Computational analysis of the R85C and R85H epilepsy mutations in Na+ channel β1 subunits

Estimating neuronal conductance model parameters using dynamic action potential clamp

BACKGROUND

Parameterization of neuronal membrane conductance models relies on data acquired from current clamp (CC) or voltage clamp (VC) recordings. Although the CC approach provides key information on a neuron's firing properties, it is often difficult to disentangle the influence of multiple conductances that contribute to the excitation properties of a real neuron. Isolation of a single conductance using pharmacological agents or heterologous expression simplifies analysis but requires extensive VC evaluation to explore the complete state behavior of the channel of interest.

NEW METHOD

We present an improved parameterization approach that uses data derived from dynamic action potential clamp (DAPC) recordings to extract conductance equation parameters. We demonstrate the utility of the approach by applying it to the standard Hodgkin-Huxley conductance model although other conductance models could be easily incorporated as well.

RESULTS

Using a fully simulated setup we show that, with as few as five action potentials previously recorded in DAPC mode, sodium conductance equation parameters can be determined with average parameter errors of less than 4% while action potential firing accuracy approaches 100%. In real DAPC experiments, we show that by "training" our model with five or fewer action potentials, subsequent firing lasting for several seconds could be predicted with ˜96% mean firing rate accuracy and 94% temporal overlap accuracy.

COMPARISON WITH EXISTING METHODS

Our DAPC-based approach surpasses the accuracy of VC-based approaches for extracting conductance equation parameters with a significantly reduced temporal overhead.

CONCLUSION

DAPC-based approach will facilitate the rapid and systematic characterization of neuronal channelopathies.

The adhesion function of the sodium channel beta subunit (β1) contributes to cardiac action potential propagation

Computational modeling indicates that cardiac conduction may involve ephaptic coupling – intercellular communication involving electrochemical signaling across narrow extracellular clefts between cardiomyocytes. We hypothesized that β1(SCN1B) –mediated adhesion scaffolds trans-activating Na_V1.5 (SCN5A) channels within narrow (<30 nm) perinexal clefts adjacent to gap junctions (GJs), facilitating ephaptic coupling. Super-resolution imaging indicated preferential β1 localization at the perinexus, where it co-locates with Na_V1.5. Smart patch clamp (SPC) indicated greater sodium current density (I_Na) at perinexi, relative to non-junctional sites. A novel, rationally designed peptide, βadp1, potently and selectively inhibited β1-mediated adhesion, in electric cell-substrate impedance sensing studies. βadp1 significantly widened perinexi in guinea pig ventricles, and selectively reduced perinexal I_Na, but not whole cell I_Na, in myocyte monolayers. In optical mapping studies, βadp1 precipitated arrhythmogenic conduction slowing. In summary, β1-mediated adhesion at the perinexus facilitates action potential propagation between cardiomyocytes, and may represent a novel target for anti-arrhythmic therapies.

Ion Channels in Genetic Epilepsy: From Genes and Mechanisms to Disease-Targeted Therapies

Epilepsy is a common and serious neurologic disease with a strong genetic component. Genetic studies have identified an increasing collection of disease-causing genes. The impact of these genetic discoveries is wide reaching-from precise diagnosis and classification of syndromes to the discovery and validation of new drug targets and the development of disease-targeted therapeutic strategies. About 25% of genes identified in epilepsy encode ion channels. Much of our understanding of disease mechanisms comes from work focused on this class of protein. In this study, we review the genetic, molecular, and physiologic evidence supporting the pathogenic role of a number of different voltage- and ligand-activated ion channels in genetic epilepsy. We also review proposed disease mechanisms for each ion channel and highlight targeted therapeutic strategies.

Ion Channel Genes and Epilepsy: Functional Alteration, Pathogenic Potential, and Mechanism of Epilepsy

Ion channels are crucial in the generation and modulation of excitability in the nervous system and have been implicated in human epilepsy. Forty-one epilepsy-associated ion channel genes and their mutations are systematically reviewed. In this paper, we analyzed the genotypes, functional alterations (funotypes), and phenotypes of these mutations. Eleven genes featured loss-of-function mutations and six had gain-of-function mutations. Nine genes displayed diversified funotypes, among which a distinct funotype-phenotype correlation was found in SCN1A. These data suggest that the funotype is an essential consideration in evaluating the pathogenicity of mutations and a distinct funotype or funotype-phenotype correlation helps to define the pathogenic potential of a gene.

Network-specific mechanisms may explain the paradoxical effects of carbamazepine and phenytoin

PURPOSE

A common notion of the mechanism by which the antiepileptic drugs (AEDs) carbamazepine and phenytoin act is that they block sodium channels by binding preferentially to the inactivated state, thereby allowing normal neuronal firing while blocking ictal activity. However, these drugs have unpredictable efficacy and, in some cases, may exacerbate seizures. Previous studies have suggested that reducing sodium channel availability in the dentate gyrus (DG) paradoxically increases excitability. We used a biophysically detailed computer model of the DG to test the hypothesis that AEDs increase excitability by disproportionately reducing negative feedback mechanisms.

