Signaling networks respond to diverse stimuli, but how the state of the signaling network is relayed to downstream cellular responses is unclear. We modeled how incremental activation of signaling molecules is transmitted to control apoptosis as a function of signal strength and dynamic range. A linear signal input-response output relationship, with signaling dynamic range uniformly distributed across activation states, most accurately predicted cellular responses. When nonlinearized signals relay network activation to apoptosis, we observe catastrophic, stimulus-specific prediction failures. We develop a general computational technique, “model-breakpoint analysis”, to analyze the mechanism of these failures, identifying new time- and stimulus-specific roles for Akt, ERK and MK2 kinase activity, which were experimentally verified. We further show that hyperactive and hypoactive MK2 alleles provide stronger and weaker levels of signaling, respectively; however both reduce apoptosis compared to wildtype MK2 because of reduced dynamic range. Dynamic range is rarely measured in signal-transduction studies but our experiments based on model-breakpoint analysis indicate that it may be a greater determinant of cell fate than measured signal strength.
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