Abstract
The ultrarapid delayed rectifier K+ current (IKur), mediated by Kv1.5 channels, constitutes a key component of the atrial action potential. Functional mutations in the underlying KCNA5 gene have been shown to cause hereditary forms of atrial fibrillation (AF). Here, we combine targeted genetic engineering with cardiac subtype-specific differentiation of human induced pluripotent stem cells (hiPSCs) to explore the role of Kv1.5 in atrial hiPSC-cardiomyocytes. CRISPR/Cas9-mediated mutagenesis of integration-free hiPSCs was employed to generate a functional KCNA5 knockout. This model as well as isogenic wild-type control hiPSCs could selectively be differentiated into ventricular or atrial cardiomyocytes at high efficiency, based on the specific manipulation of retinoic acid signaling. Investigation of electrophysiological properties in Kv1.5-deficient cardiomyocytes compared to isogenic controls revealed a strictly atrial-specific disease phentoype, characterized by cardiac subtype-specific field and action potential prolongation and loss of 4-aminopyridine sensitivity. Atrial Kv1.5-deficient cardiomyocytes did not show signs of arrhythmia under adrenergic stress conditions or upon inhibiting additional types of K+ current. Exposure of bulk cultures to carbachol lowered beating frequencies and promoted chaotic spontaneous beating in a stochastic manner. Low-frequency, electrical stimulation in single cells caused atrial and mutant-specific early afterdepolarizations, linking the loss of KCNA5 function to a putative trigger mechanism in familial AF. These results clarify for the first time the role of Kv1.5 in atrial hiPSC-cardiomyocytes and demonstrate the feasibility of cardiac subtype-specific disease modeling using engineered hiPSCs.
Introduction
Atrial fibrillation (AF) constitutes the most prevalent cardiac arrhythmia and accounts for about one third of all hospitalizations related to heart rhythm disturbances (Fuster et al., ). Although not lethal per se, persistent uncoordinated atrial activation may lead to remodeling and deterioration of atrial function, which is associated with a reduced quality of life and increased long-term risk of stroke and overall mortality (Wolf et al., ). The prevalence of AF is in the range of 1% in the general population and tightly increasing with age, thereby imposing a substantial and steadily rising burden on society (Kannel and Benjamin, ). Current treatment options are limited, however, and mostly centered around controlling risk scores for stroke and adverse symptoms associated with AF (Fabritz et al., ).
AF frequently develops secondary to other conditions such as hypertension and other cardiovascular diseases (Schotten et al., ). However, a substantial proportion of AF patients displays no history of AF-associated disorders, which also suggests a hereditary component (lone AF) (Fuster et al., ). Indeed, a familial history of AF has been associated with a 40% risk increase for developing it and over the last years, a number of AF-related gene loci and mutations have been identified (Lubitz et al., ; Hucker et al., ). These comprise several developmental regulators such as PITX2 as well as ion channel genes involved in cardiac action potential (AP) generation, suggesting a direct causative role of the latter group (Kirchhof et al., ; Christophersen and Ellinor, ).
Channelopathies in particular are amenable to disease modeling using patient-derived or genetically engineered human induced pluripotent stem cells (hiPSCs), as they tend to mediate relevant phenotypes in a cell-automomous manner (Zhang et al., ; Bezzerides et al., ; Malan et al., ). Hence, despite the fact that AF penetrance and progression is undoubtedly linked to the organismal context, hiPSC-based AF models may allow for investigating disease phenotypes and drug responses at the cellular and tissue levels. However, most hiPSC-derived cardiomyocytes (CMs) tend to acquire a ventricular rather than an atrial fate, which has until now hampered efforts to explore aspects of AF using the hiPSC system. Interestingly, this methodological hurdle has recently been overcome through manipulation of retinoic acid (RA) signaling, a physiological pathway that also drives atrial specification in vivo (Zaffran et al., ; Devalla et al., ).
Given these recent technical advances, we here seek to explore the possibility of cardiac subtype-specific disease modeling with potential relevance to familial AF by focussing on the atrial-specific K+ channel Kv1.5 (encoded by KCNA5). Kv1.5 conducts the ultrarapid delayed rectifier K+ current (IKur) (Schmitt et al., ). Interestingly, both loss and gain-of-function mutations in KCNA5 have been shown to cause familial AF (Olson et al., ; Yang et al., ; Christophersen et al., ; Hayashi et al., ). This seeming paradox is explained by the fact that AF may be promoted via distinct mechanisms, namely, triggered activity and electrical reentry. While the latter tends to be favored by AP shortening, the likelihood for the former becomes increased by AP prolongation. Hence, in agreement with the widely accepted role of Kv1.5 in the repolarization of atrial CMs, a corresponding knockout model would be based on that former rationale (Schmitt et al., ). Indeed, QTc interval prolongation predisposes for arrhythmia-inducing triggering events such as early afterdepolarizations (EADs) and is considered a risk factor in particular for lone AF cohorts (Johnson et al., ; Nielsen et al., ).
In this context, we here report an isogenic KCNA5 knockout model in hiPSCs-CMs, to investigate basic as well drug-induced phenotypes in a cardiac subtype-specific manner.
