Phenomenological models of NaV1.5. A side by side, procedural, hands-on comparison between Hodgkin-Huxley and kinetic formalisms

Genetically engineered HEK cells as a valuable tool for studying electroporation in excitable cells

Electric pulses used in electroporation-based treatments have been shown to affect the excitability of muscle and neuronal cells. However, understanding the interplay between electroporation and electrophysiological response of excitable cells is complex, since both ion channel gating and electroporation depend on dynamic changes in the transmembrane voltage (TMV). In this study, a genetically engineered human embryonic kidney cells expressing NaV1.5 and Kir2.1, a minimal complementary channels required for excitability (named S-HEK), was characterized as a simple cell model used for studying the effects of electroporation in excitable cells. S-HEK cells and their non-excitable counterparts (NS-HEK) were exposed to 100 µs pulses of increasing electric field strength. Changes in TMV, plasma membrane permeability, and intracellular Ca2+ were monitored with fluorescence microscopy. We found that a very mild electroporation, undetectable with the classical propidium assay but associated with a transient increase in intracellular Ca2+, can already have a profound effect on excitability close to the electrostimulation threshold, as corroborated by multiscale computational modelling. These results are of great relevance for understanding the effects of pulse delivery on cell excitability observed in context of the rapidly developing cardiac pulsed field ablation as well as other electroporation-based treatments in excitable tissues.

SKCa- and Kv1-type potassium channels and cancer: Promising therapeutic targets?

Ion channels are transmembrane structures that allow the passage of ions across cell membranes such as the plasma membrane or the membranes of various organelles like the nucleus, endoplasmic reticulum, Golgi apparatus or mitochondria. Aberrant expression of various ion channels has been demonstrated in several tumor cells, leading to the promotion of key functions in tumor development, such as cell proliferation, resistance to apoptosis, angiogenesis, invasion and metastasis. The link between ion channels and these key biological functions that promote tumor development has led to the classification of cancers as oncochannelopathies. Among all ion channels, the most varied and numerous, forming the largest family, are the potassium channels, with over 70 genes encoding them in humans. In this context, this review will provide a non-exhaustive overview of the role of plasma membrane potassium channels in cancer, describing 1) the nomenclature and structure of potassium channels, 2) the role of these channels in the control of biological functions that promotes tumor development such as proliferation, migration and cell death, and 3) the role of two particular classes of potassium channels, the SKCa- and Kv1- type potassium channels in cancer progression.

Ion Channel Modeling beyond State of the Art: A Comparison with a System Theory-Based Model of the Shaker-Related Voltage-Gated Potassium Channel Kv1.1

The mathematical modeling of ion channel kinetics is an important tool for studying the electrophysiological mechanisms of the nerves, heart, or cancer, from a single cell to an organ. Common approaches use either a Hodgkin-Huxley (HH) or a hidden Markov model (HMM) description, depending on the level of detail of the functionality and structural changes of the underlying channel gating, and taking into account the computational effort for model simulations. Here, we introduce for the first time a novel system theory-based approach for ion channel modeling based on the concept of transfer function characterization, without a priori knowledge of the biological system, using patch clamp measurements. Using the shaker-related voltage-gated potassium channel Kv1.1 (KCNA1) as an example, we compare the established approaches, HH and HMM, with the system theory-based concept in terms of model accuracy, computational effort, the degree of electrophysiological interpretability, and methodological limitations. This highly data-driven modeling concept offers a new opportunity for the phenomenological kinetic modeling of ion channels, exhibiting exceptional accuracy and computational efficiency compared to the conventional methods. The method has a high potential to further improve the quality and computational performance of complex cell and organ model simulations, and could provide a valuable new tool in the field of next-generation in silico electrophysiology.