Calcium encoding

Elementary modes of calcium encoding. AM, FM and AFM encoding Ca²⁺ oscillations correspond to analogous modulations in electronic communications.[3]

Although elevations of Ca²⁺ are necessary for it to act as a signal, prolonged increases of the concentration of Ca²⁺ in the cytoplasm can be lethal for the cell. Thus cells avoid death usually delivering Ca²⁺ signals as brief transients - i.e. Ca²⁺ elevations followed by a rapid decay - or in the form of oscillations. In analogy with Information Theory, either the amplitude or the frequency or both features of these Ca2+ oscillations define the Ca²⁺ encoding mode. Therefore, three classes of Ca²⁺ signals can be distinguished on the basis of their encoding mode:[2][3][5]

• • AM encoding Ca²⁺ signals: when the strength of the stimuli is encoded by amplitude modulations of Ca²⁺ oscillations. In other words, stimuli of the same nature but of different strength are associated with different amplitudes of Ca²⁺ oscillations but the frequencies of these oscillations are similar;
  • FM encoding Ca²⁺ signals: when the strength of the stimuli is encoded by frequency modulations of Ca²⁺ oscillations. In other words, stimuli of the same nature but of different strength are associated with different frequencies of Ca²⁺ oscillations but the amplitudes of these oscillations are similar;
  • AFM encoding Ca²⁺ signals: when both AM and FM encoding modes coexist.

Experiments and biophysical modeling, show that the mode of calcium encoding varies from cell to cell, and that a given cell could even show different types of calcium encoding for different patho-physiological conditions.[6][7] This could ultimately provide a crucial tool in medical diagnostics, to characterize, recognize and prevent diseases.[6] Analysis tools based on Furier transform have been developed that can perform spectral analysis and examine calcium oscillations from experimental data [8]

Calcium encoding can be mathematically characterized by biophysical models of calcium signaling.[9] Phase plane and bifurcation analysis of these models, can reveal in fact how frequency and amplitude of calcium oscillations vary as a function of any parameter of the model.[3] Occurrence of AM-, FM- or AFM-encoding can be assessed on the extension of the min-max range of amplitude and frequency of Ca²⁺ oscillations and the bifurcation structure of the system under study.

Stimulus integration. Only if the stimulus allows accumulation (i.e. integration) of IP₃ up to a certain threshold then an FM-encoding Ca²⁺ oscillation occurs.[4][7]

A critical aspect of Ca²⁺ encoding revealed by modeling, is how it depends on the dynamics of the complex network of reactions of underlying Ca²⁺-mobilizing signals. This aspect can be addressed considering Ca²⁺ models that include both Ca²⁺ dynamics and the dynamics of Ca²⁺-mobilizing signals. One simple and biophysically realistic model of this kind is the ChI model, originally developed by Eshel Ben-Jacob and co-workers,[4] for GPCR-mediated inositol-1,4,5-trisphosphate (IP₃)-triggered Ca²⁺-induced Ca²⁺-release. The main conclusion of this study was that the dynamics of the Ca²⁺-mobilizing IP₃ signal is essentially AFM encoding with respect to the stimulus whereas Ca²⁺ oscillations can be either FM or AFM but not solely AM.[4] It was argued that the AFM nature of the Ca²⁺-mobilizing IP₃ signal could represent the ideal solution to optimally translate pulsed or discontinuous extracellular signals into intracellular continuous-like Ca²⁺ oscillations.[4]

Calcium encoding can be confined within a single cell or involve cell ensembles[9][10] and deploy essential computational tasks, such as stimulus integration[4][11] or regulated activation of gene transcription.[12] Moreover, cells are often organized in networks, allowing intercellular propagation of calcium signaling.[10] With this regard, the same mode of calcium encoding could be shared by different cells, providing synchronization[4] or the functional basis to implement more complex computational tasks.[7]

Michael Forrest has shown that intracellular calcium dynamics may permit a Purkinje neuron to perform toggle and gain computations upon its inputs.[13] So, showing how an ion concentration can be used as a computational variable - in particular, as a memory element: recording a history of firing and inputs, to dictate how the neuron responds to future inputs. Thus, this work hypothesizes that the membrane potential (V) is not the Purkinje cell's only coding variable but works alongside a calcium memory system. These two interact, with the calcium memory being encoded and decoded by the membrane potential. The toggle and gain computations are likely to be salient to network computations in the cerebellum, in the brain. Thus, ion computations can be important more globally than a single cell. Forrest terms this hypothesis: "ion to network computation".

• Cell Signaling Biology
• Prof. Eshel Ben-Jacob's homepage
• Prof. Herbert Levine's homepage
• Prof. Hugues Berry's homepage
• Dr. Vladislav Volman's homepage
• Dr. Maurizio De Pittà's homepage