Materials and methods
Generation, characterization, and genetic engineering of hiPSCs
Wild-type hiPSCs were derived from fibroblasts of pooled fetal livers originally isolated in 2006 (a gift by Dr. Tobias Cantz, Hannover Medical School). These were expanded in 10% serum/Knockout™ DMEM (Thermo)/1 x penicillin/streptomycin/glutamine (PSG, Thermo), replated at 100,000 cells per well of a 12-well plate, and transfected next day using 4 μl Ribojuice (Merck) and 1 μg of self-replicating RNA containing reading frames for OCT4, SOX2, KLF4, and GLIS1 (Addgene plasmid #58974). Reprogramming RNA was generated as previously described (Yoshioka et al., ), using a RiboMAX T7 in vitro transcription kit (Promega) on linearized plasmid DNA, and Cellscript kits #C-SCCE0610, #C-SCMT0610, and #CPAP5104H for RNA capping, 2′-O-Methylation, and PolyA tailing, respectively. Reprogramming medium contained 100 ng/ml B18R protein (eBioscience), 0.5 μg/ml puromycin (for 3 days, then 0.1 μg/ml), 0.5 mM valproic acid, and 5 μM EPZ004777 (Tocris). hPSC-like colonies emerging several weeks later were picked and expanded under hiPSC maintenance conditions (see below). A selected, newly generated hiPSC line termed F1 was characterized using a panel of assays which have been described elsewhere (Greber et al., ). Karyotyping was performed according to standard procedures (n = 10). Primers for RT-qPCR and bisulfite sequencing are given in Table S2.
For KCNA5 mutagenesis, a “4n” CRISPR approach targeting the 5′ end of the KCNA5 coding sequence was employed, using 4 CRISPR/Cas9n nickase vectors as illustrated in Figure 1I. Fwd oligonucleotide sequences defining the gRNAs targeting this genomic region are given in Table S2. These were phosphorylated, annealed with their corresponding reverse oligos and cloned into a modified version of pX335 (Addgene plasmid #42335) carrying a GFP-puromycin selection cassette. F1 hiPSCs were co-transfected with all 4 CRISPR vectors using Fugene HD (Roche) and transiently selected for 24 h using 0.5 μg/ml puromycin, to enrich for transfected cells. Following replating of the cells at clonal dilution several days after transfection, clonal half-colonies were picked another ~2 weeks later, to be analyzed for successful mutagenesis. This was done using conventional DNA isolation and PCR spanning the target region (Table S2). CRISPR-induced genomic deletions were indicated by smaller PCR products which were subsequently cloned and sequenced (~10 TOPO clones per mutant hiPSC line, to statistically obtain sequence information on both alleles).
Figure 1
Maintenance of hiPSCs
F1 hiPSCs, the KCNA5fs/fs derivative line, and HuES6 human embryonic stem cells were routinely cultured in 6-well plates on 1:75 diluted Matrigel™ HC (Corning #354263), in FTDA medium [10]. FTDA consisted of DMEM/F12, 1 × ITS (Corning #354350), 0.1% human serum albumin (Biological Industries #05-720-1B), 1 × defined lipids (all Thermo), 1 × PSG, 10 ng/ml FGF2 (PeproTech #100-18B), 0.2 ng/ml TGFβ1 (eBioscience #34-8348-82), 50 nM Dorsomorphin (Santa Cruz #sc-200689), and 5 ng/ml Activin A (eBioscience #34-8993-85). Cells were routinely passaged as single cells or, initially, as clumps of cells. For single cell splitting, cells were grown to full confluence (until cultures seemingly appeared syncytial), digested for 15 min using Accutase™ containing 10 μM Y-27632 (R&D # 1254/50), and replated in the presence of Y-27632 at 600,000 cells per well of a 6-well plate. hiPSCs reached full confluence after about 4 days under these conditions and were subsequently harvested as above, for continuous maintenance or for the induction of differentiation. hiPSCs were kept in culture for a maximum of 30 passages. Cell lines were tested negative for mycoplasma.
Cardiac differentiation
Cardiac induction was performed under serum and serum albumin-free conditions (Zhang et al.,
Differentiating cultures typically started to display spontaneous beating after 6 (no RA) or 8 days (+RA). To allow maturation of the cultures until the preferred time-point of analysis (typically at ~2.5 weeks after the initiation of differentiation), beating monolayers were dissociated using TrypLE Select (Thermo) and replated at a ratio of ~1:4 using CM splitting medium consisting of RPMI 1640 (Thermo), 1 × ITS, 0.2% (w/v) HSA, 250 μM phospho-ascorbate, 0.008% thioglycerol, PSG, and 10 μM Y-27632. Next day, medium was replaced by CM maintenance medium consisting of KO-DMEM, 1 × ITS, 0.2% (w/v) HSA, 250 μM phospho-ascorbate, 0.008% thioglycerol, and PSG. Following CM maturation, cells were replated once again, at an appropriate ratio, onto MEA or glass surfaces for downstream analyses several days later (~3 week total).
