Quantifying collective behavior in mammalian cells
Author(s) -
Jacinta C. Conrad
Publication year - 2012
Publication title -
proceedings of the national academy of sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 5.011
H-Index - 771
eISSN - 1091-6490
pISSN - 0027-8424
DOI - 10.1073/pnas.1205451109
Subject(s) - computational biology , biology , chemistry , computer science
Collective social behaviors generate one emergent response from many individual actors without central coordination: bees swarm, birds flock, and fish school. Single-celled bacteria and amoebae collectively swarm, detecting chemical signals emitted by close neighbors to synchronize their motion. Within organisms, collective behaviors drive multicellular processes during migration and wound healing. Similar to unicellular organisms, mammalian cells coordinate their responses during these complex processes by detecting changes in concentration of signaling molecules. However, the signaling pathways used by mammalian cells are typically more interdependent than those in unicellular organisms, and gene expression varies with the time-dependent concentration of signaling molecules. Understanding the role of intercellular communications for collective behavior in mammalian cells thus demands sensitive measurements of responses to chemical signals. In PNAS, Sun et al. (1) quantify the spatiotemporal evolution of calcium response to ATP stimulation in fibroblasts. They find that the response of dense colonies of cells to ATP stimulation is faster and more synchronized than that of isolated cells. By quantitatively correlating responses between neighboring pairs of cells, they identify pacemaker cells; by physically separating cells in a hydrogel matrix, they confirm that cells communicate via gap junctions to synchronize their responses. These experiments show that both temporal and spatial dynamics of collective response in mammalian cells depend on intercellular signaling. In bacteria, transitions from individual to collective behavior are frequently coupled to changes in cell density. For example, bacteria transition from mechanisms of individual motility (2) to collective motility modes, such as twitching (3), when the cell density exceeds a critical threshold. Similarly, initially free-living planktonic bacteria form surface-associated communities called biofilms when the density of cells and the population size exceed critical thresholds, so that the concentration of signaling molecules (autoinducers) in the space between bacteria …
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