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Published October 7, 2015 | Published
Journal Article Open

Computational reconstitution of spine calcium transients from individual proteins


We have built a stochastic model in the program MCell that simulates Ca^(2+) transients in spines from the principal molecular components believed to control Ca^(2+) entry and exit. Proteins, with their kinetic models, are located within two segments of dendrites containing 88 intact spines, centered in a fully reconstructed 6 × 6 × 5 μm^3 cube of hippocampal neuropil. Protein components include AMPA- and NMDA-type glutamate receptors, L- and R-type voltage-dependent Ca^(2+) channels, Na^+/Ca^(2+) exchangers, plasma membrane Ca^(2+) ATPases, smooth endoplasmic reticulum Ca^(2+) ATPases, immobile Ca2+ buffers, and calbindin. Kinetic models for each protein were taken from published studies of the isolated proteins in vitro. For simulation of electrical stimuli, the time course of voltage changes in the dendritic spine was generated with the desired stimulus in the program NEURON. Voltage-dependent parameters were then continuously re-adjusted during simulations in MCell to reproduce the effects of the stimulus. Nine parameters of the model were optimized within realistic experimental limits by a process that compared results of simulations to published data. We find that simulations in the optimized model reproduce the timing and amplitude of Ca^(2+) transients measured experimentally in intact neurons. Thus, we demonstrate that the characteristics of individual isolated proteins determined in vitro can accurately reproduce the dynamics of experimentally measured Ca^(2+) transients in spines. The model will provide a test bed for exploring the roles of additional proteins that regulate Ca^(2+) influx into spines and for studying the behavior of protein targets in the spine that are regulated by Ca^(2+) influx.

Additional Information

© 2015 Bartol, Keller, Kinney, Bajaj, Harris, Sejnowski and Kennedy. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. Received: 19 June 2015; Accepted: 11 September 2015; Published: 07 October 2015. This work was supported by NIH grants NS21184, MH095980, and NS074644 (KH), NIH grants NS44306 and DA030749 (MK, TS, TB), NIH grants MH079076 and P41-GM103712 (TJS, TB), NIH grant EB00487 (CB), NSF grant OCI-1216701 (CB), the Howard Hughes Medical Institute, the Texas Emerging Technologies Fund, and the Gordon and Betty Moore Foundation. We thank B. Dylan Bannon for comments on the manuscript. The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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August 20, 2023
August 20, 2023