Abstract
Dynamic clamp, a hybrid-computational-experimental technique that has been used to elucidate ionic mechanisms underlying cardiac electrophysiology, is emerging as a promising tool in the discovery of potential anti-arrhythmic targets and in pharmacological safety testing. Through the injection of computationally simulated conductances into isolated cardiomyocytes in a real-time continuous loop, dynamic clamp has greatly expanded the capabilities of patch clamp outside traditional static voltage and current protocols. Recent applications include fine manipulation of injected artificial conductances to identify promising drug targets in the prevention of arrhythmia and the direct testing of model-based hypotheses. Furthermore, dynamic clamp has been used to enhance existing experimental models by addressing their intrinsic limitations, which increased predictive power in identifying pro-arrhythmic pharmacological compounds. Here, we review the recent advances of the dynamic clamp technique in cardiac electrophysiology with a focus on its future role in the development of safety testing and discovery of anti-arrhythmic drugs.
Introduction
The search for successful anti-arrhythmia therapeutics is rooted in the voltage clamp and current clamp techniques, which have provided the mechanistic details behind the ionic membrane currents that compose the cardiac action potential (AP). While basic science has made great leaps in identifying and characterizing the basic factors involved in arrhythmia, the translation of these advances into successful therapies has been lackluster. Nonetheless, investigators have been using a combination of experimental and computational approaches to unravel the complex mechanisms underlying cardiac arrhythmia. Using this approach, experimental measurements, typically in single cells from mammalian hearts, are used to develop biophysically detailed mathematical models that can be scaled up to the tissue and whole-organ levels where arrhythmia occurs. Unlike experiments, computational modeling readily allows for the precise perturbation of particular parameters individually or in controlled combinations (simulating, e.g., the multifactorial nature of many disorders), but results are reliant on the accuracy of the model and its many components. The dynamic clamp technique is a merger between experimental and computational techniques that has been gaining traction as a hybrid method for elucidating arrhythmia mechanisms and possible therapeutics.
Traditional patch clamp protocols are typically static and predetermined, such as sequential voltage steps used to study membrane current dependencies. Dynamic clamp is an extension of patch clamp, where measurements from the cell are used to modify a continuously changing experimental protocol in a real-time feedback loop (Robinson and Kawai, 1993; Sharp et al., 1993). Earlier work has shown broad application—coupling of separate cardiomyocytes through an artificial gap junction (Tan and Joyner, 1990; Joyner et al., ; Spitzer et al., 1997; Verheijck et al., 1998; Zaniboni et al., 2000; Huelsing et al., ), injection of measured current from a transfected cell into a primary isolated myocyte (Berecki et al., , ), antrhomorphization of mouse cardiac APs (Ahrens-Nicklas and Christini, ; Bot et al., ), and more recently in the study of cardiomyocyte coupling to unexcitable cells (McSpadden et al., ) and fibroblasts/myofibroblasts (Nguyen et al., ; Brown et al., ). The history of dynamic clamp has been reviewed in detail elsewhere (Prinz et al., ; Wilders, 2006; Ravagli et al., 2016). Here, we focus on a specific configuration of this technique, called the dynamic model clamp (referred hereafter as dynamic clamp), where a mathematically based model of a conductance is injected to the cell in real-time. Characteristically, this mathematical model describes a specific voltage and time-dependent membrane current determined by a set of differential equations. Measured voltage of a cell in a patch clamp configuration is fed into a mathematical model at high rates, from which the calculated current is injected back into the cell (Figure 1A).
Figure 1
Central to the dynamic clamp experimental rig is the software, which acts as the interface between the patch-clamp hardware and mathematical models. Accurate and rapid sampling of the membrane potential and computation of the virtual conductance is required to mimic sufficiently a biological conductance (Bettencourt et al.,
In this review, we discuss how investigators have used the dynamic clamp technique to test theoretical drug targets, validate and improve existing cardiac mathematical models, and design assays for cardiotoxicity testing.
