利用计算建模解决电压钳实验中的伪影:快速钠电流记录的应用

Chon Lok Lei, Alexander P Clark, Michael Clerx, Siyu Wei, Meye Bloothooft, Teun P de Boer, David J Christini, Trine Krogh-Madsen, Gary R Mirams
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引用次数: 0

摘要

细胞电生理学是许多领域的基础,从神经学、心脏病学、肿瘤学等基础科学到药物安全性测试、临床表型等安全关键应用。膜片钳电压钳是研究细胞电生理学的黄金标准技术。然而,这些实验的质量并不总是透明的,这可能会导致研究和应用得出错误的结论。在这里,我们开发了一种新的计算方法,可以解释和预测电压钳实验中的实验伪影。计算模型捕捉了实验过程及其不足之处,包括:电压偏移、串联电阻、膜电容和(不完善的)放大器补偿,如串联电阻补偿和增压。计算模型通过一系列电模型电池实验进行了验证。利用这种计算方法,通过将观察到的电流与模拟膜电压耦合,包括记录电流中一些典型观察到的偏移和延迟,能够解决和解释电压钳制实验中心脏快速钠电流(最具挑战性的电流之一)的伪像问题。我们进一步证明,对电流-电压关系进行数据平均的典型方法会导致峰值电流的偏差和峰值电压的偏移,这种偏差的数量级与报告的致病突变差异的数量级相同。因此,所介绍的新计算管道将为评估电压钳实验和解释实验数据提供新的标准,从而可能纠正和更好地理解离子通道突变及其他相关应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Resolving artefacts in voltage-clamp experiments with computational modelling: an application to fast sodium current recordings
Cellular electrophysiology is the foundation of many fields, from basic science in neurology, cardiology, oncology to safety critical applications for drug safety testing, clinical phenotyping, etc. Patch-clamp voltage clamp is the gold standard technique for studying cellular electrophysiology. Yet, the quality of these experiments is not always transparent, which may lead to erroneous conclusions for studies and applications. Here, we have developed a new computational approach that allows us to explain and predict the experimental artefacts in voltage-clamp experiments. The computational model captures the experimental procedure and its inadequacies, including: voltage offset, series resistance, membrane capacitance and (imperfect) amplifier compensations, such as series resistance compensation and supercharging. The computational model was validated through a series of electrical model cell experiments. Using this computational approach, the artefacts in voltage-clamp experiments of cardiac fast sodium current, one of the most challenging currents to voltage clamp, were able to be resolved and explained through coupling the observed current and the simulated membrane voltage, including some typically observed shifts and delays in the recorded currents. We further demonstrated that the typical way of averaging data for current-voltage relationships would lead to biases in the peak current and shifts in the peak voltage, and such biases can be in the same order of magnitude as those differences reported for disease-causing mutations. Therefore, the presented new computational pipeline will provide a new standard of assessing the voltage-clamp experiments and interpreting the experimental data, which may be able to rectify and provide a better understanding of ion channel mutations and other related applications.
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