Sinusoidal voltage protocols for rapid characterisation of ion channel kinetics.
Sinusoidal voltage protocols for rapid characterisation of ion channel kinetics.
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DOI：
10.1113/jp275733
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发表时间：
2018-05-15
期刊：
影响因子：
--
通讯作者：
Mirams GR
中科院分区：
文献类型：
--
作者：
Beattie KA;Hill AP;Bardenet R;Cui Y;Vandenberg JI;Gavaghan DJ;de Boer TP;Mirams GR
离子电流动力学通常由电流-电压关系、时间常数-电压关系以及随后与之相适应的数学模型表示。这些实验需要相当长的时间，这意味着它们很少在同一个细胞中进行。与传统的方波电压钳不同，我们将一个模型与一种新型的正弦和电压钳相结合，该电压钳只有8米长，S。可以在单个电池内多次执行的短程序将提供许多新的机会来测量不断变化的条件对离子电流动力学的影响。新模型很好地预测了传统方波协议下的海流，比文献模型对潜在海流的预测更好。一个新的生理相关的一系列动作电位钳下的电流被预测得非常好。短正弦协议允许模型完全适用于单个细胞，使我们能够第一次检查当前动力学中的细胞-细胞变异性。了解离子电流的作用对于预测药物和突变在不同情况下的作用至关重要，从而指导心脏、大脑和其他电生理系统的临床干预。我们预测离子电流如何对细胞电生理做出贡献的能力反过来又严重依赖于我们对离子通道动力学的表征-开放、关闭和非激活通道状态之间的电压依赖转换速率。我们提出了一种快速探索和表征离子通道动力学的新方法，以HERG钾通道为例，目的是产生离子电流的定量预测表示。我们对过量表达hERG1a的CHO细胞中由新型8秒正弦电压钳引起的电流拟合了一个数学模型。然后，该模型被用来预测同一细胞中超过5分钟的记录，以响应进一步的协议：一系列传统的方形阶跃电压钳，以及包括一组生理相关动作电位的新型电压钳。我们证明，我们可以建立预测性的细胞特异性模型，其表现优于使用来自许多不同细胞的平均数据，从而检查门控的哪些变化对当前动力学中的细胞-细胞变异性负责。我们的技术允许从单个细胞快速收集一致和高质量的数据，并产生比传统方法更具预测性的数学离子通道模型。离子电流动力学通常由电流-电压关系、时间常数-电压关系以及随后与之相适应的数学模型表示。这些实验需要相当长的时间，这意味着它们很少在同一个细胞中进行。与传统的方波电压钳不同，我们将一个模型与一种新型的正弦和电压钳相结合，该电压钳只有8米长，S。可以在单个电池内多次执行的短程序将提供许多新的机会来测量不断变化的条件对离子电流动力学的影响。新模型很好地预测了传统方波协议下的海流，比文献模型对潜在海流的预测更好。一个新的生理相关的一系列动作电位钳下的电流被预测得非常好。短正弦协议允许模型完全适用于单个细胞，使我们能够第一次检查当前动力学中的细胞-细胞变异性。
Ion current kinetics are commonly represented by current–voltage relationships, time constant–voltage relationships and subsequently mathematical models fitted to these. These experiments take substantial time, which means they are rarely performed in the same cell. Rather than traditional square‐wave voltage clamps, we fitted a model to the current evoked by a novel sum‐of‐sinusoids voltage clamp that was only 8 s long. Short protocols that can be performed multiple times within a single cell will offer many new opportunities to measure how ion current kinetics are affected by changing conditions. The new model predicts the current under traditional square‐wave protocols well, with better predictions of underlying currents than literature models. The current under a novel physiologically relevant series of action potential clamps is predicted extremely well. The short sinusoidal protocols allow a model to be fully fitted to individual cells, allowing us to examine cell–cell variability in current kinetics for the first time. Understanding the roles of ion currents is crucial to predict the action of pharmaceuticals and mutations in different scenarios, and thereby to guide clinical interventions in the heart, brain and other electrophysiological systems. Our ability to predict how ion currents contribute to cellular electrophysiology is in turn critically dependent on our characterisation of ion channel kinetics – the voltage‐dependent rates of transition between open, closed and inactivated channel states. We present a new method for rapidly exploring and characterising ion channel kinetics, applying it to the hERG potassium channel as an example, with the aim of generating a quantitatively predictive representation of the ion current. We fitted a mathematical model to currents evoked by a novel 8 second sinusoidal voltage clamp in CHO cells overexpressing hERG1a. The model was then used to predict over 5 minutes of recordings in the same cell in response to further protocols: a series of traditional square step voltage clamps, and also a novel voltage clamp comprising a collection of physiologically relevant action potentials. We demonstrate that we can make predictive cell‐specific models that outperform the use of averaged data from a number of different cells, and thereby examine which changes in gating are responsible for cell–cell variability in current kinetics. Our technique allows rapid collection of consistent and high quality data, from single cells, and produces more predictive mathematical ion channel models than traditional approaches. Ion current kinetics are commonly represented by current–voltage relationships, time constant–voltage relationships and subsequently mathematical models fitted to these. These experiments take substantial time, which means they are rarely performed in the same cell. Rather than traditional square‐wave voltage clamps, we fitted a model to the current evoked by a novel sum‐of‐sinusoids voltage clamp that was only 8 s long. Short protocols that can be performed multiple times within a single cell will offer many new opportunities to measure how ion current kinetics are affected by changing conditions. The new model predicts the current under traditional square‐wave protocols well, with better predictions of underlying currents than literature models. The current under a novel physiologically relevant series of action potential clamps is predicted extremely well. The short sinusoidal protocols allow a model to be fully fitted to individual cells, allowing us to examine cell–cell variability in current kinetics for the first time.