Computer modeling of whole-cell voltage-clamp analyses to delineate guidelines for good practice of manual and automated patch-clamp

Abstract

The patch-clamp technique and more recently the high throughput patch-clamp technique have contributed to major advances in the characterization of ion channels. However, the whole-cell voltage-clamp technique presents certain limits that need to be considered for robust data generation. One major caveat is that increasing current amplitude profoundly impacts the accuracy of the biophysical analyses of macroscopic ion currents under study. Using mathematical kinetic models of a cardiac voltage-gated sodium channel and a cardiac voltage-gated potassium channel, we demonstrated how large current amplitude and series resistance artefacts induce an undetected alteration in the actual membrane potential and affect the characterization of voltage-dependent activation and inactivation processes. We also computed how dose–response curves are hindered by high current amplitudes. This is of high interest since stable cell lines frequently demonstrating high current amplitudes are used for safety pharmacology using the high throughput patch-clamp technique. It is therefore critical to set experimental limits for current amplitude recordings to prevent inaccuracy in the characterization of channel properties or drug activity, such limits being different from one channel type to another. Based on the predictions generated by the kinetic models, we draw simple guidelines for good practice of whole-cell voltage-clamp recordings.

Leak current, even with gigaohm seals, can cause misinterpretation of stem-cell derived cardiomyocyte action potential recordings

“…While the effects of experimental artefacts in single-cell studies are well-established, consideration of them while building ion channel and action potential models has been limited (Whittaker et al, 2020). In silico studies investigating series resistance effects on voltage clamp recordings have been done in fast-activating currents, such as I Na and I to (Ebihara and Johnson, 1980; Montnach et al, 2021), but to our knowledge artefact equations have not been included in the calibration process for widely-used models of these currents — although the I Na model by Ebihara and Johnson was incorporated directly into the widely copied INa model by Luo and Rudy (1994). Recently, Lei et al (2020) demonstrated that coupling experimental artefact equations with an I Kr mechanistic model improved predictions.…”

Neural Network Differential Equations For Ion Channel Modelling

“…This flexibility enables neural networks to approximate (almost) any function, making them a powerful universal approximator. However, experimental data are generally imperfect; there are experimental artefacts in the data, for example imperfect series resistance and membrane capacitance compensations, imperfect leak correction, etc., as discussed in Marty and Neher (1995), Sherman et al (1999), Raba et al (2013), Lei et al (2020a,b), and Montnach et al (2021). Unlike (smaller) biophysical models, with limited flexibility, neural networks might easily absorb such undesired, non-biophysical artefacts into the model, hence making non-physiologicallyrelevant predictions.…”

Spliced isoforms of the cardiac Nav1.5 channel modify channel activation by distinct structural mechanisms

“…To control this large variability, a moderate correlation was identified between activation V 1/2 and peak current amplitude in all conditions where peak amplitude ranged beyond 10 nA, such that larger amplitude currents tended to be associated with more hyperpolarized activation V 1/2 values. To ensure that the reported shifts were real and not an artifact of skewed amplitude distributions ( Montnach et al, 2021 ), scatter plots in which V 1/2 values were plotted as a function of their corresponding peak current amplitude were reported. The resulting scatter distribution was then fitted with a line of regression: where V x is the predicted V 1/2 , m is the line slope, A is the maximum current amplitude, and b is the line y-intercept.…”