Electrophysiological analysis on MEAs
For electrophysiological analysis on microelectrode arrays (USB-MEA256 system, Multichannel Systems), the electrode areas of plasma-cleaned 9-well MEAs were coated with 3 μl of a 1:150 diluted Matrigel/0.1% gelatin solution in KO-DMEM for ~2 h at 37°C in a humidified cell culture incubator. hiPSC-CMs were dissociated from maintenance cultures using a 10 × TrypLE Select digestion to obtain a single-cell/small aggregate suspension. Coating solution was removed from the electrode arrays to be replaced by 25,000–50,000 cells resuspended in a ~3 μl droplet of CM replating medium. CMs were allowed to attach for ~30 min. Subsequently, MEA chambers with attached cells were filled with 150 μl of CM replating medium. Next day, medium was replaced by CM maintenance medium once more. From the following day onwards, cell preparations were used for electrophysiological recordings at 37°C. Recordings of drug-treated cells were initiated after a wash-in time of about 5 min (4-AP: 1 mM, propranolol: 10 μM, isoprenaline: 10 μM, AF-DX-116: 10 μM, cisapride: 100 nM, carbachol: 0.2–0.5 mM). Wash-out recordings were performed after five media changes. Tmax and peak-to-peak finding algorithms were implemented in MC Rack software v4.5.7. Field potential durations (FPDs, QTmax intervals) and peak-to-peak (RR) intervals were averaged from five consecutive measurements of a given sample, if appropriate, and averaged between independent replicates. Data were processed in MS Excel where QTmax-like intervals were frequency-corrected using Bazett's formula: QTcmax = QTmax [ms]/(RR [s])0.5. Poincaré plots were generated from representative recordings.
Action potential measurements
For action potential (AP) measurements, culture tissues were enzymatically dissociated into single cells as described previously (Meijer van Putten et al.,
APs were recorded at 36 ± 0.2°C from single and spontaneously contracting hiPSC-CMs. Cells were superfused with solution containing (in mmol/L): 140 NaCl, 5.4 KCl, 1.8 CaCl2, 1.0 MgCl2, 5.5 glucose, 5.0 HEPES; pH 7.4 (NaOH). Patch pipettes (borosilicate glass; resistance ≈2.5 MΩ) contained (in mmol/L): 125 K-gluconate, 20 KCl, 5 NaCl, 0.44 amphotericin-B, 10 HEPES; pH 7.2 (KOH). hiPSC-CMs typically lack the inward rectifier K+ current, IK1, that limits the functional availability of Na+ current (INa) and transient outward K+ current (ITo) (Hoekstra et al.,
Immunocytochemistry, FACS, RT-qPCR
Immunofluorescence analysis was carried out according to standard procedures following paraformaldehyde fixation and permeabilization/blocking with 0.2% Triton X-100/5% FCS/2% BSA/2% glycine in PBS for 45 min. Antibodies used were anti-AFP (1:250, Sigma #A8452), ANP (1:50, R&D # AF3366), Kv1.5 (1:100, Santa Cruz #sc-377110), MLC2v (1:200, ProteinTech Group #10906-1-AP), NKX2.5 (1:200, R&D #AF2444), OCT4 (1:100, Santa Cruz #sc-5279), SMA (1:200, Sigma #C6198), SOX2 (1:200, R&D #AF2018), Troponin C (1:100, Thermo #MS-295-P), Troponin I (1:250, Santa Cruz #sc15368), βIII-Tubulin (1:2000, Covance #PRB-435P), as well as appropriate Alexa Fluor 488 or 568-conjugated secondary antibodies (Thermo). Images shown are full or cropped frames taken with a 10 or 20 × objective mounted to a Zeiss Axiovert inverted microscope.
Intracellular staining prior to FACS analysis was performed as described (Zhang et al.,
RNA was isolated using NucleoSpin RNA kits with on-column DNA digestion (Machery Nagel). Reverse transcription was performed using M-MLV reverse transcriptase (Affymetrix #78306) with oligo-dT15 priming at 42°C. Real-time PCR was carried out using validated primers in Table S2 and BioRad iTaq™ Universal SYBR Green Supermix (#172-5124) on an ABI 7500 cycler. Efficiency-validated primers used are given in Table S2. RPL37A served as housekeeping control. Data are expressed relative to an indicated control sample or, alternatively, as percentage of RPL37A abundance (100*2−ΔCt).
Statistical analysis
Unless otherwise stated, data are presented as means between biological replicates ± SEM. Statistical analysis was carried out with SigmaStat 3.5 software. Two groups were compared using unpaired t-tests or, in case of a failed normality and/or equal variance test, Mann-Whitney Rank Sum Test. In action potential measurements, normality and equal variance assumptions were tested with the Kolmogorov-Smirnov and the Levene median test, respectively. More than 2 groups were compared using One-Way ANOVA or Two-Way repeated ANOVA followed by a Student-Newman-Keuls Method post-hoc test. In case of non-normally distributed parameters, Kruskal-Wallis test followed by pairwise comparisons with Dunn's Method was performed. P < 0.05 defines statistical significance.
