1. Medicine

Ankyrin-G mediates targeting of both Na+ and KATP channels to the rat cardiac intercalated disc

  1. Hua-Qian Yang
  2. Marta Pérez-Hernández
  3. Jose Sanchez-Alonso
  4. Andriy Shevchuk
  5. Julia Gorelik
  6. Eli Rothenberg
  7. Mario Delmar
  8. William A Coetzee  Is a corresponding author
  1. NYU School of Medicine, United States
  2. Imperial College London, United Kingdom
https://doi.org/10.7554/eLife.52373
Share this article
Cite this article
  1. Hua-Qian Yang
  2. Marta Pérez-Hernández
  3. Jose Sanchez-Alonso
  4. Andriy Shevchuk
  5. Julia Gorelik
  6. Eli Rothenberg
  7. Mario Delmar
  8. William A Coetzee
(2020)
Ankyrin-G mediates targeting of both Na+ and KATP channels to the rat cardiac intercalated disc
eLife 9:e52373.
https://doi.org/10.7554/eLife.52373
  2. Download BibTeX
  3. Download .RIS

Abstract

We investigated targeting mechanisms of Na+ and KATP channels to the intercalated disk (ICD) of cardiomyocytes. Patch clamp and surface biotinylation data show reciprocal downregulation of each other’s surface density. Mutagenesis of the Kir6.2 ankyrin binding site disrupts this functional coupling. Duplex patch clamping and Angle SICM recordings show that INa and IKATP functionally co-localize at the rat ICD, but not at the lateral membrane. Quantitative STORM imaging show that Na+ and KATP channels are localized close to each other and to AnkG, but not to AnkB, at the ICD. Peptides corresponding to Nav1.5 and Kir6.2 ankyrin binding sites dysregulate targeting of both Na+ and KATP channels to the ICD, but not to lateral membranes. Finally, a clinically relevant gene variant that disrupts KATP channel trafficking also regulates Na+ channel surface expression. The functional coupling between these two channels need to be considered when assessing clinical variants and therapeutics.

Introduction

Voltage-gated Na+ channels are responsible for the initiation and propagation of action potentials in many excitable cell types, including neurons, skeletal muscle and cardiac myocytes. The pore-forming α-subunit of the cardiac Na+ channel (Nav1.5) is encoded by the SCN5A gene. A large amount of genetic information has linked SCN5A variants to inherited forms of arrhythmias and sudden death, including Brugada syndrome, sick sinus syndrome, Long-QT syndrome and others (Veerman et al., 2015). Nav1.5 interacts with several types of proteins, including 14-3-3, Ca2+/calmodulin-dependent protein kinase II (CaMKII), Fibroblast growth factor 13 (FGF13), Ankyrin-G (AnkG) and several others (Shy et al., 2013). Mutations in these interactors are also associated with arrhythmogenic syndromes since they affect the Na+ channel (Shy et al., 2013). It is of paramount importance, therefore, to know which proteins associate with Na+ channels and how they affect Na+ channel expression and function.

The sarcolemmal ATP-sensitive K+ (KATP) channel is one of the most abundant channels expressed in cardiac myocytes and it promotes action potential shortening adaptation with elevated heart rates (Foster and Coetzee, 2016). KATP channels additionally have important protective effects during metabolic stress and hypoxia/ischemia. Studies with murine genetic models have demonstrated that sarcolemmal KATP channels mediate a key component of the protective effects of ischemic preconditioning (Foster and Coetzee, 2016). As sensors of intracellular nucleotides (ATP, MgADP and AMP), KATP channels couple alterations in energy metabolism to K+ fluxes and membrane excitability (Foster and Coetzee, 2016). Intracellular ATP blocks the channel by binding to a pocket formed by the intracellular N- and C-termini of Kir6.x, whereas ADP promotes channel opening by binding to intracellular nucleotide binding folds on the partner subunit, SURx. Two genes (KCNJ8 and KCNJ11) respectively code two distinct pore-forming Kir6.1 and Kir6.2 subunits, and two genes (ABCC8 and ABCC9) code for the accessory SUR1 and SUR2 subunits. Two major SUR2 isoforms (SUR2A and SUR2B) exist as a result of alternative mRNA splicing (Foster and Coetzee, 2016).

