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.