Migration of cells in a social context

Abstract

In multicellular organisms and complex ecosystems, cells migrate in a social context. Whereas this is essential for the basic processes of life, the influence of neighboring cells on the individual remains poorly understood. Previous work on isolated cells has observed a stereotypical migratory behavior characterized by short-time directional persistence with long-time random movement. We discovered a much richer dynamic in the social context, with significant variations in directionality, displacement, and speed, which are all modulated by local cell density. We developed a mathematical model based on the experimentally identified "cellular traffic rules" and basic physics that revealed that these emergent behaviors are caused by the interplay of single-cell properties and intercellular interactions, the latter being dominated by a pseudopod formation bias mediated by secreted chemicals and pseudopod collapse following collisions. The model demonstrates how aspects of complex biology can be explained by simple rules of physics and constitutes a rapid test bed for future studies of collective migration of individual cells.cell migration | single-cell analysis | physical modeling | microfluidics C ollective migration, from migrating cells in tissue (1-3) to swarming insects (4) to flocks of birds (5) and pedestrians in heavy traffic (6), constitutes one of the most fascinating spectacles in nature. In addition to its aesthetic qualities, social cell migration is involved in embryonic development (7), wound healing (8), and immune response (9), and unregulated migration leads to disease, including cancer metastasis (10). Previous work on single-cell migration has focused on isolated (11)(12)(13)(14)(15)(16)(17)(18)(19)(20) or strongly polarized and aligning (21, 22) cell types, mostly using population-averaged bulk assays (23) or simple observations in a social context (2, 3). However, strongly cross-correlated cell motion and collective substrate deformation has been found to arise in mechanically interlinked cells transmitting forces through both cell-cell linkages and the substrate (24-29). These studies revealed useful information on cell migration, but because in general the relevant interactions in a social context and their relative importance are not established, migratory behavior of cells in a social context remains as one of the major unresolved problems in biology (30). Furthermore, striking social effects such as highly sensitive collective responses in a number of sensing systems [e.g., quorum sensing (31, 32) and onset of collective behavior in Dictyostelium discoideum (33)] mediated by increased levels of cell-secreted signals in higher cell density indicate that mechanical links are not necessary for collective behavior. At the subcellular level, many types of nonswimming motile cells involved in multicellular biology [e.g., fibroblasts, Dictyostelium, and neutrophils (13,14,(16)(17)(18)] have been found to transmit traction force to the substrate by intracellularly polymerizing their cytoskeleton...

Spatial moment dynamics for collective cell movement incorporating a neighbour-dependent directional bias

“…Pathologies such as cancer can arise when the regulatory mechanisms controlling movement are disrupted [4]. A desire to understand how large numbers of individuals are able to coordinate their movement has fuelled extensive studies into the interactions occurring between migrating cells [5][6][7]. Some interactions act as attractive forces to drive cells towards one another, for example, the physical coupling of neighbouring cells [8] or the release and detection of diffusible chemoattractant signals which give rise to chemotaxis [9,10].…”

Particle methods to solve modelling problems in wound healing and tumor growth

“…On the other hand, the parameter space in our models is much smaller, which also poses some merits for experimental validation and regression techniques. This is the clearest advantage of the current approach that is shared by the approach in [47]. The model in [47] is very interesting in the sense that it is also based on first principles and that it is probably also cheap in terms of computation time.…”

“…This is the clearest advantage of the current approach that is shared by the approach in [47]. The model in [47] is very interesting in the sense that it is also based on first principles and that it is probably also cheap in terms of computation time. The only shortcoming may be its applicability to high cell densities where cells collide often.…”

“…In literature, many other studies can be found concerning cellshape evolution, such as in the works by [4,21,29,33,36,47]. In [21], the cell moves through a complicated domain with obstacles as a result of a chemical stimulus.…”

“…Further, no partial differential equations have to be solved over the cell boundary in our methods opposed to the studies in [36,37]. The model in [47] treats migration of cells in larger quantities with applications to fibroblasts. The model is based on traffic rules that were observed experimentally in collective cell movement.…”