Results
Generation of a KCNA5 knockout hiPSC model
A previously described approach based on a self-replicating RNA vector expressing four reprogramming factors was employed to generate integration-free wild-type hiPSCs from fetal human fibroblasts (Figure 1A) (Yoshioka et al.,
Immunocytochemical analysis of spontaneously differentiated cultures indicated competency to form derivatives of all three germ layers suggesting acquired pluripotent characteristics (Figure S1B). Finally, a previously established protocol for directed differentiation along the cardiac lineage was applied revealing that CMs could be generated at high efficiency (Figure S1C, Video S1). These data suggest that F1 cells are fully reprogrammed to a pluripotent state.
The KCNA5 gene encoding Kv1.5 (Figure 1H) is composed of a single exon. Four CRISPR/Cas9 nickase vectors were designed to target the 5′ end of the open reading frame, to potentially induce frame shift-causing deletion mutations in a controlled manner. Indeed, we were able to isolate one clone showing small homozygous frame shift-causing deletions leading to a premature stop codon on both alleles (Figure 1I). This engineered cell line designated KCNA5fs/fs hence resembles the genotype of a well-documented patient case of lone AF caused by a heterozygous but dominant KCNA5 nonsense mutation, to lead to a loss of Kv1.5 function (Olson et al.,
Cardiac subtype-specific differentiation of WT and KCNA5fs/fs hiPSCs
Next, we sought to assess whether both the mutant and the wild-type (WT) control lines were capable of undergoing selective differentiation into ventricular vs. atrial-like CMs. The Zhang et al. protocol (Zhang et al.,
Figure 2

Cardiac subtype-specific differentiation of WT and KCNA5fs/fs hiPSCs. (A) Illustration of directed differentiation protocol. Retinoic acid addition (RA, 0.5 μM) during the indicated time interval was used to selectively induce an atrial differentiation fate. (B) Subtype-specific cardiac differentiation showing RA-dependent suppression of ventricular gene expression (green) and induction of atrial markers (red) both in WT and KCNA5fs/fs hiPSCs (n = 2). Note the diminished KCNA5 expression level in RA-treated mutant cardiomyocytes. (C) Immunocytochemical staining of Kv1.5 (top), atrial natruretic peptide, and ventricular-specific myosin light chain 2 (bottom). Note that the MLC2v staining appears relatively weak and diffuse due to the early time-point of analysis (2.5 week after differentiation start).
Importantly, this variant of the protocol was applicable both to WT and KCNA5fs/fs hiPSCs suggesting that the model as well as its isogenic control may efficiently be converted into the desired cardiac subtype (atrial-enriched CMs). Default ventricular-like CMs could instead serve as an important specificity control in subtype-specific disease modeling (Figure 2B). After ~1.5 weeks of maturation under CM maintenance conditions, RA untreated CMs showed MYL2 (MLC2v) expression and low atrial natriuretic peptide (ANP) abundance at the protein level, whereas the reverse pattern was obtained after RA treatment (Figure 2C, bottom). By contrast, Kv1.5 was detectable only in atrial-like WT cells and absent in KCNA5fs/fs CMs, which confirmed the homozygosity of the underlying mutation and the consistency of the differentiation methodology (Figure 2C, Figure S2B).
The primary disease phenotype in KCNA5fs/fs CMs is atrial-specific
Electrophysiological analyses on multielectrode arrays (MEAs) revealed that spontaneous beating frequencies were increased in atrial CMs as compared to ventricular ones, as expected given shorter AP durations (APDs) in the former (Figure 3A). In ventricular CMs, beat-to-beat (RR) intervals were indistinguishable between WT and KCNA5fs/fs cells. In atrial-enriched cell preparations, however, KCNA5fs/fs CMs showed slower beating frequencies than isogenic WT controls implying that Kv1.5 functionally influences atrial CM beat rates (Figure 3A, Videos S2, S3). Analysis of frequency-corrected field potential durations (QTcmax intervals, FPDs) likewise showed no difference between the cell lines under default differentiation conditions. Atrial-enriched WT CMs displayed greatly reduced (< 100 ms) QTcmax intervals as compared to ventricular WT CMs, which is expected given the lack of a plateau phase in underlying atrial APs. Compared to atrial WT cells, atrial KCNA5fs/fs CMs however showed a substantial FPD prolongation (~200 ms, Figure 3B).
Figure 3

Subtype-specific phenotype of KCNA5fs/fs hiPSC-cardiomyocytes. (A) Left: MEA-based quantification of beat-to-beat intervals in ventricular and atrial CMs (n = 3, **p < 0.01). Right panels: Representative MEA traces showing frequency differences in spontaneous beating behavior as dependent on genotype and cardiac subtype. (B) Frequency-corrected field potential durations in ventricular and atrial WT and KCNA5fs/fs hiPSC-CMs. Quantification from three independent experiments (left, ***p < 0.001) and representative MEA traces (right). Horizontal bars indicate QTmax intervals which were more accurately determined by averaging several consecutive signals. (C) Left: Representative action potential traces elicited at 1 Hz in default and RA-treated CMs using the perforated patch clamp technique. Right: Quantification of AP-related parameters from independent measurements and cell batches. *p < 0.05 WT+RA vs. WT and KCNA5fs/fs. #p < 0.05 WT+RA vs. KCNA5fs/fs+RA, **p < 0.05 KCNA5fs/fs+RA vs. WT and KCNA5fs/fs. APD, action potential duration at 20, 50, and 90% or repolarization, RMP, resting membrane potential, APA, maxiumum AP amplitude, Plateau, potential 20 ms after the AP upstroke, dV/dt, maximal upstroke velocity. (D) Frequency-dependence of APD50. *p < 0.05 WT+RA vs. WT and KCNA5fs/fs. #p < 0.05 WT+RA vs. KCNA5fs/fs+RA, **p < 0.05 KCNA5fs/fs+RA vs. WT and KCNA5fs/fs.