Investigation of arrhythmia mechanisms
Drug target identification
Dynamic clamp studies on the cardiac L-type Ca2+ current (ICaL) by Madhvani et al. identified arrhythmia mechanisms, which could potentially be targeted by anti-arrhythmic drugs (Madhvani et al.,
In rabbit ventricular myocyte exhibiting EADs, induced with either hydrogen peroxide (Figure 1B, top) or hypokalemia, they replaced native ICaL (blocked with nifedipine) with a virtual model-based ICaL, which was injected using dynamic clamp (Figure 1B, middle). The consequences of alterations in ICaL biophysical properties were investigated by manipulating the parameters underlying the modeled current. For example, shifting the half-maximal activation voltage by 5 mV abolished EADs and returned AP duration (APD) to normal values (Figure 1B, bottom). Note that H2O2 affects multiple inward currents in addition to ICaL, such as the late sodium current (Xie et al., 2009), but modification of ICaL alone was able to eliminate EADs.
The mechanistic basis for the observed behavior was established in earlier work describing a window current region between −40 and 0 mV (January and Riddle,
Using a similar approach to the ICaL studies, Altomare et al. investigated the human ether-a-go-go related gene (hERG) channel responsible for the rapid portion of the delayed rectifier K+ current (IKr) (Altomare et al.,
Dynamic clamp has also been used successfully in studies of the transient outward K+ current (Ito), where dynamic clamp was used to vary Ito conductance in ventricular (Dong et al.,
Workman et al. investigated the influence of Ito on atrial arrhythmogenesis, a topic which was unclear due to the lack of Ito specific drugs (Workman et al., 2012). Reduction of Ito through dynamic clamp revealed AP prolongation, and additional β-adrenergic stimulation evoked EADs. Ito increase or exposure to the β-blocker atenolol prevented EAD formation. This suggests Ito enhancement holds promise in arrhythmia prevention, at least in the atrium. On the other hand, the dynamic clamp study by Nguyen et al. showed that Ito enhancement potentiated EADs in rabbit ventricular myocytes with reduced repolarization reserve, i.e., the intrinsic redundancy against excessive APD (Roden, 1998). By affecting the early AP phases, Ito augmentation can alter other voltage-dependent repolarization currents, leading to decreased late repolarization reserve and increased EAD formation (Nguyen et al.,
It is important to note that the dynamic clamp technique suffers from a major limitation, i.e., the lack of ion selectivity in the current injection. Given physiological intracellular solutions contain predominantly K+, dynamic clamp of ICaL current will be carried mainly by K+, and not Ca2+. Thus, the simulated conductance—which should be Ca2+-dependent per se, is unable to trigger secondary intracellular Ca2+ release and contraction. In an attempt to compensate for this limitation, Madhvani et al. simulated the intracellular Ca2+ transient, which was then fed back into the ICaL model (Madhvani et al.,
Improvement of cardiac computational models
The Comprehensive in vitro Proarrhythmia Assay (CiPA) initiative seeks to introduce a new cardiac drug safety testing paradigm that combines in vitro drug effects on multiple ion channels, computational modeling of cardiac currents and AP, and the use of human stem-cell derived cardiomyocytes (Sager et al., 2014; Colatsky et al.,
Ravagli et al. compared two computational models of the hyperpolarization-activated funny current, If (Ravagli et al., 2016), which plays a major role in the pacemaker activity current of sinoatrial node (SAN) cells. The authors used a dynamic clamp rescue experiment, where ivabradine was used to partially block If current, and a dynamic clamp injected model current was used to rescue control behavior. They showed one model significantly outperformed the other by restoring spontaneous activity in SAN cells, identifying the more accurate mathematical formulation of their experimental data. Bartolucci et al. used this strategy to validate an optimized formulation of the IKr current (Bartolucci et al.,
Devenyi et al. used dynamic clamp to artificially scale multiple cardiac currents in guinea pig ventricular myocytes using a single whole cell model (Devenyi et al.,
These studies illustrate how dynamic clamp can be used to experimentally validate computational models, which are typically built from heterogenous data sets spanning numerous experiments, under consistent conditions. Thereafter, new data can be used to further refine the models and advance mechanistic understanding.