Despite the obvious functional differences in cardiac Na+ channels and KATP channels, there are also similarities, particularly in their subcellular expression profiles. At least two distinct pools of Na+ channels have been identified in cardiac myocytes (Shy et al., 2013). One pool is targeted to lateral membranes by the syntrophin/dystrophin complex (Gavillet et al., 2006; Hund et al., 2010), whereas another subpopulation is organized in a highly specialized macromolecular complex at the intercalated disk (ICD) region (Agullo-Pascual et al., 2014), where targeting and anchoring is coordinated by AnkG, Synapse-associated protein 97 (SAP97), Microtubule plus-end binding protein (EB1) and Plakophilin-2 (PKP2) (Shy et al., 2013; Gillet et al., 2014). KATP channel subcellular expression follows a similar trend: The presence of KATP channels in lateral membranes was established by their initial identification with patch clamp methods (Foster and Coetzee, 2016). However, as with Na+ channels, KATP channels are enriched at the ICD of cardiac myocytes where they morphologically cluster with desmosomal proteins such as PKP2 (Hong et al., 2012), suggesting that KATP channels form part of an ICD channel/transporter complex that is gaining increasing recognition for roles in cell-cell communication and cell adhesion.

It is a common theme in cardiac electrophysiology that ion channels in the same subdomain have the potential to interact with each other, as well as with other channels and transporters. Here, we provide evidence that Na+ channels and KATP channels are morphologically clustered (particularly at the ICD) and that they interact functionally, most likely due to the fact that they are targeted to a common subcellular location by AnkG. These studies provide a new paradigm when considering pharmacological and genetic aspects of arrhythmogenesis.

Results

KATP and Nav1.5 channels negatively regulate each other in HEK293 cells

Distinct subpopulations of Na+ channels and KATP channels exist in a cardiomyocyte, but the relevance of this observation has been unclear. Recent studies have shown that the function and trafficking of Na+ channels can be regulated by some K+ channels, including Kir2.1 and Kv4.3 (Portero et al., 2018; Ponce-Balbuena et al., 2018). We investigated whether an interaction exists between Na+ and KATP channels. First, we performed experiments with HEK293 cells transfected with only KATP channels (Kir6.2/SUR2A), only Na+ channels (Nav1.5), both type of channels, or with an empty vector (pcDNA3) as a negative control. Unlike Kir2.1, which positively regulates Nav1.5, we unexpectedly found that the whole-cell Na+ current density was significantly smaller when KATP channels were present (Figure 1A and B). The voltage-dependence of steady-state activation of the Na+ channel and the inactivation kinetics were unchanged by the presence of KATP channels (Figure 1C and Figure 1—figure supplement 1). We next tested whether K+ flux through KATP channels plays a role. To answer this question, we took advantage of the fact that mutating the GFG sequence in the Kir6.2 pore to AAA produces a non-functional channel that still traffics normally to the cell membrane (Tong et al., 2006). As with the wild-type channel, Kir6.2-AAA also suppressed Nav1.5 currents (Figure 1—figure supplement 2), demonstrating that a conducting KATP channel is not required. Reciprocal functional interaction occurs since the KATP channel mean patch current in excised patches were significantly reduced when Na+ channels were present (Figure 1D and E). The presence of Na+ channels did not affect the sensitivity of KATP channels to ‘cytosolic’ ATP (Figure 1F). Of note, the negative regulation of one channel by the other was not due to differences in transfection efficiency, transcription or translation since the Nav1.5 protein levels in cell lysates were unchanged in the presence of KATP channels, and co-transfection with Nav1.5 did not affect total Kir6.2 protein levels (Figure 2). Collectively, these data demonstrate that KATP channels and Na+ channels negatively regulate each other’s function when overexpressed in a heterologous expression system.

Figure 1 with 2 supplements see all
Download asset Open asset
KATP channels and Na+ channels reciprocally reduce the functional expression of one another.