In agreement with these data based on bulk cultures, perforated patch clamp measurements revealed an atrial-specific phenotype of our model at single-cell level. Compared with ventricular-like CMs, APs of RA-treated cells were in general characterized by fast phase-1 repolarization resulting in short APs with a negative plateau phase (Figure 3C). APs in atrial KCNA5fs/fs CMs, however, were significantly prolonged at 20 and 50% of repolarization and had a more positive AP plateau phase, as compared to atrial WT CMs (Figure 3C). Notably, these marked differences in atrial APDs remained conserved at various stimulation frequencies (Figure 3D). By contrast, APDs in ventricular-enriched cultures did not differ significantly between the WT and KCNA5fs/fs CMs. Furthermore, there was no marked difference in AP amplitudes, plateau, or upstroke velocities between the groups (Figure 3C). These data indicate the functional importance of Kv1.5 in shaping the atrial action potential in the hPSC system and reveal a pronounced cardiac subtype-specific phenotype in the disease model.
To affirm that this primary phenotype is indeed due to the loss of Kv1.5 in atrial KCNA5fs/fs CMs, we next evaluated the effects of 4-aminopyridine (4-AP), an inhibitor of Kv1.5 (Devalla et al.,
Figure 4

Atrial and WT-specific response to a Kv1.5 channel blocker. (A) Quantification of field potential durations in response to 4-aminopyridine (4-AP, 1 mM, n = 3). Note the lack of response in atrial KCNA5fs/fs hiPSC-CMs. **p < 0.01. (B) Representative action potential traces at 1 Hz highlighting a specific 4-AP (50 μM) response exclusively in atrial WT CMs.
KCNA5fs/fs-specific drug responses
A patient-specific KCNA5 nonsense mutation has previously been shown to increase vulnerability for triggered activity under adrenergic stress conditions (Olson et al.,
To challenge the model in an alternative manner, we next used carbachol, a cholinergic agonist promoting the acethylcholine-sensitive K+ current (IKACh). Although this type of treatment might seem counterintuitive in the context of a KCNA5 mutation, carbachol administration presents an accepted means of inducing AF in animal models (Kovoor et al.,
Figure 5

KCNA5fs/fs-specific irregularities in spontaneous beating and action potential firing at low stimulation frequency. (A) Effects of carbachol stimulation on atrial WT and KCNA5fs/fs hiPSC-CMs. Representative MEA recordings (top) and corresponding Poincaré plots (bottom). Carbachol-induced baseline irregularities (top middle panel) or chaotic beating (top right) was exclusive to atrial KCNA5fs/fs CMs and observed in 4 out of 8 experiments. (B) At single-cell level, atrial KCNA5fs/fs CMs were prone to develop EADs at low (0.2 Hz) stimulation frequencies, as observed in 5 out of 12 cells (right). WT controls (left) did not show any action potential irregularities (0 out of 9 cells).
Discussion
In this study, we have explored the potential of the hiPSC system for cardiac subtype-specific disease modeling. In this context, RA signaling has proven a powerful means of redirecting the cardiac differentiation cell fate from a default ventricular to an atrial-like identity (Devalla et al.,
AF is a complex disease that frequently develops secondary to other cardiac conditions and may involve specific organ-linked structures like the pulmonary veins (Schotten et al.,
Interestingly, we could stochastically observe EADs in atrial KCNA5fs/fs CMs, but never in isogenic wild-type or ventricular cells. This was confined to bradycardic conditions, i.e., low stimulation frequencies in our setting. The strict mutation dependency of these observations strongly suggests a cell autonomous cause of EADs in this Kv1.5-deficient scenario. Our finding is consistent with those of Olson et al. (Olson et al.,
Overactivation of IKACh by a gain-of-function mutation in the GNB2 gene leads to bradycardia by reduction of pacemaker function in humans, as recently shown (Stallmeyer et al.,
It is beyond doubt that AF causes are highly diverse. Nonetheless, specific mutations underlying familial AF bear the potential of recapitulating aspects of the disease using patient-derived or engineered hiPSC-CMs in isolation. Moreover, there is a chance that familial AF models may also prove useful in more general, for devising functional correction assays in drug screening paradigms, for instance. Our study provides a first hiPSC model in this context and strongly encourages efforts to generate additional models of familial AF, such as hiPSC lines carrying KCNA5 gain-of-function mutations as a next step.