Drug safety testing platforms
Dynamic clamp has also been utilized in the development of new assays for assessment of drug proarrhythmic risks. The current regulatory framework used to prevent approval of drugs with the potential to induce TdP is focused on two main areas: the propensity of the drug to block the hERG channel in vitro, and whether the drug prolongs the QTc interval of the ECG. Though largely successful at preventing proarrhythmic drugs from entering the market, the approach has been criticized due to its low specificity, as hERG block and QT prolongation do not always carry torsadogenic risk (Sager et al., 2014; Colatsky et al.,
Human induced pluripotent stem cell derived cardiomyocytes (hiPSC-CMs) are being used as an alternative to traditional animal models, cell lines, and heterologous expression systems in the study of cardiac electrophysiology mechanisms and drug-induced arrhythmia. Due to the inherent difficulty in obtaining human cardiac tissue for study, hiPSC-CMs may provide an accessible source of human cell lines and includes the additional capacity to produce patient-specific lines. However, as with human embryonic stem cell derived cardiomyocytes, hiPSC-CMs exhibit an immature phenotype. These cells are stereotypically characterized by spontaneous activity, elevated maximum diastolic potentials, low maximum upstroke velocity, and highly variable APD (Hoekstra et al.,
Bett et al. implemented a dynamic clamp based approach to resolve the immaturity issue in hiPSC-CMs through the addition of a virtual IK1 current (Bett et al.,
Figure 2

Addressing the immature electrophysiological phenotype of hiPSC-CMs. General lack of the IK1 current in hiPSC-CMs plays a major role in their immature phenotype, which was compensated for through IK1 dynamic clamp. (A) Spontaneous and erratic activity is typical of hiPSC-CMs (average resting potential = −63 ± 5.8 mV, n = 21). (B) After injection of a virtual IK1 current via dynamic clamp, cells become quiescent and produce adult-like stimulated APs (average resting potential = −84 ± 0.1, n = 21). (C) When exposed to the Ca2+ agonist BayK-8644, increased Ca2+ loading terminated spontaneous AP generation. (D) Exposure of BayK-8644 along with IK1 dynamic clamp prolonged APD compared to (B). (A–D) adapted with permission (Bett et al.,
Building upon this work, Putten et al. used multiple IK1 models in their dynamic clamp experiments to examine the impact of varying degrees of rectification (Meijer van Putten et al.,
More recently, hiPSC-CM studies augmented with IK1 dynamic clamp have provided insight into cardiac abnormalities such as Brugada syndrome (Veerman et al., 2016), long QT syndrome (Rocchetti et al., 2017), and familial atrial fibrilliation (Marczenke et al.,
IK1 dynamic clamp is becoming more common to hiPSC-CM studies to reduce variability in experimental metrics, eliminate spontaneity due to elevated resting membrane potential, and yield a more physiological relevant phenotype. Verkerk et al. systematically analyzed the impact of IK1 dynamic clamp on AP characteristics in atrial and ventricular hiPSC-CMs, and provided an in-depth comparison of the methodology and experimental variability of the studies discussed above (Verkerk et al., 2017). While IK1 dynamic clamp appears to reduce the variability of most AP parameters, enthusiasm of reducing the large experimental variability of hiPSC-CMs is tempered by the observation that APD variability is not affected. However, elimination of spontaneous depolarizations allows for stimulus at static frequencies, permitting investigation into rate-dependence. More importantly, static pacing reduces beat-to-beat variability, granting a greater ability to detect AP parameter changes. Verkerk et al. also investigated the impact of different mathematical formulations of the injected IK1 current, by comparing the models used in several studies discussed previously (Bett et al.,
The low throughput of dynamic clamp is a major limitation to its use as part of a drug testing hiPSC-CM platform. Techniques to increase maturation and IK1 density, such as 3D culturing (Lemoine et al.,
In summary, dynamic clamp has been utilized in a number of exciting studies to address some of the inherent limitations of hiPSC-CMs, suggesting a promise as a component of safety pharmacology testing. Furthermore, the ability to modify the underlying mathematical models to examine channelopathies expands the capabilities of this platform.
Conclusion
By coupling mathematical models with biological experiments, dynamic clamp has provided a powerful tool in the search for potential anti-arrhythmic therapies through model-based perturbations, enhanced hiPSC-CMs as a platform for pharmacological safety testing, and used to clarify and improve mathematical models of cardiac electrophysiology. Dynamic clamp allows fine manipulation of numerous parameters like in-silico studies, but is performed in the context of experimental biology. This approach has enabled investigators to test theoretical perturbations in real-time and in live cells, and the power of this technique is represented by the broadness seen in the studies discussed here. It is expected dynamic clamp will continue to elucidate the mechanisms underlying cardiac arrhythmia and identify novel drug targets, and could evolve into a high-throughput assay, e.g., on automated patch clamp platforms to improve maturity of hiPSC-CMs.
Statements
Author contributions
FO, EG, TK-M, and DC all contributed to the planning, writing, and editing of the manuscript and figures contained herein.
