From intracellular signaling to population oscillations: bridging size‐ and time‐scales in collective behavior

• Published in: Molecular systems biology 2015-01, Vol.11 (1), p.779-n/a
• Main Authors: Sgro, Allyson E, Schwab, David J, Noorbakhsh, Javad, Mestler, Troy, Mehta, Pankaj, Gregor, Thomas
• Format: Article
• Language: English
• Subjects: Amoeba; Behavior; Cell adhesion & migration; Cellular communication; Complexity; Dictyostelium - cytology; dynamical systems; EMBO33; EMBO37; Fourier transforms; FRET; Gene expression; Gene Expression Regulation; Image Processing, Computer-Assisted; In vivo methods and tests; Intracellular; Intracellular signalling; live microscopy; Mathematical models; Microfluidic Analytical Techniques - instrumentation; Molecular Dynamics Simulation; Noise prediction; Oscillations; Phase transitions; phenomenological modeling; Population; Populations; Signal Transduction; Signaling
• ISSN: 1744-4292; 1744-4292
• DOI: 10.15252/msb.20145352

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 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. Synopsis A simple two‐variable model in combination with quantitative in vivo measurements of single‐cell and population signaling dynamics is used to analyze the emergence of collective cAMP oscillations in Dictyostelium discoideum . Single Dictyostelium cells are well described as excitable, oscillatory systems. A universal, top‐down model reproduces single‐cell and population‐level behaviors. Model‐based predictions are validated in individual cells and in cellular populations. Stochasticity drives the emergence and continued coordination of collective behavior. Graphical Abstract A simple two‐variable model in combination with quantitative in vivo measurements of single‐cell and population signaling dynamics is used to analyze the emergence of collective cAMP oscillations in Dictyostelium discoideum .