(A) Representative whole-cell Na+ current recordings from Nav1.5 transfected HEK293 cells co-transfected with empty vector (pcDNA3) or KATP channel (Kir6.2+SUR2A). (B) Averaged current-voltage relationships of Nav1.5 co-expressed with empty vector (open symbols; n = 12) or Kir6.2/SUR2A (filled symbols; n = 10). *p<0.001 determined by two-way ANOVA followed by Tukey’s test. (C) The voltage dependence of steady-state activation was calculated from the traces in panel A. Values of GNa were normalized to the maximum conductance and plotted as a function of voltage. The symbols have the same meaning as in panel B. (D) Representative inside-out current recordings obtained from KATP channel (Kir6.2+SUR2A) transfected HEK293 cells co-transfected with empty vector (pcDNA3) or Nav1.5. ATP concentrations (µM) were switched as indicated. The mean patch current was recorded at a membrane potential of −80 mV (a voltage at which Nav1.5 is inactive) and the KATP channel current was defined by the current component blocked by 1 mM ATP applied to the ‘cytosolic’ face of the patch. Recordings were made immediately after patch excision to minimize effects of ‘run-down’. (E) Data points from Kir6.2/SUR2A transfected cells co-transfected with empty vector (pcDNA3) (open symbols; n = 12) or Nav1.5 (filled symbols; n = 14). *p=0.022 using the Student’s t test. (F) The ATP-sensitivity of KATP channels was determined by plotting the KATP current (normalized to the maximum current) as a function of the ‘cytosolic’ ATP concentration. Data from individual patches were subjected to curve fitting to a modified Boltzmann equation, yielding IC50 values for ATP inhibition of 63.0 ± 9.5 µM and 66.2 ± 10.6 µM respectively for Kir6.2/SUR2A without and with Nav1.5. Data are from a minimum of 3 separate transfections.

Figure 2
Download asset Open asset
KATP channels and Na+ channels reciprocally reduce the surface expression of each other.

HEK-293 cells were transfected with combinations of Kir6.2 (C-terminal tagged with 6 × myc epitopes), SUR2A, Nav1.5 as indicated. pcDNA3 was included to keep the cDNA amounts equivalent in transfections. (A) Cell lysates (Total) or surface biotinylated membrane fractions (Surface) were subjected to SDS-PAGE and immunoblotted with antibodies against Nav1.5, myc, or GAPDH. A representative immunoblot is shown. Panels B and C respectively show data averaged from three similar blots. Total Nav1.5 or Kir6.2 protein in cell lysates were normalized to the amount of GAPDH, whereas surface expression was normalized to the total Nav1.5 or Kir6.2 protein. *p=0.0001 and p=0.0003 for panel B and C respectively with Student’s t test.

Negative regulation is imparted by a reduction in surface expression

Since the current densities were reduced by co-expression, but other channel properties remained unaltered, we used surface biotinylation assays to investigate whether surface expression was reduced. Data from these experiments demonstrated that the surface expression of Nav1.5, relative to the total Nav1.5 protein in the cell lysates, was significantly reduced when KATP channels were co-expressed (Figure 2A and B). To assess KATP channel surface expression we used a Kir6.2 construct with an extracellular Avi tag and C-terminal myc tag (Avi-Kir6.2-myc), which functions and traffics similar to wild-type Kir6.2 (Yang et al., 2018). Similar to the previous result, we found that KATP channel surface expression was significantly impaired by Na+ channels overexpression (Figure 2A and C).

A key role for the Kir6.2 ankyrin binding site

The surface abundance of membrane proteins can be regulated by anchoring mechanisms. Na+ and KATP channels have been reported to be respectively regulated by Ankyrin-G and B (Mohler et al., 2004; Kline et al., 2009). The AnkG binding motif of Nav1.5 consists of amino acids VPIAVAESD (Mohler et al., 2004), whereas the Kir6.2 C-terminal amino acid sequence VPIVAEED is necessary for in vitro binding to a GST-tagged AnkB membrane-binding domain, AnkB-MBD (Figure 3A) (Kline et al., 2009). Mutagenesis of negatively charged amino acids within this motif (E321K, E322K and D323K) disrupts both Kir6.2/AnkB-MBD binding and Kir6.2 surface expression (Kline et al., 2009). To investigate the potential role of ankyrin binding, we mutated the EED residues to lysine (Kir6.2-KKK). These mutations decreased Kir6.2 surface expression in HEK293 cells and we had to increase the cDNA amounts during transfections to accomplish cellular protein levels comparable to wild-type (Figure 3—figure supplement 1). As before, co-expression with WT-Kir6.2/SUR2A significantly reduced whole-cell Nav1.5 currents. By contrast, Kir6.2-KKK/SUR2A did not functionally interact with Na+ channels (Figure 3B). Moreover, surface biotinylation data demonstrated that WT-Kir6.2/SUR2A reduced surface expression of Nav1.5 as expected, but Kir6.2-KKK/SUR2A had no such effect (Figure 3C and D). We investigated whether the functional interaction also occurs with the other member of the Kir6 subfamily, namely Kir6.1, which does not bind to AnkB-MBD (Kline et al., 2009). Interestingly, Kir6.1/SUR2A was without effect on Nav1.5 currents (Figure 3B). Note that SUR2A was also present in this experiment, which supports the argument that the phenotype is intrinsic to Kir6.2, and not to SUR2A. Overall, these results demonstrate that the functional interactions of Nav1.5 and KATP channels are tightly coupled to the presence of an intact ankyrin binding domain in Kir6.2, therefore suggesting the possibility that competition for ankyrin binding mediates the functional interaction.

