Dendritic spines are small morphologically identifiable structures that are the major sites where excitatory neurotransmission occurs in the mammalian brain. Thorough knowledge of their structure and function are critical for understanding information processing in the nervous system at the cellular level. Spines are well isolated biochemical compartments permitting each spine to function as an independent biochemical unit. Spines are also the site where synaptic plasticity is in part induced and maintained via the activation of well-orchestrated sets of enzymes that modify synaptic function. Critical in most models of synaptic plasticity is the role of increased intracellular Ca2+ in inducing long-term functional changes and spines have evolved unique mechanisms to finely control the temporal and quantitative nature of the Ca2+-signal. However, how this single second messenger is used to produce responses as distinct as long-term potentiation or long-term depression is not clear. We propose that calmodulin serves a critical role in determining how Ca2+ signals are decoded by the spine's biochemical apparatus. More specifically, we hypothesize that previously unrecognized Ca2+-dependent and Ca2+- independent calmodulin-target interaction are responsible for decoding the Ca2+-signal. We propose to test these ideas by applying a computational strategy.
Three specific aims will be accomplished. First, detailed models will be constructed of the Ca2+/calmodulin signaling pathway based on biophysical and enzymatic data collected from in vitro experiments. This will allow us to investigate an important role of calmodulin-target interaction in decoding Ca2+ signals in a well-mixed compartment. Second, a Monte Carlo computer simulation will be constructed to model molecular interaction between CaM and target protein that are undergoing diffusion in a non-homogenous model of spine cytoplasm. This novel simulation is based on and guided by on-going in vitro as well as in vivo fluorescence spectroscopic data of calmodulin-target protein interactions. Third, the simulation will be extended to incorporate geometric boundaries and spatial constraints of the dendritic spine. This model will allow us to explore how Ca2+- signal driven calmodulin-target interactions in the spine are orchestrated in space and time and to correlate their activation with different forms of synaptic plasticity (e.g., spike-timing dependent plasticity, LTP and LTD). The long-term goal of the studies is to establish a computational model of a spine that can be used to investigate hypotheses concerning the information processing capabilities of enzymatic networks constrained by known structural, biochemical and biophysical data.
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