METHODS

We built a Markov model of sodium channel gating that reproduces responses to voltage clamp experiments in the presence of carbamazepine and phenytoin. We incorporated this validated Markov model into a biophysically realistic computer model of DG neurons and networks. Simulated drug concentrations were similar to those measured in cerebral spinal fluid in medicated patients. Single neuron models were stimulated with current injections, and networks were stimulated with perforant path synaptic input. In the network model, environmental effects were studied by introducing mossy fiber sprouting.

KEY FINDINGS

As expected, drugs reduced sodium channel availability, which in turn reduced action potential amplitude. This had only a small effect on action potential (AP) firing rate during brief (100 msec) current injections. Paradoxically, long current injections (2,500 msec) increased AP firing rates. This was caused by reduced calcium entry and consequently reduced activation of calcium activated potassium channels. It is important to note that the main determinant of drug effect was resting membrane potential (RMP) and not action potential firing rate. Binding of phenytoin and carbamazepine is slow and, thus drug effects are largely determined by the long term state of the RMP. This paradoxical AP firing increase was dependent on the unusually large calcium-activated potassium conductances expressed by DG granule cells. This predicts that drug efficacy in a given network will depend on the precise makeup of conductances in the network. RMP is expected to vary with the level of activity in the network. We simulated the effects of drugs on single shot stimulus responses in networks with mossy fiber sprouting and varied the RMP in all neurons as a model for network activity. For an RMP of -50 mV, representing an active network, drugs had no effect, or in some cases, increased excitability. Drugs had an increasingly larger inhibitory effect on network responses as RMP decreased. An important prediction is that drugs will be unable to block ictal activity invading an active network.

SIGNIFICANCE

Our key findings are that drug effects depend on both intrinsic properties of the network and its behavioral state. This may explain the paradoxical and unpredictable effects of some AEDs on seizure control in some patients.

Sodium channels and the neurobiology of epilepsy

Voltage-gated sodium channels (VGSCs) are integral membrane proteins. They are essential for normal neurologic function and are, currently, the most common recognized cause of genetic epilepsy. This review summarizes the neurobiology of VGSCs, their association with different epilepsy syndromes, and the ways in which we can experimentally interrogate their function. The most important sodium channel subunit of relevance to epilepsy is SCN1A, in which over 650 genetic variants have been discovered. SCN1A mutations are associated with a variety of epilepsy syndromes; the more severe syndromes are associated with truncation or complete loss of function of the protein. SCN2A is another important subtype associated with epilepsy syndromes, across a range of severe and less severe epilepsies. This subtype is localized primarily to excitatory neurons, and mutations have a range of functional effects on the channel. SCN8A is the other main adult subtype found in the brain and has recently emerged as an epilepsy gene, with the first human mutation discovered in a severe epilepsy syndrome. Mutations in the accessory β subunits, thought to modulate trafficking and function of the α subunits, have also been associated with epilepsy. Genome sequencing is continuing to become more affordable, and as such, the amount of incoming genetic data is continuing to increase. Current experimental approaches have struggled to keep pace with functional analysis of these mutations, and it has proved difficult to build associations between disease severity and the precise effect on channel function. These mutations have been interrogated with a range of experimental approaches, from in vitro, in vivo, to in silico. In vitro techniques will prove useful to scan mutations on a larger scale, particularly with the advance of high-throughput automated patch-clamp techniques. In vivo models enable investigation of mutation in the context of whole brains with connected networks and more closely model the human condition. In silico models can help us incorporate the impact of multiple genetic factors and investigate epistatic interactions and beyond.

Parametric computation predicts a multiplicative interaction between synaptic strength parameters that control gamma oscillations

Gamma oscillations are thought to be critical for a number of behavioral functions, they occur in many regions of the brain and through a variety of mechanisms. Fast repetitive bursting (FRB) neurons in layer 2 of the cortex are able to drive gamma oscillations over long periods of time. Even though the oscillation is driven by FRB neurons, strong feedback within the rest of the cortex must modulate properties of the oscillation such as frequency and power. We used a highly detailed model of the cortex to determine how a cohort of 33 parameters controlling synaptic drive might modulate gamma oscillation properties. We were interested in determining not just the effects of parameters individually, but we also wanted to reveal interactions between parameters beyond additive effects. To prevent a combinatorial explosion in parameter combinations that might need to be simulated, we used a fractional factorial design (FFD) that estimated the effects of individual parameters and two parameter interactions. This experiment required only 4096 model runs. We found that the largest effects on both gamma power and frequency came from a complex interaction between efficacy of synaptic connections from layer 2 inhibitory neurons to layer 2 excitatory neurons and the parameter for the reciprocal connection. As well as the effect of the individual parameters determining synaptic efficacy, there was an interaction between these parameters beyond the additive effects of the parameters alone. The magnitude of this effect was similar to that of the individual parameters, predicting that it is physiologically important in setting gamma oscillation properties.

