Conductivity noise in transmembrane ion channels due to ion concentration fluctuations via diffusion

Light-Nucleotide versus Ion-Nucleotide Interactions for Single-Nucleotide Resolution

Several parallel reads of ionic currents through multiple CsgG nanopores provide information about ion-nucleotide interactions for sequencing single-stranded DNA (ss-DNA) using base-calling algorithms. However, the information in ion-nucleotide interactions seems insufficient for single-read nanopore DNA sequencing. Here we report discriminative light-nucleotide interactions calculated from density functional theory (DFT), which are compared with ionic currents obtained from molecular dynamics (MD) simulations. The MD simulations were performed on a system containing a transverse nanochannel and a longitudinal solid state nanopore. We show that both of the transverse and longitudinal ionic currents during the translocation of A₁₆, G₁₆, T₁₆, and C₁₆ through the nanopore, overlapped widely. On the other hand, the UV-vis and Raman spectra of different types of single nucleotides, nucleosides, and nucleobases show relatively higher resolution than the ionic currents. Light-nucleotide interactions provide better information for characterizing the nucleotides in comparison to ion-nucleotide interactions for nanopore DNA sequencing. This can be realized by using optical techniques including surface-enhanced Raman spectroscopy (SERS) or tip-enhanced Raman spectroscopy (TERS), while plasmon excitation can be used to localize light and control the rate of nucleotide flow.

Hidden Quantum Processes, Quantum Ion Channels, and 1/ fθ-Type Noise

In this letter, we perform a complete and in-depth analysis of Lorentzian noises, such as those arising from [Formula: see text] and [Formula: see text] channel kinetics, in order to identify the source of [Formula: see text]-type noise in neurological membranes. We prove that the autocovariance of Lorentzian noise depends solely on the eigenvalues (time constants) of the kinetic matrix but that the Lorentzian weighting coefficients depend entirely on the eigenvectors of this matrix. We then show that there are rotations of the kinetic eigenvectors that send any initial weights to any target weights without altering the time constants. In particular, we show there are target weights for which the resulting Lorenztian noise has an approximately [Formula: see text]-type spectrum. We justify these kinetic rotations by introducing a quantum mechanical formulation of membrane stochastics, called hidden quantum activated-measurement models, and prove that these quantum models are probabilistically indistinguishable from the classical hidden Markov models typically used for ion channel stochastics. The quantum dividend obtained by replacing classical with quantum membranes is that rotations of the Lorentzian weights become simple readjustments of the quantum state without any change to the laboratory-determined kinetic and conductance parameters. Moreover, the quantum formalism allows us to model the activation energy of a membrane, and we show that maximizing entropy under constrained activation energy yields the previous [Formula: see text]-type Lorentzian weights, in which the spectral exponent [Formula: see text] is a Lagrange multiplier for the energy constraint. Thus, we provide a plausible neurophysical mechanism by which channel and membrane kinetics can give rise to [Formula: see text]-type noise (something that has been occasionally denied in the literature), as well as a realistic and experimentally testable explanation for the numerical values of the spectral exponents. We also discuss applications of quantum membranes beyond [Formula: see text]-type -noise, including applications to animal models and possible impact on quantum foundations.

Electrodiffusion phenomena in neuroscience: a neglected companion

The emerging technological revolution in genetically encoded molecular sensors and super-resolution imaging provides neuroscientists with a pass to the real-time nano-world. On this small scale, however, classical principles of electrophysiology do not always apply. This is in large part because the nanoscopic heterogeneities in ionic concentrations and the local electric fields associated with individual ions and their movement can no longer be ignored. Here, we review basic principles of molecular electrodiffusion in the cellular environment of organized brain tissue. We argue that accurate interpretation of physiological observations on the nanoscale requires a better understanding of the underlying electrodiffusion phenomena.

