Monte Carlo simulation of cell death signaling predicts large cell-to-cell stochastic fluctuations through the type 2 pathway of apoptosis |
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Authors: | Raychaudhuri Subhadip Willgohs Eric Nguyen Thuc-Nghi Khan Elaine M Goldkorn Tzipora |
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Institution: | * Department of Biomedical Engineering, University of California, Davis, California † Graduate Group in Biophysics, University of California, Davis, California ‡ Graduate Group in Immunology, University of California, Davis, California § Graduate Group in Applied Mathematics, University of California, Davis, California ¶ School of Medicine, University of California, Davis, California |
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Abstract: | Apoptosis, or genetically programmed cell death, is a crucial cellular process that maintains the balance between life and death in cells. The precise molecular mechanism of apoptosis signaling and the manner in which type 1 and type 2 pathways of the apoptosis signaling network are differentially activated under distinct apoptotic stimuli is poorly understood. Based on Monte Carlo stochastic simulations, we show that the type 1 pathway becomes activated under strong apoptotic stimuli, whereas the type 2 mitochondrial pathway dominates apoptotic signaling in response to a weak death signal. Our results also show signaling in the type 2 pathway is stochastic; the population average over many cells does not capture the cell-to-cell fluctuations in the time course (~1–10 h) of downstream caspase-3 activation. On the contrary, the probability distribution of caspase-3 activation for the mitochondrial pathway shows a distinct bimodal behavior that can be used to characterize the stochastic signaling in type 2 apoptosis and other similar complex signaling processes. Interestingly, such stochastic fluctuations in apoptosis signaling occur even in the presence of large numbers of signaling molecules. |
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