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Register a new userMultimodal encoding in a simplified model of intracellular calcium signaling
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Maurizio De Pitta`
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Many cells use calcium signalling to carry information from the extracellular side of the plasma membrane to targets in their interior. Since virtually all cells employ a network of biochemical reactions for Ca2+ signalling, much effort has been devoted to understand the functional role of Ca2+ responses and to decipher how their complex dynamics is regulated by the biochemical network of Ca2+-related signal transduction pathways. Experimental observations show that Ca2+ signals in response to external stimuli encode information via frequency modulation or alternatively via amplitude modulation. Although minimal models can capture separately both types of dynamics, they fail to exhibit different and more advanced encoding modes. By arguments of bifurcation theory, we propose instead that under some biophysical conditions more complex modes of information encoding can also be manifested by minimal models. We consider the minimal model of Li and Rinzel and show that information encoding can occur by amplitude modulation (AM) of Ca2+ oscillations, by frequency modulation (FM) or by both modes (AFM). Our work is motivated by calcium signalling in astrocytes, the predominant type of cortical glial cells that is nowadays recognized to play a crucial role in the regulation of neuronal activity and information processing of the brain. We explain that our results can be crucial for a better understanding of synaptic information transfer. Furthermore, our results might also be important for better insight on other examples of physiological processes regulated by Ca2+ signalling.
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The complex dynamics of intracellular calcium regulates cellular responses to information encoded in extracellular signals. Here, we study the encoding of these external signals in the context of the Li-Rinzel model. We show that by control of biophysical parameters the information can be encoded in amplitude modulation, frequency modulation or mixed (AM and FM) modulation. We briefly discuss the possible implications of this new role of information encoding for astrocytes.
Transforming Growth Factor-beta (TGF-beta) signalling is an important regulator of cellular growth and differentiation. The principal intracellular mediators of TGF-beta signalling are the Smad proteins, which upon TGF-beta stimulation accumulate in the nucleus and regulate transcription of target genes. To investigate the mechanisms of Smad nuclear accumulation, we developed a simple mathematical model of canonical Smad signalling. The model was built using both published data and our experimentally determined cellular Smad concentrations (isoforms 2, 3, and 4). We found in mink lung epithelial cells that Smad2 (8.5-12 x 10^4 molecules/cell) was present in similar amounts to Smad4 (9.3-12 x 10^4 molecules/cell), while both were in excess of Smad3 (1.1-2.0 x 10^4 molecules/cell). Variation of the model parameters and statistical analysis showed that Smad nuclear accumulation is most sensitive to parameters affecting the rates of RSmad phosphorylation and dephosphorylation and Smad complex formation/dissociation in the nucleus. Deleting Smad4 from the model revealed that rate-limiting phospho-R-Smad dephosphorylation could be an important mechanism for Smad nuclear accumulation. Furthermore, we observed that binding factors constitutively localised to the nucleus do not efficiently mediate Smad nuclear accumulation if dephosphorylation is rapid. We therefore conclude that an imbalance in the rates of R-Smad phosphorylation and dephosphorylation is likely an important mechanism of Smad nuclear accumulation during TGF-beta signalling.
Signaling pathways serve to communicate information about extracellular conditions into the cell, to both the nucleus and cytoplasmic processes to control cell responses. Genetic mutations in signaling network components are frequently associated with cancer and can result in cells acquiring an ability to divide and grow uncontrollably. Because signaling pathways play such a significant role in cancer initiation and advancement, their constituent proteins are attractive therapeutic targets. In this review, we discuss how signaling pathway modeling can assist with identifying effective drugs for treating diseases, such as cancer. An achievement that would facilitate the use of such models is their ability to identify controlling biochemical parameters in signaling pathways, such as molecular abundances and chemical reaction rates, because this would help determine effective points of attack by therapeutics.
Recently, we have proposed a redox molecular hypothesis about the natural biophysical substrate of visual perception and imagery (Bokkon, 2009. BioSystems; Bokkon and DAngiulli, 2009. Bioscience Hypotheses). Namely, the retina transforms external photon signals into electrical signals that are carried to the V1 (striate cortex). Then, V1 retinotopic electrical signals (spike-related electrical signals along classical axonal-dendritic pathways) can be converted into regulated ultraweak bioluminescent photons (biophotons) through redox processes within retinotopic visual neurons that make it possible to create intrinsic biophysical pictures during visual perception and imagery. However, the consensus opinion is to consider biophotons as by-products of cellular metabolism. This paper argues that biophotons are not by-products, other than originating from regulated cellular radical/redox processes. It also shows that the biophoton intensity can be considerably higher inside cells than outside. Our simple calculations, within a level of accuracy, suggest that the real biophoton intensity in retinotopic neurons may be sufficient for creating intrinsic biophysical picture representation of a single-object image during visual perception.
Intracellular recordings of neuronal membrane potential are a central tool in neurophysiology. In many situations, especially in vivo, the traditional limitation of such recordings is the high electrode resistance, which may cause significant measurement errors. We introduce a computer-aided technique, Active Electrode Compensation (AEC), based on a digital model of the electrode interfaced in real time with the electrophysiological setup. The characteristics of this model are first estimated using white noise current injection. The electrode and membrane contribution are digitally separated, and the recording is then made by online subtraction of the electrode contribution. Tests comparing AEC to other techniques demonstrate that it yields recordings with improved accuracy. It enables high-frequency recordings in demanding conditions, such as injection of conductance noise in dynamic-clamp mode, not feasible with a single high resistance electrode until now. AEC should be particularly useful to characterize fast phenomena in neurons, in vivo and in vitro.
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