Phosphorylation of rat brain purified mitochondrial Voltage-Dependent Anion Channel by c-Jun N-terminal kinase-3 modifies open-channel noise

The drift kinetic energy of ionic flow through single ion channels cause vibrations of the pore walls which are observed as open-state current fluctuations (open-channel noise) during single-channel recordings. Vibration of the pore wall leads to transitions among different conformational sub-states of the channel protein in the open-state. Open-channel noise analysis can provide important information about the different conformational sub-state transitions and how biochemical modifications of ion channels would affect their transport properties. It has been shown that c-Jun N-terminal kinase-3 (JNK3) becomes activated by phosphorylation in various neurodegenerative diseases and phosphorylates outer mitochondrion associated proteins leading to neuronal apoptosis. In our earlier work, JNK3 has been reported to phosphorylate purified rat brain mitochondrial voltage-dependent anion channel (VDAC) in vitro and modify its conductance and opening probability. In this article we have compared the open-state noise profile of the native and the JNK3 phosphorylated VDAC using Power Spectral Density vs frequency plots. Power spectral density analysis of open-state noise indicated power law with average slope value α ≈1 for native VDAC at both positive and negative voltage whereas average α value < 0.5 for JNK3 phosphorylated VDAC at both positive and negative voltage. It is proposed that 1/f¹ power law in native VDAC open-state noise arises due to coupling of ionic transport and conformational sub-states transitions in open-state and this coupling is perturbed as a result of channel phosphorylation.

Effect of finite ion sizes in an electrostatic potential distribution for a charged soft surface in contact with an electrolyte solution

We provide a theory to analyze the impact of finite ion sizes (or steric effect) in electrostatic potential distribution for a charged soft surface in contact with an electrolyte solution. The theory is based on a free energy model that appropriately accounts for the contribution of finite ion sizes as well as the structural characteristics of a soft interface, represented by a combination of a rigid surface and a fixed charge layer (FCL), with the FCL being in contact with an electrolyte solution forming an electric double layer (EDL). This FCL contains a particular kind of ion which is impermeable to the electrolyte solution, and this impermeability is quantified in terms of the corresponding Donnan potential of the "membrane" represented by the FCL-electrolyte interface. We find that consideration of the finite ion size increases the magnitude of this Donnan potential, with the extent of increase being dictated by three length scales, namely, the thickness of the FCL, the thickness of the electrolyte EDL, and the thickness of an equivalent EDL within the FCL. Such regulation of the Donnan potential strongly affects the distribution of the permeable electrolyte ions within the FCL, which in turn will have significant implications in several processes involving "soft" biological membranes.

Efficient calculation of the quasi-static electrical potential on a tetrahedral mesh and its implementation in STEPS

We describe a novel method for calculating the quasi-static electrical potential on tetrahedral meshes, which we call E-Field. The E-Field method is implemented in STEPS, which performs stochastic spatial reaction-diffusion computations in tetrahedral-based cellular geometry reconstructions. This provides a level of integration between electrical excitability and spatial molecular dynamics in realistic cellular morphology not previously achievable. Deterministic solutions are also possible. By performing the Rallpack tests we demonstrate the accuracy of the E-Field method. Efficient node ordering is an important practical consideration, and we find that a breadth-first search provides the best solutions, although principal axis ordering suffices for some geometries. We discuss potential applications and possible future directions, and predict that the E-Field implementation in STEPS will play an important role in the future of multiscale neural simulations.

Subthreshold activation of spinal motoneurones in the stretch reflex: experimental data and modeling

Responses of gastrocnemius-soleus motoneurones to stretches of the homonymous muscles were recorded intrasomatically in decerebrate cats; changes of membrane potential (MP) were evoked by smoothed trapezoid stretches of the muscles. Amplitudes of separate excitatory postsynaptic potentials (EPSPs) were defined via differences between values of MP at the end and beginning of the positive derivative waves, which were also used as basic elements in the model of the excitatory postsynaptic currents (EPSCs). EPSCs were assumed to be transformed into EPSPs by low-pass filtering properties of the somatic membrane; parameters of the filtering were firstly defined from analysis of Ia EPSP in the same cell and then were applied in model P ( m0). The model showed unsatisfactory quality in tracking slow components of MP; to overcome the disadvantage there was proposed model P ( m1) based on addition to P ( m0) the difference between two low-pass filtered signals MP and P ( m0) (the cutoff frequency 10 or 20 Hz). An overestimation of EPSPs' amplitudes was corrected in model P ( m2). The mismatch in tracking slow changes of MP was assumed to be connected with summation of a great number of low-amplitude EPSPs generated at distal dendrites; information about waveform of separate EPSPs could disappear in this process. One can speculate that slow components of membrane depolarization at least partly are linked with the persistent inward currents in dendrites; variable and, sometimes, too fast decays in EPSPs seem to reflect inhibitory synaptic influences.