Figure 3 with 1 supplement see all
Download asset Open asset
An intact Kir6.2 ankyrin binding motif is necessary for functional interaction.

(A) Sequence alignment of ankyrin binding motifs (or corresponding residues) of various Nav channels and members of the Kir6 subfamily of inward rectifier K+ channels. The Kir6.2-KKK shows the mutations made to disrupt the binding motif. (B) Whole-cell Na+ currents were measured in HEK293 cells and averaged current-voltage relationships are plotted for cells transfected with Nav1.5 plus either empty vector (n = 8), Kir6.1/SUR2A (n = 6), Kir6.2/SUR2A (n = 7) or Kir6.2-KKK/SUR2A (n = 6). Data are from a minimum of 3 transfections. *p<0.001 determined by two-way ANOVA followed by Tukey’s test. (C) HEK-293 cells were transfected with Nav1.5 plus combinations of empty vector, Kir6.2/SUR2A, or Kir6.2-KKK/SUR2A. Cell lysates (Total) or surface biotinylated membrane fractions (Surface) were subjected to SDS-PAGE and immunoblotted with antibodies against Nav1.5 or GAPDH. A representative immunoblot is shown. (D) Averaged data of Nav1.5 surface expression normalized to the total Nav1.5 protein from three similar blots. *p=0.020 with 1W ANOVA followed by Dunnett’s test.

Functional co-localization of Na+ and KATP channels at the intercalated disc region of cardiac myocytes

We started to investigate whether Na+ channels and KATP channels functionally interact in cardiomyocytes by overexpressing Kir6.2 with a C-terminal mEos tag (Ad.Kir6.2-mEos) via adenoviral delivery. Indeed, rat cardiomyocytes expressing Kir6.2-mEos had a significantly reduced whole-cell Na+ current density compared to Ad.mCherry as a negative control (Figure 4—figure supplement 1). A key question, however, is whether the functional co-localization of Na+ channels and KATP channels can be demonstrated at a subcellular level. To accomplish this goal, we have developed a novel duplex patch clamp technique that allows sequential measurements of the two currents in the same membrane patch (illustrated in Figure 4A). Assuming that the free patch area of a 2–3 MΩ pipette is ~10 µm2 (Sakmann and Neher, 1995), this technique has a spatial resolution of ~2–3 µm. The INa is first recorded in a cell-attached membrane patch as in our previous studies (Lin et al., 2011). This Na+ channel recording is uncontaminated by KATP channels, which are closed at rest in an intact cell. The patch is then excised to measure the IK(ATP) mean patch current in an inside-out membrane patch. The membrane voltage is kept at +80 mV to inactivate INa and the magnitude of IK(ATP) is defined as the current component that is blocked by ‘intracellular’ ATP. Such paired recordings were made at the lateral membrane, or as close as feasible to the end of the cardiomyocyte (the ICD region) and paired recordings are summarized in Figure 4B. A key observation was that the majority of ICD patches expressed INa, but it was found in only ~50% of lateral patches. By contrast, each of the patches from lateral membranes and the ICD contained KATP channels. These paired data (blinded to their origin) were analyzed with machine learning algorithms (hierarchical clustering), which demonstrated two distinct populations (Figure 4—figure supplement 2). The lateral and ICD paired recordings segregated statistically between these two clusters (Figure 4B; Fisher’s Exact test, p=0.002), demonstrating that the ICD and lateral paired data points are distinct populations. To examine functional co-localization of Na+ channels and KATP channels at a subcellular level, we next performed duplex patch clamping after adenoviral delivery of Kir6.2-mEos. This intervention led to significantly larger KATP channel currents at both the lateral membranes and at the ICD. The corresponding INa patch current was significantly reduced at the ICD, but not at lateral membranes (Figure 4C). Thus, cardiac Na+ channels and KATP channels functionally interact predominantly at the ICD in cardiac myocytes.

