the related experimental observations and treating them in the light of a few basic computational models so as to make an interpretation of the phenomena at a quantitative level as well.