Funding
This work was funded by NIH grants U01HL136297 (to DC) and R01HL131517 (to EG), and the American Heart Association (15SDG24910015 to EG).
Conflict of interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
References
1
Ahrens-NicklasR. C.ChristiniD. J. (2009). Anthropomorphizing the mouse cardiac action potential via a novel dynamic clamp method. Biophys. J.97, 2684–2692. 10.1016/j.bpj.2009.09.002
2
AltomareC.BartolucciC.SalaL.BernardiJ.MostacciuoloG.RocchettiM.et al. (2015). IKr impact on repolarization and its variability assessed by dynamic clamp. Circ. Arrhythm. Electrophysiol. 8, 1265–1275. 10.1161/CIRCEP.114.002572
3
AntzelevitchC.SicouriS.LitovskyS. H.LukasA.KrishnanS. C.DiegoJ. M. D.et al. (1991). Heterogeneity within the ventricular wall. Electrophysiology and pharmacology of epicardial, endocardial, and M cells. Circ. Res. 69, 1427–1449. 10.1161/01.RES.69.6.1427
4
Aréchiga-FigueroaI. A.Rodríguez-MartínezM.AlbaradoA.Torres-JácomeJ.Sánchez-ChapulaJ. A. (2010). Multiple effects of 4-aminopyridine on feline and rabbit sinoatrial node myocytes and multicellular preparations. Pflugers Arch. 459, 345–355. 10.1007/s00424-009-0734-3
5
BartolucciC.AltomareC.BennatiM.FuriniS.ZazaA.SeveriS. (2015). Combined action potential- and dynamic-clamp for accurate computational modelling of the cardiac IKr current. J. Mol. Cell. Cardiol.79, 187–194. 10.1016/j.yjmcc.2014.11.011
6
BereckiG.ZegersJ. G.BhuiyanZ. A.VerkerkA. O.WildersR.Van GinnekenA. C. G. (2006). Long-QT syndrome-related sodium channel mutations probed by the dynamic action potential clamp technique. J. Physiol. 570, 237–250. 10.1113/jphysiol.2005.096578
7
BereckiG.ZegersJ. G.VerkerkA. O.BhuiyanZ. A.de JongeB.VeldkampM. W.et al. (2005). HERG channel (dys)function revealed by dynamic action potential clamp technique. Biophys. J. 88, 566–578. 10.1529/biophysj.104.047290
8
BettG. C.KaplanA. D.LisA.CimatoT. R.TzanakakisE. S.ZhouQ.et al. (2013). Electronic “expression” of the inward rectifier in cardiocytes derived from human-induced pluripotent stem cells. Heart Rhythm10, 1903–1910. 10.1016/j.hrthm.2013.09.061
9
BettencourtJ. C.LillisK. P.StupinL. R.WhiteJ. A. (2008). Effects of imperfect dynamic clamp: computational and experimental results. J. Neurosci. Methods169, 282–289. 10.1016/j.jneumeth.2007.10.009
10
BotC. T.KherlopianA. R.OrtegaF. A.ChristiniD. J.Krogh-MadsenT. (2012). Rapid genetic algorithm optimization of a mouse computational model: benefits for anthropomorphization of neonatal mouse cardiomyocytes. Comput. Physiol. Med. 3:421. 10.3389/fphys.2012.00421
11
BrownT. R.Krogh-MadsenT.ChristiniD. J. (2016). Illuminating myocyte-fibroblast homotypic and heterotypic gap junction dynamics using dynamic clamp. Biophys. J. 111, 785–797. 10.1016/j.bpj.2016.06.042
12
ColatskyT.FerminiB.GintantG.PiersonJ. B.SagerP.SekinoY.et al. (2016). The comprehensive in vitro Proarrhythmia Assay (CiPA) initiative — Update on progress. J. Pharmacol. Toxicol. Methods81, 15–20. 10.1016/j.vascn.2016.06.002
13
CranefieldP. F.AronsonR. S. (1991). Torsades de pointes and early afterdepolarizations. Cardiovasc. Drugs Ther. 5, 531–537. 10.1007/BF03029780
14
DevallaH. D.SchwachV.FordJ. W.MilnesJ. T.El-HaouS.JacksonC.et al. (2015). Atrial-like cardiomyocytes from human pluripotent stem cells are a robust preclinical model for assessing atrial-selective pharmacology. EMBO Mol. Med.7, 394–410. 10.15252/emmm.201404757