In sum, we have used a combination of cardiac subtype-specific hiPSC differentiation and targeted genetic manipulation to generate a KCNA5fs/fs disease model that recapitulates clinical features of Kv1.5 deficiency. Furthermore, beyond primary phenotypes associated with the loss of Kv1.5 function, our data encourage the idea that familial AF models may be utilized for investigating triggers of the disease at the cellular level as well as for devising assays aiming at drug-mediated phenotype correction. This exciting perspective, however, will require macroscopic readouts that would indicate disease-specific irregularities in all mutant samples/cell preparations rather than merely in a stochastic fraction of these. This requirement of compatibility with functional screening paradigms hence calls for more AF-specific and potentially more reliable readouts compared with monitoring spontaneous beat rhythm abnormalities. For instance, it will be interesting in future investigation to combine hiPSC-based genetic AF models with optical or phase-mapping methodologies enabling the detection of triggered activity or spiral wave circuitries at the macroscopic level (Umapathy et al.,
Statements
Author contributions
AV and BG designed experiments. MM, IP, IM, JF, AR, AV, and BG performed experiments. MM, IP, GS, AV, and BG analyzed the data. GS, AV, and BG wrote the manuscript with input from co-authors.
Funding
This work was supported by the Chemical Genomics Centre of the Max Planck Society and the Bundesinstitut für Risikobewertung, grant 1328-539 (BG).
Acknowledgments
IP acknowledges support by the IMF (University of Münster Medical School).
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.
Supplementary material
The Supplementary Material for this article can be found online at: http://journal.frontiersin.org/article/10.3389/fphys.2017.00469/full#supplementary-material
Supplementary Figure 1Generation and differentiation of F1 hiPSCs. (A) Left: Reprogramming factor expression from polycistronic self-replicating RNA vector in freshly transfected parental fibroblasts (RT-qPCR data, n = 2). Right: Immunostaining prior to enriching the reprogramming factorexpressing fraction further by puromycin selection. (C) Embryoid body-based spontaneous differentiation of F1 hiPSCs into derivatives of the three germ layers, following EB attachment and outgrowth (3 wk). (C) Optimization of directed cardiac differentiation using F1 hiPSCs by varying the initial BMP4 stimulation dose, while keeping other signaling factor concentrations at constant standard levels. Left: FACS analysis (n = 3). Right: Immunostaining of replated CMs (< 2 wk). Later in this study, the non-CM fraction appeared to be further reduced.
Supplementary Figure 2Optimization of cardiac subtype-specific directed differentiation. (A) Titration of retinoic acid concentration applied on days 3-4 of differentiation (RT-qPCR analysis, n = 4). An RA dose of 0.5 μg/ml was sufficient to almost fully suppress ventricular gene expression in favor of maximum atrial marker induction including KCNA5. Overall pan-cardiac markers appeared to be somewhat compromised in primary differentiation cultures analyzed in these experiments but tended to recover following replating of the cells. (B) Immunostaining of replated WT and KCNA5fs/fs CMs confirming this fact and showing Kv1.5 expression exlusively in atrial WT CMs.
Supplementary Figure 3CM subtype-specific 4-AP responses. (A) Beat-to-beat intervals were only moderately affected by 4-AP in WT and KCNA5fs/fs hiPSC-cardiomyocytes, regardless of the CM subtype (n = 3). (B) Representative MEA traces of untreated (top) and Kv1.5 inhibitor-treated CMs (bottom). Note the comparatively short QTmax interval in atrial WT cells and the pronounced relative prolongation by 4- AP exclusively in this sample type.
Supplementary Figure 4Invariant drug responses between atrial WT and KCNA5fs/fs hiPSC-CMs. (A) Propranolol causes beat frequency reduction without promoting beat-to-beat variability. (B) Isoprenaline accelerates spontaneous beating without provoking arrhthmia. (C) M2 muscarinic receptor antagonist AF-DX-116 promotes a slight increase in beating frequencies of atrial WT and KCNA5fs/fs hiPSC-CMs. (D) hERG channel blocker cisapride does not affect beating behavior in atrial hiPSC-CMs.
Table S1Quantification of AP parameters in RA-treated WT (n = 5) and KCNA5fs/fs (n = 6) CMs with and without 4-AP treatment.
Table S2Oligonucleotides used in this study.
Video S1Primary monolayer of F1 hiPSC-CMs at day 9 of directed cardiac differentiation.
Video S2Replated WT CMs differentiated into an atrial-like fate via transient RA supplementation.
Video S3Replated atrial KCNA5fs/fs CMs.
