Self-organization of signal transduction

We propose a model of parameter learning for signal transduction, where the objective function is defined by signal transmission efficiency. We apply this to learn kinetic rates as a form of evolutionary learning, and look for parameters which satisfy the objective. This is a novel approach compared to the usual technique of adjusting parameters only on the basis of experimental data. The resulting model is self-organizing, i.e. perturbations in protein concentrations or changes in extracellular signaling will automatically lead to adaptation. We systematically perturb protein concentrations and observe the response of the system. We find compensatory or co-regulation of protein expression levels. In a novel experiment, we alter the distribution of extracellular signaling, and observe adaptation based on optimizing signal transmission. We also discuss the relationship between signaling with and without transients. Signaling by transients may involve maximization of signal transmission efficiency for the peak response, but a minimization in steady-state responses. With an appropriate objective function, this can also be achieved by concentration adjustment. Self-organizing systems may be predictive of unwanted drug interference effects, since they aim to mimic complex cellular adaptation in a unified way.Comment: updated version, 13 pages, 4 figures, 3 Tables, supplemental tabl

Finite-State Channel Models for Signal Transduction in Neural Systems

Information theory provides powerful tools for understanding communication systems. This analysis can be applied to intercellular signal transduction, which is a means of chemical communication among cells and microbes. We discuss how to apply information-theoretic analysis to ligand-receptor systems, which form the signal carrier and receiver in intercellular signal transduction channels. We also discuss the applications of these results to neuroscience.Comment: Accepted for publication in 2016 IEEE International Conference on Acoustics, Speech, and Signal Processing, Shanghai, Chin

Fold-Hopf Bursting in a Model for Calcium Signal Transduction

We study a recent model for calcium signal transduction. This model displays spiking, bursting and chaotic oscillations in accordance with experimental results. We calculate bifurcation diagrams and study the bursting behaviour in detail. This behaviour is classified according to the dynamics of separated slow and fast subsystems. It is shown to be of the Fold-Hopf type, a type which was previously only described in the context of neuronal systems, but not in the context of signal transduction in the cell.Comment: 13 pages, 5 figure

Optimal length and signal amplification in weakly activated signal transduction cascades

Weakly activated signaling cascades can be modeled as linear systems. The input-to-output transfer function and the internal gain of a linear system, provide natural measures for the propagation of the input signal down the cascade and for the characterization of the final outcome. The most efficient design of a cascade for generating sharp signals, is obtained by choosing all the off rates equal, and a ``universal'' finite optimal length.Comment: 27 pages, 10 figures, LaTeX fil

Enzyme localization can drastically affect signal amplification in signal transduction pathways

Push-pull networks are ubiquitous in signal transduction pathways in both prokaryotic and eukaryotic cells. They allow cells to strongly amplify signals via the mechanism of zero-order ultrasensitivity. In a push-pull network, two antagonistic enzymes control the activity of a protein by covalent modification. These enzymes are often uniformly distributed in the cytoplasm. They can, however, also be colocalized in space, for instance, near the pole of the cell. Moreover, it is increasingly recognized that these enzymes can also be spatially separated, leading to gradients of the active form of the messenger protein. Here, we investigate the consequences of the spatial distributions of the enzymes for the amplification properties of push-pull networks. Our calculations reveal that enzyme localization by itself can have a dramatic effect on the gain. The gain is maximized when the two enzymes are either uniformly distributed or colocalized in one region in the cell. Depending on the diffusion constants, however, the sharpness of the response can be strongly reduced when the enzymes are spatially separated. We discuss how our predictions could be tested experimentally.Comment: PLoS Comp Biol, in press. 32 pages including 6 figures and supporting informatio

Ras p21 protein promotes survival and fiber outgrowth of cultured embryonic neurons

Although evidence obtained with the PC12 cell line has suggested a role for the ras oncogene proteins in the signal transduction of nerve growth factor-mediated fiber outgrowth, little is known about the signal transduction mechanisms involved in the neuronal response to neurotrophic factors in nontransformed cells. We report here that the oncogene protein T24-ras, when introduced into the cytoplasm of freshly dissociated chick embryonic neurons, promotes the in vitro survival and neurite outgrowth of nerve growth factor-responsive dorsal root ganglion neurons, brain-derived neurotrophic factor-responsive nodose ganglion neurons, and ciliary neuronotrophic factor-responsive ciliary ganglion neurons. The proto-oncogene product c-Ha-ras also promotes neuronal survival, albeit less strongly. No effect could be observed with truncated counterparts of T24-ras and c-Ha-ras lacking the 23 C-terminal amino acids including the membrane-anchoring, palmityl-accepting cysteine. These results suggest a generalized involvement of ras or ras-like proteins in the intracellular signal transduction pathway for neurotrophic factors

Capacity of a Simple Intercellular Signal Transduction Channel

We model the ligand-receptor molecular communication channel with a discrete-time Markov model, and show how to obtain the capacity of this channel. We show that the capacity-achieving input distribution is iid; further, unusually for a channel with memory, we show that feedback does not increase the capacity of this channel.Comment: 5 pages, 1 figure. To appear in the 2013 IEEE International Symposium on Information Theor