15
DevenyiR. A.OrtegaF. A.GroenendaalW.Krogh-MadsenT.ChristiniD. J.SobieE. A. (2017). Differential roles of two delayed rectifier potassium currents in regulation of ventricular action potential duration and arrhythmia susceptibility. J. Physiol. 595, 2301–2317. 10.1113/JP273191
16
DongM.SunX.PrinzA. A.WangH.-S. (2006). Effect of simulated Ito on guinea pig and canine ventricular action potential morphology. Am. J. Physiol. Heart Circ. Physiol. 291, H631–H637. 10.1152/ajpheart.00084.2006
17
DongM.YanS.ChenY.NiklewskiP. J.SunX.ChenaultK.et al. (2010). Role of the transient outward current in regulating mechanical properties of canine ventricular myocytes. J. Cardiovasc. Electrophysiol. 21, 697–703. 10.1111/j.1540-8167.2009.01708.x
18
DossM. X.DiegoJ. M. D.GoodrowR. J.WuY.CordeiroJ. M.NesterenkoV. V.et al. (2012). Maximum diastolic potential of human induced pluripotent stem cell-derived cardiomyocytes depends critically on IKr. PLoS ONE7:e40288. 10.1371/journal.pone.0040288
19
GoversenB.BeckerN.Stoelzle-FeixS.ObergrussbergerA.van VeenT.FertigN.et al. (2017). A hybrid model for safety pharmacology on an automated patch clamp platform: using dynamic clamp to join iPSC-derived cardiomyocytes and simulations of IK1 ion channels in real-time. Front. Physiol.8:1094. 10.3389/fphys.2017.01094
20
HoekstraM.MummeryC. L.WildeA. A. M.BezzinaC. R.VerkerkA. O. (2012). Induced pluripotent stem cell derived cardiomyocytes as models for cardiac arrhythmias. Front. Physiol.3:346. 10.3389/fphys.2012.00346
21
HuelsingD. J.PollardA. E.SpitzerK. W. (2001). Transient outward current modulates discontinuous conduction in rabbit ventricular cell pairs. Cardiovasc. Res. 49, 779–789. 10.1016/S0008-6363(00)00300-X
22
JanuaryC. T.RiddleJ. M. (1989). Early afterdepolarizations: mechanism of induction and block. A role for L-type Ca2+ current. Circ. Res.64, 977–990. 10.1161/01.RES.64.5.977
23
JoynerR. W.SugiuraH.TanR. C. (1991). Unidirectional block between isolated rabbit ventricular cells coupled by a variable resistance. Biophys. J. 60, 1038–1045. 10.1016/S0006-3495(91)82141-5
24
KaragueuzianH. S.PezhoumanA.AngeliniM.OlceseR. (2017). Enhanced late Na and Ca currents as effective antiarrhythmic drug targets. Front. Pharmacol.8:36. 10.3389/fphar.2017.00036
25
LemoineM. D.MannhardtI.BreckwoldtK.ProndzynskiM.FlennerF.UlmerB.et al. (2017). Human iPSC-derived cardiomyocytes cultured in 3D engineered heart tissue show physiological upstroke velocity and sodium current density. Sci. Rep.7:5464. 10.1038/s41598-017-05600-w
26
LuoC. H.RudyY. (1994). A dynamic model of the cardiac ventricular action potential. I. Simulations of ionic currents and concentration changes. Circ. Res.74, 1071–1096. 10.1161/01.RES.74.6.1071
27
MadhvaniR. V.AngeliniM.XieY.PantazisA.SurianyS.BorgstromN. P.et al. (2015). Targeting the late component of the cardiac L-type Ca2+ current to suppress early afterdepolarizations. J. Gen. Physiol. 145, 395–404. 10.1085/jgp.201411288
28
MadhvaniR. V.XieY.PantazisA.GarfinkelA.QuZ.WeissJ. N.et al. (2011). Shaping a new Ca2+ conductance to suppress early afterdepolarizations in cardiac myocytes. J. Physiol. 589, 6081–6092. 10.1113/jphysiol.2011.219600
29
MarczenkeM.PicciniI.MengarelliI.FellJ.RöpkeA.SeebohmG.et al. (2017). Cardiac subtype-specific modeling of Kv1.5 ion channel deficiency using human pluripotent stem cells. Front. Physiol.8:469. 10.3389/fphys.2017.00469
