Model Documentation

Model Status

This model has been altered by James Lawson on 14/05/07. The math in reaction elements has been moved up a level and is now the child of the component, not the reaction element. Backrates have been added and delta variables defined. The variable x_infinity is still missing, pending contact with the author of this paper. This model represents only the presynaptic cell model described in the paper. The postsynaptic cell model needs to be coded and the cells put in the network arrangement defined by the paper using CellML 1.1 imports. This work is pending the upgrade of the model repository to handle CellML 1.1 based models which use imports.

Model Structure

Ca²⁺ flux through voltage-gated channels plays a role in muscle contraction, gene expression, synaptic transmission, short- and long-term memory. Ca²⁺ channels are regulated by many electrical, genetic and biochemical pathways, including G-protein signal transduction pathways. In their 2002 study, Richard Bertram, Michelle I. Arnot, and Gerald W. Zamponi focus on the direct regulation of N-type Ca²⁺ channels by the G-beta-gamma subunits of activated G-proteins (see the figure below). Ca²⁺ ion binding to a low-affinity binding site induces vesicle fusion with the plasma membrane, followed by the release of transmitter by exocytosis. Transmitter binding to a presynaptic autoreceptor activates a G-protein, the G-beta-gamma subunit od which binds directly to an N-type Ca²⁺ channel. Such binding puts channels into a reluctant state, reducing the net flow of Ca²⁺ into the cell. Autoinhibition of transmitter release then occurs as the result of the G-protein-mediated inhibition of Ca²⁺ channels. The resultant depolarisation results in the unbinding of G-beta-gamma from the channel.

The mathematical model developed by bertram et al. in this study was used to address two questions: 1) What is the role of G-protein-mediated autoinhibition on synaptic signalling processing; and 2) How is signal processing affected by different G-beta-gamma isoforms? The presynaptic model has equations for membrane potential, Ca²⁺-dependent transmitter release, transmitter binding to autoreceptors, and Ca²⁺ influx through G-protein-regulated channels. This mathematical model has been translated into a CellML description which can be downloaded in various formats as described in .

The complete original paper reference is cited below:

Role for G Protein G-Beta-Gamma Isoform Specificity in Synaptic Signal Processing: A Computational Study, Richard Bertram, Michelle I. Arnot, and Gerald W. Zamponi, 2002, Journal of Neurophysiology , 87, 2612-2623. (Full text and PDF versions of the article are available for Journal Members on the Journal of Neurophysiology website.) PubMed ID: 11976397

Schematic diagram of the presynaptic model.

G-protein autoinhibitory feedback on the presynaptic terminal acts like a high-pass filter, allowing only high-frequency signals to pass through the to the postsynaptic cell. Low-frequency signals are effectively filtered out. Model simulations in this study show how different G-beta-gamma isoforms have different filtering properties. They also emphasise that the different filtering characteristics associated with a specific G-beta-gamma subunit depend on many biophysical parameters, such as the unbinding rate of a transmitter molecule from the presynaptic autoreceptor. For example faster unbinding lowers the filter cut while slower unbinding raises it. This allows for great synapse-tot-synapse variability in the distinction between signal and background noise.

Related Models

• Role for G protein Gbetagamma isoform specificity in synaptic signal processing: a computational study version 4
• Role for G Protein G-beta-gamma Isoform Specificity in Synaptic Signal Processing: A Computational Study version 3
• Role for G Protein G-beta-gamma Isoform Specificity in Synaptic Signal Processing: A Computational Study version 1