Computational model of the insect pheromone transduction cascade

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Abstract

A biophysical model of receptor potential generation in the male moth olfactory receptor neuron is presented. It takes into account all pre-effector processes-the translocation of pheromone molecules from air to sensillum lymph, their deactivation and interaction with the receptors, and the G-protein and effector enzyme activation-and focuses on the main post-effector processes. These processes involve the production and degradation of second messengers (IP3 and DAG), the opening and closing of a series of ionic channels (IP3-gated Ca2+ channel, DAG-gated cationic channel, Ca2+-gated Cl- channel, and Ca2+- and voltage-gated K+ channel), and Ca2+ extrusion mechanisms. The whole network is regulated by modulators (protein kinase C and Ca 2+-calmodulin) that exert feedback inhibition on the effector and channels. The evolution in time of these linked chemical species and currents and the resulting membrane potentials in response to single pulse stimulation of various intensities were simulated. The unknown parameter values were fitted by comparison to the amplitude and temporal characteristics (rising and falling times) of the experimentally measured receptor potential at various pheromone doses. The model obtained captures the main features of the dose-response curves: the wide dynamic range of six decades with the same amplitudes as the experimental data, the short rising time, and the long falling time. It also reproduces the second messenger kinetics. It suggests that the two main types of depolarizing ionic channels play different roles at low and high pheromone concentrations; the DAG-gated cationic channel plays the major role for depolarization at low concentrations, and the Ca2+-gated Cl - channel plays the major role for depolarization at middle and high concentrations. Several testable predictions are proposed, and future developments are discussed.

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Gu, Y., Lucas, P., & Rospars, J. P. (2009). Computational model of the insect pheromone transduction cascade. PLoS Computational Biology, 5(3). https://doi.org/10.1371/journal.pcbi.1000321

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