In Dictyostelium discoideum extracellular cyclic AMP (cAMP), as shown by previous studies, induces a transient accumulation of intracellular cyclic guanosine-5'-monophosphate (cGMP), which peaks at 10 s and recovers basal levels at 30 s after stimulation, even with persistent cAMP stimulation. Additional investigations have shown that the cAMP-mediated cGMP response is built up from surface cAMP receptor-mediated activation of guanylyl cyclase and hydrolysis of cGMP by phosphodiesterase. The regulation of these activities was measured in detail on a seconds time-scale, demonstrating complex adaptation of the receptor, allosteric activation of cGMP-phosphodiesterase by cGMP, and potent inhibition of guanylyl cyclase by Ca2+. In this paper we present a computer model that combines all experimental data on the cGMP response. The model is used to investigate the contribution of each structural and regulatory component in the final cGMP response. Four models for the activation and adaptation of the receptor are compared with experimental observations. Only one model describes the magnitude and kinetics of the response accurately. The effect of Ca2+ on the cGMP response is simulated by changing the Ca2+ concentrations outside the cell (Ca2+ influx) and in stores (IP3-mediated release) and changing phospholipase C activity. The simulations show that Ca2+ mainly determines the magnitude of the cGMP accumulation; simulations are in good agreement with experiments on the effect of Ca2+ in electropermeabilized cells. Finally, when cGMP-phosphodiesterase activity is deleted from the model, the simulated cGMP response is elevated and prolonged, which is in close agreement with the experimental observations in mutant stmF that lacks this enzyme activity. We conclude that the computer model provides a good description of the observed response, suggesting that the main structural and regulatory components have been identified.
Modeling of the Kinetics of Carbonitride Precipitation Process in High-Strength Low-Alloy Steels Using Cellular Automata Method