References
1
BarryP. H.LynchJ. W. (1991). Liquid junction potentials and small cell effects in patch-clamp analysis. J. Membr. Biol.121, 101–117. 10.1007/BF01870526
2
BezzeridesV. J.ZhangD.PuW. T. (2016). Modeling inherited arrhythmia disorders using induced pluripotent stem cell-derived cardiomyocytes. Circ. J.81, 12–21. 10.1253/circj.CJ-16-1113
3
BingenB. O.EngelsM. C.SchalijM. J.JangsangthongW.NeshatiZ.FeolaI.et al. (2014). Light-induced termination of spiral wave arrhythmias by optogenetic engineering of atrial cardiomyocytes. Cardiovasc. Res.104, 194–205. 10.1093/cvr/cvu179
4
ChristophersenI. E.EllinorP. T. (2016). Genetics of atrial fibrillation: from families to genomes. J. Hum. Genet.61, 61–70. 10.1038/jhg.2015.44
5
ChristophersenI. E.OlesenM. S.LiangB.AndersenM. N.LarsenA. P.NielsenJ. B.et al. (2013). Genetic variation in KCNA5: impact on the atrial-specific potassium current IKur in patients with lone atrial fibrillation. Eur. Heart J.34, 1517–1525. 10.1093/eurheartj/ehs442
6
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
7
FabritzL.GuaschE.AntoniadesC.BardinetI.BenningerG.BettsT. R.et al. (2016). Expert consensus document: defining the major health modifiers causing atrial fibrillation: a roadmap to underpin personalized prevention and treatment. Nat. Rev. Cardiol.13, 230–237. 10.1038/nrcardio.2015.194
8
FrankS.ZhangM.ScholerH. R.GreberB. (2012). Small molecule-assisted, line-independent maintenance of human pluripotent stem cells in defined conditions. PLoS ONE7:e41958. 10.1371/journal.pone.0041958
9
FusterV.RydenL. E.CannomD. S.CrijnsH. J.CurtisA. B.EllenbogenK. A.et al. (2011). 2011 ACCF/AHA/HRS focused updates incorporated into the ACC/AHA/ESC 2006 guidelines for the management of patients with atrial fibrillation: a report of the American College of Cardiology Foundation/American Heart Association Task Force on Practice guidelines developed in partnership with the European Society of Cardiology and in collaboration with the European Heart Rhythm Association and the Heart rhythm society. J. Am. Coll. Cardiol.57, e101–198. 10.1016/j.jacc.2010.09.013
10
GaboritN.Le BouterS.SzutsV.VarroA.EscandeD.NattelS.et al. (2007). Regional and tissue specific transcript signatures of ion channel genes in the non-diseased human heart. J. Physiol.582(Pt 2), 675–693. 10.1113/jphysiol.2006.126714
11
GilesW. R.NobleD. (2016). Rigorous phenotyping of cardiac iPSC preparations requires knowledge of their resting potential(s). Biophys. J.110, 278–280. 10.1016/j.bpj.2015.06.070
12
GoedelA.MyI.SinneckerD.MorettiA. (2017). Perspectives and challenges of pluripotent stem cells in cardiac arrhythmia research. Curr. Cardiol. Rep.19:23. 10.1007/s11886-017-0828-z
13
GreberB.CoulonP.ZhangM.MoritzS.FrankS.Muller-MolinaA. J.et al. (2011). FGF signalling inhibits neural induction in human embryonic stem cells. EMBO J.30, 4874–4884. 10.1038/emboj.2011.407
14
HammerR.GiraldoE.SchiaviG. B.MonferiniE.LadinskyH. (1986). Binding profile of a novel cardioselective muscarine receptor antagonist, AF-DX 116, to membranes of peripheral tissues and brain in the rat. Life Sci.38, 1653–1662. 10.1016/0024-3205(86)90409-1
15
HayashiK.KonnoT.TadaH.TaniS.LiuL.FujinoN.et al. (2015). Functional characterization of rare variants implicated in susceptibility to lone atrial fibrillation. Circ. Arrhythm. Electrophysiol.8, 1095–1104. 10.1161/CIRCEP.114.002519
16
HoekstraM.MummeryC. L.WildeA. A.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
17
HuckerW. J.SainiH.LubitzS. A.EllinorP. T. (2016). Atrial fibrillation genetics: is there a practical clinical value now or in the future?Can. J. Cardiol.32, 1300–1305. 10.1016/j.cjca.2016.02.032
18
JohnsonJ. N.TesterD. J.PerryJ.SalisburyB. A.ReedC. R.AckermanM. J. (2008). Prevalence of early-onset atrial fibrillation in congenital long QT syndrome. Heart Rhythm5, 704–709. 10.1016/j.hrthm.2008.02.007
19
KannelW. B.BenjaminE. J. (2008). Status of the epidemiology of atrial fibrillation. Med. Clin. North Am.92, 17–40. 10.1016/j.mcna.2007.09.002
20
KirchhofP.KahrP. C.KaeseS.PicciniI.VokshiI.ScheldH. H.et al. (2011). PITX2c is expressed in the adult left atrium, and reducing Pitx2c expression promotes atrial fibrillation inducibility and complex changes in gene expression. Circ. Cardiovasc. Genet.4, 123–133. 10.1161/CIRCGENETICS.110.958058
21
KovoorP.WickmanK.MaguireC. T.PuW.GehrmannJ.BerulC. I.et al. (2001). Evaluation of the role of I(KACh) in atrial fibrillation using a mouse knockout model. J. Am. Coll. Cardiol.37, 2136–2143. 10.1016/S0735-1097(01)01304-3
