28 September 2007
Wallace Marshall
Department of Biochemistry and Biophysics
UCSF
Self-organization and collective phenomena such as phase transitions and large-scale pattern formation are often studied in systems whose interacting components are fixed in space. However, there has been recently increasing interest in studying these phenomena in systems whose components actively move relative to one another, such as robots or flocking birds. In such cases the individual components are termed agents or self-propelled particles (SPPs). One underlying question in studies of systems of SPP is how intelligent do the individual agents need to be in order to generate collective behavior within a population. Most of the SPPs that have been studied posses significant computational capacity and can interact with each other using detailed visual observations as well as overt inter-agent communication channels such as speech. How much of this computation and communication is really necessary to get self-organization? Our approach to this question is to explore the ability of single swimming cells to self-organize and perform collective movements, since single cells are presumably quite limited in their computational capacity and communication ability. Our studies use suspensions of the unicellular green alga Chlamydomonas, which swim at a speed of 100 microns per second using a pair of flagella. These cells are both phototactic, swimming towards light, and gravitactic, swimming down towards the center of the earth. We fortuitously noticed, in earlier studies, that identical suspensions of cells distributed in a series of identical containers appeared to initiate gravitactic motion at random times, suggesting that individual populations make a collective decision to initiate gravitaxis. We also have noticed waves and other large scale patterns in suspensions of cells at the onset of gravitaxis. Based on these observations, we have set out to develop Chlamydomonas gravitaxis as a system to study self-organization and phase transitions in populations of self-propelled particles. Compared to other biological SPP systems, such as schooling fish or swarming locusts, the simple growth conditions, facile genetic manipulations, and easy observation make this an excellent experimental system, while the comparative stupidity of Chlamydomonas cells compared to whole animals with brains simplifies the range of potential models. We therefore feel that this system provides an excellent opportunity to combine experimental measurements and modeling approaches to understand how SPPs can self-organize at the lower limits of computational capacity. We are now developing both agent-based and lattice-based models for self-organization in this system, and conducting measurements to analyze the effect of hydrodynamic coupling between neighboring cells on their behavior, which we assume to be the underlying basis of agent-agent communication.