30
McSpaddenL. C.NguyenH.BursacN. (2012). Size and ionic currents of unexcitable cells coupled to cardiomyocytes distinctly modulate cardiac action potential shape and pacemaking activity in micropatterned cell pairs. Circ. Arrhythm. Electrophysiol. 5, 821–830. 10.1161/CIRCEP.111.969329
31
Meijer van PuttenR. M.MengarelliI.GuanK.ZegersJ. G.GinnekenV.et al. (2015). Ion channelopathies in human induced pluripotent stem cell derived cardiomyocytes: a dynamic clamp study with virtual IK1. Front. Physiol.6:7. 10.3389/fphys.2015.00007
32
NguyenT. P.SinghN.XieY.QuZ.WeissJ. N. (2015). Repolarization reserve evolves dynamically during the cardiac action potential: effects of transient outward currents on early afterdepolarizations. Circ. Arrhythm. Electrophysiol. 8, 694–702. 10.1161/CIRCEP.114.002451
33
NguyenT. P.XieY.GarfinkelA.QuZ.WeissJ. N. (2012). Arrhythmogenic consequences of myofibroblast–myocyte coupling. Cardiovasc. Res. 93, 242–251. 10.1093/cvr/cvr292
34
OrtegaF. A.ButeraR. J.ChristiniD. J.WhiteJ. A.DorvalA. D. (2014). Dynamic clamp in cardiac and neuronal systems using RTXI, in Patch-Clamp Methods and Protocols Methods in Molecular Biology, (New York, NY: Humana Press), 327–354.
35
PatelY. A.GeorgeA.DorvalA. D.WhiteJ. A.ChristiniD. J.ButeraR. J. (2017). Hard real-time closed-loop electrophysiology with the Real-Time eXperiment Interface (RTXI). PLoS Comput. Biol. 13:e1005430. 10.1371/journal.pcbi.1005430
36
PrinzA. A.AbbottL. F.MarderE. (2004). The dynamic clamp comes of age. Trends Neurosci. 27, 218–224. 10.1016/j.tins.2004.02.004
37
RavagliE.BucchiA.BartolucciC.PainaM.BaruscottiM.DiFrancescoD.et al. (2016). Cell-specific dynamic clamp analysis of the role of funny If current in cardiac pacemaking. Prog. Biophys. Mol. Biol. 120, 50–66. 10.1016/j.pbiomolbio.2015.12.004
38
RidleyJ. M.MilnesJ. T.ZhangY. H.WitchelH. J.HancoxJ. C. (2003). Inhibition of HERG K+ current and prolongation of the guinea-pig ventricular action potential by 4-aminopyridine. J. Physiol. 549, 667–672. 10.1113/jphysiol.2003.043976
39
RobinsonH. P.KawaiN. (1993). Injection of digitally synthesized synaptic conductance transients to measure the integrative properties of neurons. J. Neurosci. Methods49, 157–165. 10.1016/0165-0270(93)90119-C
40
RocchettiM.SalaL.DreizehnterL.CrottiL.SinneckerD.MuraM.et al. (2017). Elucidating arrhythmogenic mechanisms of long-QT syndrome CALM1-F142L mutation in patient-specific induced pluripotent stem cell-derived cardiomyocytes. Cardiovasc. Res.113, 531–541. 10.1093/cvr/cvx006
41
RodenD. M. (1998). Taking the “idio” out of “idiosyncratic”: predicting torsades de pointes. Pacing Clin. Electrophysiol.21, 1029–1034. 10.1111/j.1540-8159.1998.tb00148.x
42
SagerP. T.GintantG.TurnerJ. R.PettitS.StockbridgeN. (2014). Rechanneling the cardiac proarrhythmia safety paradigm: a meeting report from the Cardiac Safety Research Consortium. Am. Heart J. 167, 292–300. 10.1016/j.ahj.2013.11.004
43
SanguinettiM. C.JurkiewiczN. K. (1990). Two components of cardiac delayed rectifier K+ current. Differential sensitivity to block by class III antiarrhythmic agents. J. Gen. Physiol.96, 195–215. 10.1085/jgp.96.1.195
44
SharpA. A.O'NeilM. B.AbbottL. F.MarderE. (1993). Dynamic clamp: computer-generated conductances in real neurons. J. Neurophysiol. 69, 992–995.