Intrinsic noise in cultured hippocampal neurons: experiment and modeling

Ion channels open and close stochastically. The fluctuation of these channels represents an intrinsic source of noise that affects the input-output properties of the neuron. We combined whole-cell measurements with biophysical modeling to characterize the intrinsic stochastic and electrical properties of single neurons as observed at the soma. We measured current and voltage noise in 18 d postembryonic cultured neurons from the rat hippocampus, at various subthreshold and near-threshold holding potentials in the presence of synaptic blockers. The observed current noise increased with depolarization, as ion channels were activated, and its spectrum demonstrated generalized 1/f behavior. Exposure to TTX removed a significant contribution from Na+ channels to the noise spectrum, particularly at depolarized potentials, and the resulting spectrum was now dominated by a single Lorentzian (1/f2) component. By replacing the intracellular K+ with Cs+, we demonstrated that a major portion of the observed noise was attributable to K+ channels. We compared the measured power spectral densities to a 1-D cable model of channel fluctuations based on Markov kinetics. We found that a somatic compartment, in combination with a single equivalent cylinder, described the effective geometry from the viewpoint of the soma. Four distinct channel populations were distributed in the membrane and modeled as Lorentzian current noise sources. Using the NEURON simulation program, we summed up the contributions from the spatially distributed current noise sources and calculated the total voltage and current noise. Our quantitative model reproduces important voltage- and frequency-dependent features of the data, accounting for the 1/f behavior, as well as the effects of various blockers.

Subthreshold voltage noise of rat neocortical pyramidal neurones

Neurones are noisy elements. Noise arises from both intrinsic and extrinsic sources, and manifests itself as fluctuations in the membrane potential. These fluctuations limit the accuracy of a neurone's output but have also been suggested to play a computational role. We present a detailed study of the amplitude and spectrum of voltage noise recorded at the soma of layer IV-V pyramidal neurones in slices taken from rat neocortex. The dependence of the noise on holding potential, synaptic activity and Na+ conductance is systematically analysed. We demonstrate that voltage noise increases non-linearly as the cell depolarizes (from a standard deviation (s.d.) of 0.19 mV at -75 mV to an s.d. of 0.54 mV at -55 mV). The increase in voltage noise is accompanied by an increase in the cell impedance, due to voltage dependence of Na+ conductance. The impedance increase accounts for the majority (70%) of the voltage noise increase. The increase in voltage noise and impedance is restricted to the low-frequency range (0.2-2 Hz). At the high frequency range (5-100 Hz) the voltage noise is dominated by synaptic activity. In our slice preparation, synaptic noise has little effect on the cell impedance. A minimal model reproduces qualitatively these data. Our results imply that ion channel noise contributes significantly to membrane voltage fluctuations at the subthreshold voltage range, and that Na+ conductance plays a key role in determining the amplitude of this noise by acting as a voltage-dependent amplifier of low-frequency transients.

Fluorescence correlation spectroscopy: inception, biophysical experimentations, and prospectus

Fluorescence correlation spectroscopy examines the chemical and the photophysical dynamics of dilute molecular solutions by measurement of the dynamic optical fluctuations of the fluorescence of a few molecules, even averaging less than one molecule at a time, in open focal volumes that are usually less than a femtoliter (<10(-18) m(3)). It applies the same principles of statistical thermodynamics as does quasi-elastic light scattering. Molecular interactions, conformational changes, chemical reactions, and photophysical dynamics that are not ordinarily detectable by quasi-elastic light scattering can be analyzed by fluorescence correlation spectroscopy in cases in which molecular fluorescence changes in the dynamic range 10(-7)-10(2) s.