Sodium potassium ATPases (Na/K pumps) mediate long-lasting, dynamic cellular memories that can last tens of seconds. The mechanisms controlling the dynamics of this type of cellular memory are not well understood and can be counterintuitive. Here, we use computational modeling to examine how Na/K pumps and the ion concentration dynamics they influence shape cellular excitability. In a Drosophila larval motor neuron model, we incorporate a Na/K pump, a dynamic intracellular Na+ concentration, and a dynamic Na+ reversal potential. We probe neuronal excitability with a variety of stimuli, including step currents, ramp currents, and zap currents, then monitor the sub- and suprathreshold voltage responses on a range of time scales. We find that the interactions of a Na+-dependent pump current with a dynamic Na+ concentration and reversal potential endow the neuron with rich response properties that are absent when the role of the pump is reduced to the maintenance of constant ion concentration gradients. In particular, these dynamic pump-Na+ interactions contribute to spike rate adaptation and result in long-lasting excitability changes after spiking and even after sub-threshold voltage fluctuations on multiple time scales. We further show that modulation of pump properties can profoundly alter a neuron’s spontaneous activity and response to stimuli by providing a mechanism for bursting oscillations. Our work has implications for experimental studies and computational modeling of the role of Na/K pumps in neuronal activity, information processing in neural circuits, and the neural control of animal behavior.
Expression of appropriate ion channels is essential to allow developing neurons to form functional networks. Our previous studies have identified LIM-homeodomain (HD) transcription factors (TFs), expressed by developing neurons, that are specifically able to regulate ion channel gene expression. In this study, we use the technique of DNA adenine methyltransferase identification (DamID) to identify putative gene targets of four such TFs that are differentially expressed in Drosophila motoneurons. Analysis of targets for Islet (Isl), Lim3, Hb9, and Even-skipped (Eve) identifies both ion channel genes and genes predicted to regulate aspects of dendritic and axonal morphology. Significantly, some ion channel genes are bound by more than one TF, consistent with the possibility of combinatorial regulation. One such gene is Shaker (Sh), which encodes a voltage-dependent fast K+ channel (Kv1.1). DamID reveals that Sh is bound by both Isl and Lim3. We used body wall muscle as a test tissue because in conditions of low Ca2+, the fast K+ current is carried solely by Sh channels (unlike neurons in which a second fast K+ current, Shal, also contributes). Ectopic expression of isl, but not Lim3, is sufficient to reduce both Sh transcript and Sh current level. By contrast, coexpression of both TFs is additive, resulting in a significantly greater reduction in both Sh transcript and current compared with isl expression alone. These observations provide evidence for combinatorial activity of Isl and Lim3 in regulating ion channel gene expression.
Activity of voltage-gated Na channels (Nav) is modified by alternative splicing. However, whether altered splicing of human Nav’s contributes to epilepsy remains to be conclusively shown. We show here that altered splicing of the Drosophila Nav (paralytic, DmNav) contributes to seizure-like behaviour in identified seizure-mutants. We focus attention on a pair of mutually-exclusive alternate exons (termed K and L), which form part of the voltage sensor (S4) in domain III of the expressed channel. The presence of exon L results in a large, non-inactivating, persistent INap. Many forms of human epilepsy are associated with an increase in this current. In wildtype (WT) Drosophila larvae ~70-80% of DmNav transcripts contain exon L, the remainder contain exon K. Splicing of DmNav to include exon L is increased to ~100% in both the slamdance and easily-shocked seizure-mutants. This change to splicing is prevented by reducing synaptic activity levels through exposure to the antiepileptic phenytoin or the inhibitory transmitter GABA. Conversely, enhancing synaptic activity in WT, by feeding of picrotoxin, is sufficient to increase INap and promote seizure through increased inclusion of exon L to 100%. We also show that the underlying activity-dependent mechanism requires the presence of Pasilla, an RNA-binding protein. Finally, we use computational modelling to show that increasing INap is sufficient to potentiate membrane excitability consistent with a seizure phenotype. Thus, increased synaptic excitation favors inclusion of exon L which, in turn, further increases neuronal excitability. Thus, at least in Drosophila, this self-reinforcing cycle may promote the incidence of seizure.
Studying ion channel currents generated distally from the recording site is difficult because of artifacts caused by poor space clamp and membrane filtering. A computational model can quantify artifact parameters for correction by simulating the currents only if their exact anatomical location is known. We propose that the same artifacts that confound current recordings can help pinpoint the source of those currents by providing a signature of the neuron’s morphology. This method can improve the recording quality of currents initiated at the spike initiation zone (SIZ) that are often distal to the soma in invertebrate neurons. Drosophila being a valuable tool for characterizing ion currents, we estimated the SIZ location and quantified artifacts in an identified motoneuron, aCC/MN1-Ib, by constructing a novel multicompartmental model. Initial simulation of the measured biophysical channel properties in an isopotential Hodgkin-Huxley type neuron model partially replicated firing characteristics. Adding a second distal compartment, which contained spike-generating Na+ and K+ currents, was sufficient to simulate aCC’s in vivo activity signature. Matching this signature using a reconstructed morphology predicted that the SIZ is on aCC’s primary axon, 70 μm after the most distal dendritic branching point. From SIZ to soma, we observed and quantified selective morphological filtering of fast activating currents. Non-inactivating K+ currents are filtered ∼3 times less and despite their large magnitude at the soma they could be as distal as Na+ currents. The peak of transient component (NaT) of the voltage-activated Na+ current is also filtered more than the magnitude of slower persistent component (NaP), which can contribute to seizures. The corrected NaP/NaT ratio explains the previously observed discrepancy when the same channel is expressed in different cells. In summary, we used an in vivo signature to estimate ion channel location and recording artifacts, which can be applied to other neurons.
The function of brain networks is highly dependent on the dynamical properties of single neurons, whose activity ranges from complex spontaneous activity patterns such as oscillations and bursting, to a variety of synaptic response patterns serving functions such as coincidence detection or rebound firing. These dynamical properties vary in time through modulation and plasticity, and are also heterogeneous across individual neurons of the same type. Commonly, neurons show two to five-fold variability in the density of voltage-gated conductances, which accounts for large variations in dynamical behavior.