22
LubitzS. A.YinX.FontesJ. D.MagnaniJ. W.RienstraM.PaiM.et al. (2010). Association between familial atrial fibrillation and risk of new-onset atrial fibrillation. JAMA304, 2263–2269. 10.1001/jama.2010.1690
23
MalanD.ZhangM.StallmeyerB.MullerJ.FleischmannB. K.Schulze-BahrE.et al. (2016). Human iPS cell model of type 3 long QT syndrome recapitulates drug-based phenotype correction. Basic Res. Cardiol.111:14. 10.1007/s00395-016-0530-0
24
Meijer van PuttenR. M. E.MengarelliI.GuanK.ZegersJ. G.van GinnekenA. C. G.VerkerkA. O.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
25
NielsenJ. B.GraffC.PietersenA.LindB.StruijkJ. J.OlesenM. S.et al. (2013). J-shaped association between QTc interval duration and the risk of atrial fibrillation: results from the Copenhagen ECG study. J. Am. Coll. Cardiol.61, 2557–2564. 10.1016/j.jacc.2013.03.032
26
OlsonT. M.AlekseevA. E.LiuX. K.ParkS.ZingmanL. V.BienengraeberM.et al. (2006). Kv1.5 channelopathy due to KCNA5 loss-of-function mutation causes human atrial fibrillation. Hum. Mol. Genet.15, 2185–2191. 10.1093/hmg/ddl143
27
PicciniI.RaoJ.SeebohmG.GreberB. (2015). Human pluripotent stem cell-derived cardiomyocytes: genome-wide expression profiling of long-term in vitro maturation in comparison to human heart tissue. Genom Data4, 69–72. 10.1016/j.gdata.2015.03.008
28
RampeD.RoyM. L.DennisA.BrownA. M. (1997). A mechanism for the proarrhythmic effects of cisapride (Propulsid): high affinity blockade of the human cardiac potassium channel HERG. FEBS Lett.417, 28–32. 10.1016/S0014-5793(97)01249-0
29
SchmittN.GrunnetM.OlesenS. P. (2014). Cardiac potassium channel subtypes: new roles in repolarization and arrhythmia. Physiol. Rev.94, 609–653. 10.1152/physrev.00022.2013
30
SchottenU.VerheuleS.KirchhofP.GoetteA. (2011). Pathophysiological mechanisms of atrial fibrillation: a translational appraisal. Physiol. Rev.91, 265–325. 10.1152/physrev.00031.2009
31
StallmeyerB.KußJ.KotthoffS.ZumhagenS.VowinkelK.RinnéS.et al. (2017). A mutation in the G-protein gene GNB2 causes familial sinus node and atrioventricular conduction dysfunction. Circ. Res. 120, e33–e34. 10.1161/CIRCRESAHA.116.310112
32
UmapathyK.NairK.MasseS.KrishnanS.RogersJ.NashM. P.et al. (2010). Phase mapping of cardiac fibrillation. Circ. Arrhythm. Electrophysiol.3, 105–114. 10.1161/CIRCEP.110.853804
33
WolfP. A.AbbottR. D.KannelW. B. (1991). Atrial fibrillation as an independent risk factor for stroke: the Framingham study. Stroke22, 983–988. 10.1161/01.STR.22.8.983
34
YangY.LiJ.LinX.YangY.HongK.WangL.et al. (2009). Novel KCNA5 loss-of-function mutations responsible for atrial fibrillation. J. Hum. Genet.54, 277–283. 10.1038/jhg.2009.26
35
YoshiokaN.GrosE.LiH. R.KumarS.DeaconD. C.MaronC.et al. (2013). Efficient generation of human iPSCs by a synthetic self-replicative RNA. Cell Stem Cell13, 246–254. 10.1016/j.stem.2013.06.001
36
ZaffranS.RobriniN. E.BertrandN. (2014). Retinoids and cardiac development. J. Dev. Biol.2, 50–71. 10.3390/jdb2010050
37
ZhangM.D'AnielloC.VerkerkA. O.WrobelE.FrankS.Ward-van OostwaardD.et al. (2014). Recessive cardiac phenotypes in induced pluripotent stem cell models of Jervell and Lange-Nielsen syndrome: disease mechanisms and pharmacological rescue. Proc. Natl. Acad. Sci. U.S.A.111, E5383–E5392. 10.1073/pnas.1419553111
38
ZhangM.SchulteJ. S.HeinickA.PicciniI.RaoJ.QuarantaR.et al. (2015). Universal cardiac induction of human pluripotent stem cells in two and three-dimensional formats: implications for in-vitro maturation. Stem Cells33, 1456–1469. 10.1002/stem.1964
Summary
Keywords
induced pluripotent stem cells, disease modeling, cardiac differentiation, Kv1.5, atrial fibrillation
Citation
Marczenke M, Piccini I, Mengarelli I, Fell J, Röpke A, Seebohm G, Verkerk AO and Greber B (2017) Cardiac Subtype-Specific Modeling of Kv1.5 Ion Channel Deficiency Using Human Pluripotent Stem Cells. Front. Physiol. 8:469. doi: 10.3389/fphys.2017.00469
Received
26 April 2017
Accepted
19 June 2017
Published
06 July 2017
Volume
8 - 2017
Edited by
Zhilin Qu, University of California, Los Angeles, United States
Reviewed by
Michel Puceat, Institut National de la Santé et de la Recherche Médicale (INSERM), France; Michele Miragoli, University of Parma, Italy
Updates

Check for updates
Copyright
© 2017 Marczenke, Piccini, Mengarelli, Fell, Röpke, Seebohm, Verkerk and Greber.
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: Arie O. Verkerk a.o.verkerk@amc.uva.nl
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.