  Collective behavior in cellular populations is coordinated by biochemical
signaling networks within individual cells. Connecting the dynamics of these
intracellular networks to the population phenomena they control poses a
considerable challenge because of network complexity and our limited knowledge
of kinetic parameters. However, from physical systems we know that behavioral
changes in the individual constituents of a collectively-behaving system occur
in a limited number of well-defined classes, and these can be described using
simple models. Here we apply such an approach to the emergence of collective
oscillations in cellular populations of the social amoeba Dictyostelium
discoideum. Through direct tests of our model with quantitative in vivo
measurements of single-cell and population signaling dynamics, we show how a
simple model can effectively describe a complex molecular signaling network and
its effects at multiple size and temporal scales. The model predicts novel
noise-driven single-cell and population-level signaling phenomena that we then
experimentally observe. Our results suggest that like physical systems,
collective behavior in biology may be universal and described using simple
mathematical models.
