Mathematical Biology Seminar
Tatsuo Shibata
Hiroshima University
Wednesday Feb 22, 2006
"Stochastic signal processing in chemotactic response of eukaryotic cells"
Abstract:
Living cells can sense and respond to environmental signals through the
dynamic processes of molecular machines such as molecular sensors, signal
transducer, and molecular motors. Recent progress in single-molecule
analysis has been revealing the stochastic nature of the molecular machines
in eukaryotic cells. Thus, living cells is considered as
stochastically-operating bimolecular computation systems. The chemotactic
cell Dyctostelium can detect chemoattractant gradients that differ by as
little as 2% between the front and the back of the cell. Stochastic
fluctuations involving in the signaling process may have strong influence on
the chemotaxis. Here, we study a stochastic model of chemotactic signaling
in order to discuss quantitatively the propagation of signal and noise along
transmembrane signaling processes. Based on the model, we derived
signal-to-noise ratio (S/N) in the transmembrane signaling processes. The
dependence of S/N on the chemoattractant concentration exhibits bell-shaped
profile, which is in good agreement with chemotaxis accuracy obtained
experimentally. We also show how S/N can be improved or deteriorated by the
stochastic properties of receptors and the downstream molecules.
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Mathematical Biology Program
Department of Mathematics
University of Utah
155 South 1400 East Room 233
Salt Lake City, UT 84112
rasmusse@math.utah.edu
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