Entropy involved in fidelity of DNA replication

Information has an entropic character which can be analyzed within the Statistical Theory in molecular systems. R. Landauer and C.H. Bennett showed that a logical copy can be carried out in the limit of no dissipation if the computation is performed sufficiently slowly. Structural and recent single-molecule assays have provided dynamic details of polymerase machinery with insight into information processing. We introduce a rigorous characterization of Shannon Information in biomolecular systems and apply it to DNA replication in the limit of no dissipation. Specifically, we devise an equilibrium pathway in DNA replication to determine the entropy generated in copying the information from a DNA template in the absence of friction. Both the initial state, the free nucleotides randomly distributed in certain concentrations, and the final state, a polymerized strand, are mesoscopic equilibrium states for the nucleotide distribution. We use empirical stacking free energies to calculate the probabilities of incorporation of the nucleotides. The copied strand is, to first order of approximation, a state of independent and non-indentically distributed random variables for which the nucleotide that is incorporated by the polymerase at each step is dictated by the template strand, and to second order of approximation, a state of non-uniformly distributed random variables with nearest-neighbor interactions for which the recognition of secondary structure by the polymerase in the resultant double-stranded polymer determines the entropy of the replicated strand. Two incorporation mechanisms arise naturally and their biological meanings are explained. It is known that replication occurs far from equilibrium and therefore the Shannon entropy here derived represents an upper bound for replication to take place. Likewise, this entropy sets a universal lower bound for the copying fidelity in replication.Comment: 25 pages, 5 figure

The Rate of Information Transfer of Naturalistic Stimulation by Graded Potentials

We present a method to measure the rate of information transfer for any continuous signals of finite duration without assumptions. After testing the method with simulated responses, we measure the encoding performance of Calliphora photoreceptors. We find that especially for naturalistic stimulation the responses are nonlinear and noise is nonadditive, and show that adaptation mechanisms affect signal and noise differentially depending on the time scale, structure, and speed of the stimulus. Different signaling strategies for short- and long-term and dim and bright light are found for this graded system when stimulated with naturalistic light changes

Single neuron activity-dependent signal processing

Activity in a neural network can affect both the synaptic strengths and the intrinsic electrical properties of neurons within the network. Changes of the intrinsic properties can enhance, reduce or stabilize the neural excitability. One of the activity-dependent regulatory mechanisms is the afterhyperpolarization, generally due to the activation of K+ conductances and to a Na+/K+ pump. In many neurons, the afterhyperpolarization is modified after a period of spike activity. In the mechanosensory T neurons of the leech, a prolonged electrical activity produces an increase of the afterhyperpolarization. This is believed to induce conduction block of spikes in several regions of the neuron, which in turn may decrease presynaptic invasion of spikes and thereby decrease transmitter release. To explore this possibility, we developed a multicompartment model of a T neuron [1]. The model incorporated empirical data describing the geometry of the cell and activity-dependent changes of the afterhyperpolarization. Simulations indicated that at some branching points activity-dependent increases of the afterhyperpolarization reduced the number of spikes transmitted from the receptive fields to the soma and beyond. Simulations also showed that the afterhyperpolarization could modulate transmission from the soma to the synaptic terminals, suggesting that it can regulate spike conduction within the presynaptic arborizations of the neuron, contributing to the synaptic depression correlated with increases in the afterhyperpolarization. In order to investigate how the afterhyperpolarization modulatory capabilities on transmission were dependent on the axonal geometry as well as on membrane properties, we developed [2] another multicompartment model of the mechanosensory cell, representing the reduced version of the model developed in [1]. The simulations suggested that channel kinetics influence the afterhyperpolarization-dependent modulation of spike conduction through points of impedance mismatch. The processing or conductive features of neurons seems to be determined in the first instance by the channel kinetics of the membrane and secondarily by the axonal geometry and activity-dependent processes and noise. We have also showed [3] that the role of the afterhyperpolarization induced by Na+/K+ pump-activity, which consists in a slow reduction in excitability, is also involved in neuronal coding. We showed that the regulation of excitability by Na+/K+ pump-activity is necessary for the neuron to make different responses depending on the statistical context of the stimuli. We investigate the role of membrane kinetics and input conductance mismatch in the adaptation of spike bursting to stimulus statistics