ABSTRACT
Transportation .................................................................................................. 222 11.4.3 Interaction Between Migratory Cells................................................... 225 11.4.4 Other Properties of Multi-Cellular Logistics ....................................... 230 11.5 Conclusion ....................................................................................................... 233 Keywords ................................................................................................................. 233 Author Contributions ............................................................................................... 234 Acknowledgments .................................................................................................... 234 References ................................................................................................................ 234
11.1 INTRODUCTION
During development, the formation of biological networks (such as organs and neuronal networks) is controlled by multicellular transportation phenomena based on cell migration. In multi-cellular systems, cellular locomotion is restricted by physical interactions with other cells in a crowded space, similar to passengers pushing others out of their way on a packed train. The motion of individual cells is intrinsically stochastic and may be viewed as a type of random walk. However, this walk takes place in a noisy environment because the cell interacts with its randomly moving neighbors. Despite this randomness and complexity, development is highly orchestrated and precisely regulated, following genetic (and even epigenetic) blueprints. Although individual cell migration has long been studied, the manner in which stochasticity affects multicellular transportation within the precisely controlled process of development remains largely unknown. To explore the general principles underlying multicellular migration,
we focus on the migration of neural crest cells, which migrate collectively and form streams. We introduce a mechanical model of multi-cellular migration. Simulations based on the model show that the migration mode depends on the relative strengths of the noise from migratory and non-migratory cells. Strong noise from migratory cells and weak noise from surrounding cells causes “collective migration,” whereas strong noise from non-migratory cells causes “dispersive migration.” Moreover, theoretical analyses reveal that migratory cells attract each other over long distances, even without direct mechanical contacts. This effective interaction depends on the stochasticity of the migratory and non-migratory cells. On the basis of these findings, we propose that stochastic behavior at the single-cell level works effectively and precisely to achieve collective migration in multi-cellular systems. Movements of various cell groups are ubiquitous during development. The extent and speed of migrations must be wellcontrolled to achieve precise axon placement in the wiring of neuronal networks and to ensure the appropriate morphogenesis of tissues and organs [1]. In this chapter, we focus on multi-cellular collective migration, which can be observed in the behaviors of cranial neural crest cells during embryonic development, as a model system for understanding how the system-level control of cellular transportation is achieved; such system-level control is called “logistics”. This transportation is accompanied by cell migration that is directed by extra-cellular signaling molecules working as chemoattractants or repellants. In multi-cellular systems, cellular locomotion is restricted by physical interactions with other cells in a crowded space, similarly to passengers pushing others out of their way on a packed train. The mechanisms underlying multicellular logistics in these crowded space remain largely unknown.
