Coupled active systems encode emergent behavioral dynamics of the unicellular predator Lacrymaria olor
Authors: Scott M. Coyle, Eliott M. Flaum, Hongquan Li, Deepak Krishnamurthy, Manu Prakash
Link: https://www.sciencedirect.com/science/article/pii/S0960982219311960
DOI: https://doi.org/10.1016/j.cub.2019.09.034
Abstract: Many single-celled protists use rapid morphology changes to perform fast animal-like behaviors. To understand how such behaviors are encoded, we analyzed the hunting dynamics of the predatory ciliate Lacrymaria olor, which locates and captures prey using the tip of a slender “neck” that can rapidly extend more than seven times its body length (500 μm from its body) and retract in seconds. By tracking single cells in real-time over hours and analyzing millions of sub-cellular postures, we find that these fast extension-contraction cycles underlie an emergent hunting behavior that comprehensively samples a broad area within the cell’s reach. Although this behavior appears complex, we show that it arises naturally as alternating sub-cellular ciliary and contractile activities rearrange the cell’s underlying helical cytoskeleton to extend or retract the neck. At short timescales, a retracting neck behaves like an elastic filament under load, such that compression activates a series of buckling modes that reorient the head and scramble its extensile trajectory. At longer timescales, the fundamental length of this filament can change, altering the location in space where these transitions occur. Coupling these fast and slow dynamics together, we present a simple model for how Lacrymaria samples the range of geometries and orientations needed to ensure dense stochastic sampling of the immediate environment when hunting to locate and strike at prey. More generally, coupling active mechanical and chemical signaling systems across different timescales may provide a general strategy by which mechanically encoded emergent cell behaviors can be understood or engineered.
Highlights
Lacrymaria is a unicellular predator that hunts using extreme morphology dynamics
Computer vision digitizes millions of real-time sub-cellular postures during hunts
Morphology dynamics result in dense stochastic sampling of the local environment
Behavior emerges from fast and slow response of helical cytoskeleton to cyclic stress
Project: Lacrymaria olor