45
SpitzerK. W.SatoN.TanakaH.FirekL.ZaniboniM.GilesW. R. (1997). Electrotonic modulation of electrical activity in rabbit atrioventricular node myocytes. Am. J. Physiol. 273, H767–H776.
46
TanR. C.JoynerR. W. (1990). Electrotonic influences on action potentials from isolated ventricular cells. Circ. Res. 67, 1071–1081. 10.1161/01.RES.67.5.1071
47
VaidyanathanR.MarkandeyaY. S.KampT. J.MakielskiJ. C.JanuaryC. T.EckhardtL. L. (2016). IK1-enhanced human-induced pluripotent stem cell-derived cardiomyocytes: an improved cardiomyocyte model to investigate inherited arrhythmia syndromes. Am. J. Physiol. Heart Circ. Physiol.310, H1611–H1621. 10.1152/ajpheart.00481.2015
48
VerheijckE. E.WildersR.JoynerR. W.GolodD. A.KumarR.JongsmaH. J.et al. (1998). Pacemaker synchronization of electrically coupled rabbit sinoatrial node cells. J. Gen. Physiol. 111, 95–112. 10.1085/jgp.111.1.95
49
VeermanC. C.MengarelliI.GuanK.StauskeM.BarcJ.TanH. L.et al. (2016). hiPSC-derived cardiomyocytes from Brugada Syndrome patients without identified mutations do not exhibit clear cellular electrophysiological abnormalities. Sci. Rep.6:30967. 10.1038/srep30967
50
VerkerkA. O.VeermanC. C.ZegersJ. G.MengarelliI.BezzinaC. R.WildersR. (2017). Patch-clamp recording from human induced pluripotent stem cell-derived cardiomyocytes: improving action potential characteristics through dynamic clamp. Int. J. Mol. Sci.18:1873. 10.3390/ijms18091873
51
WangZ.YueL.WhiteM.PelletierG.NattelS. (1998). Differential distribution of inward rectifier potassium channel transcripts in human atrium versus ventricle. Circulation98, 2422–2428. 10.1161/01.CIR.98.22.2422
52
WildersR. (2006). Dynamic clamp: a powerful tool in cardiac electrophysiology. J. Physiol. 576, 349–359. 10.1113/jphysiol.2006.115840
53
WorkmanA. J.MarshallG. E.RankinA. C.SmithG. L.DempsterJ. (2012). Transient outward K+ current reduction prolongs action potentials and promotes afterdepolarisations: a dynamic-clamp study in human and rabbit cardiac atrial myocytes. J. Physiol. 590, 4289–4305. 10.1113/jphysiol.2012.235986
54
XieL. H.ChenF.KaragueuzianH. S.WeissJ. N. (2009). Oxidative stress–induced afterdepolarizations and calmodulin kinase II signaling. Circ. Res. 104, 79–86. 10.1161/CIRCRESAHA.108.183475
55
ZaniboniM.PollardA. E.YangL.SpitzerK. W. (2000). Beat-to-beat repolarization variability in ventricular myocytes and its suppression by electrical coupling. Am. J. Physiol. Heart Circ. Physiol. 278, H677–H687. 10.1152/ajpheart.2000.278.3.H677
Summary
Keywords
dynamic clamp, cardiac electrophysiology, cardiac modeling, arrhythmia mechanisms, antiarrhythmic drugs, pharmacology & drug discovery
Citation
Ortega FA, Grandi E, Krogh-Madsen T and Christini DJ (2018) Applications of Dynamic Clamp to Cardiac Arrhythmia Research: Role in Drug Target Discovery and Safety Pharmacology Testing. Front. Physiol. 8:1099. doi: 10.3389/fphys.2017.01099
Received
01 September 2017
Accepted
13 December 2017
Published
04 January 2018
Volume
8 - 2017
Edited by
Catherine Proenza, University of Colorado Denver, United States
Reviewed by
Arie O. Verkerk, University of Amsterdam, Netherlands; Andrew F. James, University of Bristol, United Kingdom; T Alexander Quinn, Dalhousie University, Canada
Updates

Check for updates
Copyright
© 2018 Ortega, Grandi, Krogh-Madsen and Christini.
This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: David J. Christini dchristi@med.cornell.edu
This article was submitted to Cardiac Electrophysiology, a section of the journal Frontiers in Physiology
Disclaimer
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.