Kinetic modeling of Nav1.7 provides insight into erythromelalgia-associated F1449V mutation

Gain-of-function mutations of the voltage-gated sodium channel (VGSC) Na(v)1.7 have been linked to human pain disorders. The mutation F1449V, located at the intracellular end of transmembrane helix S6 of domain III, induces the inherited pain syndrome erythromelalgia. A kinetic model of wild-type (WT) and F1449V Na(v)1.7 may provide a basis for predicting putative intraprotein interactions. We semiautomatically constrained a Markov model using stochastic search algorithms and whole cell patch-clamp recordings from human embryonic kidney cells transfected with Na(v)1.7 and its F1449V mutation. The best models obtained simulated known differences in action potential thresholds and firing patterns in spinal sensory neurons expressing WT and F1449V. The most suitable Markov model consisted of three closed, one open, and two inactivated states. The model predicted that the F1449V mutation shifts occupancy of the closed states closer to the open state, making it easier for the channel pore to open. It also predicted that F1449V's second inactivated state is more than four times more likely to be occupied than the equivalent state in WT at hyperpolarized potentials, although the mutation still lowered the firing threshold of action potentials. The differences between WT and F1449V were not limited to a single transition. Thus a point mutation in position F1449, while phenotypically most probably affecting the activation gate, may also modify channel functions mediated by structures in more distant areas of the channel protein.

Axon initial segment dysfunction in a mouse model of genetic epilepsy with febrile seizures plus

Febrile seizures are a common childhood seizure disorder and a defining feature of genetic epilepsy with febrile seizures plus (GEFS+), a syndrome frequently associated with Na+ channel mutations. Here, we describe the creation of a knockin mouse heterozygous for the C121W mutation of the beta1 Na+ channel accessory subunit seen in patients with GEFS+. Heterozygous mice with increased core temperature displayed behavioral arrest and were more susceptible to thermal challenge than wild-type mice. Wild-type beta1 was most concentrated in the membrane of axon initial segments (AIS) of pyramidal neurons, while the beta1(C121W) mutant subunit was excluded from AIS membranes. In addition, AIS function, an indicator of neuronal excitability, was substantially enhanced in hippocampal pyramidal neurons of the heterozygous mouse specifically at higher temperatures. Computational modeling predicted that this enhanced excitability was caused by hyperpolarized voltage activation of AIS Na+ channels. This heat-sensitive increased neuronal excitability presumably contributed to the heightened thermal seizure susceptibility and epileptiform discharges seen in patients and mice with beta1(C121W) subunits. We therefore conclude that Na+ channel beta1 subunits modulate AIS excitability and that epilepsy can arise if this modulation is impaired.

Generalized epilepsy with febrile seizures plus-associated sodium channel beta1 subunit mutations severely reduce beta subunit-mediated modulation of sodium channel function

Two novel mutations (R85C and R85H) on the extracellular immunoglobulin-like domain of the sodium channel beta1 subunit have been identified in individuals from two families with generalized epilepsy with febrile seizures plus (GEFS+). The functional consequences of these two mutations were determined by co-expression of the human brain NaV1.2 alpha subunit with wild type or mutant beta1 subunits in human embryonic kidney (HEK)-293T cells. Patch clamp studies confirmed the regulatory role of beta1 in that relative to NaV1.2 alone the NaV1.2+beta1 currents had right-shifted voltage dependence of activation, fast and slow inactivation and reduced use dependence. In addition, the NaV1.2+beta1 current entered fast inactivation slightly faster than NaV1.2 channels alone. The beta1(R85C) subunit appears to be a complete loss of function in that none of the modulating effects of the wild type beta1 were observed when it was co-expressed with NaV1.2. Interestingly, the beta1(R85H) subunit also failed to modulate fast kinetics, however, it shifted the voltage dependence of steady state slow inactivation in the same way as the wild type beta1 subunit. Immunohistochemical studies revealed cell surface expression of the wild type beta1 subunit and undetectable levels of cell surface expression for both mutants. The functional studies suggest association of the beta1(R85H) subunit with the alpha subunit where its influence is limited to modulating steady state slow inactivation. In summary, the mutant beta1 subunits essentially fail to modulate alpha subunits which could increase neuronal excitability and underlie GEFS+ pathogenesis.

A childhood epilepsy mutation reveals a role for developmentally regulated splicing of a sodium channel

Seizure susceptibility is high in human infants compared to adults, presumably because of developmentally regulated changes in neural excitability. Benign familial neonatal-infantile seizures (BFNIS), characterized by both early onset and remission, are caused by mutations in the gene encoding a human sodium channel (NaV1.2). We analyzed neonatal and adult splice forms of NaV1.2 with a BFNIS mutation (L1563V) in human embryonic kidney cells. Computer modeling revealed that neonatal channels are less excitable than adult channels. Introduction of the mutation increased excitability in the neonatal channels to a level similar to adult channels. By contrast, the mutation did not affect the adult channel variant. This "adult-like" increased excitability is likely to be the mechanism underlying BFNIS in infants with this mutation. More generally, developmentally regulated NaV1.2 splicing may be one mechanism that counters the normally high excitability of neonatal neurons and helps to reduce seizure susceptibility in normal human infants.