Figure 4 with 2 supplements see all
Download asset Open asset
Functional interaction between KATP channels and Na+ channels in cardiac myocytes occurs predominantly at the ICD.

(A) Illustration of the duplex patch clamp method, which allows sequential recordings of INa and IKATP in the same membrane patch. In cell-attached mode (left), INa is recorded by changing the membrane potential. Recordings can be made in the absence of IKATP, which is generally not active in resting cardiomyocytes. After patch excision (right), recordings of KATP channels are made at +80 mV, a voltage at which INa is inactivated. Representative patch recordings are illustrated. (B) Paired duplex patch clamp recordings of IKATP and INa are plotted as individual points for patches from the lateral membrane (filled symbols; n = 15) or the ICD region of cardiomyocytes (open symbols; n = 14). The dotted circles illustrate the result of an independent hierarchal clustering analysis of these data (Figure 4—figure supplement 2). Data were obtained using cells from three separate isolations. (C) Duplex patch clamping was performed with rat cardiomyocytes treated with Ad.mCherry or Ad.Kir6.2-mEos. The average IKATP or INa recorded from lateral membranes (n = 14 for Ad.mCherry and 11 for Ad.Kir6.2-mEos) or the ICD (n = 13 for Ad.mCherry and 10 for Ad.Kir6.2-mEos) are plotted as bar graphs. Data were obtained using cells from four separate isolations. *p=0.032 and p=0.027 respectively for left panel, p=0.031 for right panel vs. Ad-mCherry using the Student’s t test.

To investigate the functional co-localization of Na+ and KATP channels at the ICD with improved spatial resolution, we performed Angle SICM experiments with high resistance (~30 MΩ) patch pipettes. With this methodology, a topographical image of the ICD surface is produced before performing cell attached patch clamping at a selected position (Figure 5A and B). The Na+ channels were activated by voltage clamp steps from −120 mV, whereas KATP channels were simultaneously recorded by activating them with pinacidil included in the pipette solution. Similar to our previous report (Leo-Macias et al., 2016), around 80% of recordings from ICD did not show Na+ channels activity. Notably, the patches without INa also lacked KATP channels. However, the Angle SICM patches from the ICD that contained a cluster of Na+ channels also contained KATP channel activity (Figure 5C and D). Thus, these data further support the concept that Na+ channels and KATP channels are functionally co-localized at the ICD of cardiac myocytes.

Figure 5
Download asset Open asset
Angle SICM recordings demonstrate functional co-localization of Na+ and KATP channels at the ICD of adult rat ventricular cardiomyocytes.

(A) Representative phase contrast image of a single cardiomyocyte. Recording pipette can be observed in the upper left. (B) Scan image acquired from location marked with red dashed line in A showing ICD region (top panel). Cross section showing the position of the pipette with respect the ICD (bottom). (C) Representative traces of the recorded current. Na+ channel currents can be observed at −40 mV and −50 mV steps (blue arrow and dashed box), KATP channel currents can be observed at +70 mV and −130 mV, when the Na+ channels are inactive. (D) Summary of cell-attached patch recordings. A total of 12 seals were recorded in which 10 of them did not show any channel activity at any voltage and 2 of them shown both Na+ and KATP channels activity.

KATP channels colocalize with AnkG but not AnkB at intercalated disc

In cardiomyocytes, AnkG localizes primarily, but not exclusively, to the ICD (Mohler et al., 2004; Lowe et al., 2008) and targets Nav1.5 to the ICD in cardiomyocytes (Mohler et al., 2004; Makara et al., 2014; Knezl et al., 2008). By contrast, AnkB is expressed mainly at lateral membranes where it localizes to Z- and M-lines in an isoform-dependent manner (Wu et al., 2015). Although Kir6.2 can interact with an AnkB-MBD construct (Kline et al., 2009), co-localization of AnkB and KATP channels has not been investigated in adult cardiomyocytes. Given the prominent role for the Kir6.2 ankyrin binding site in the functional interaction between KATP channels and Na+ channels, we next asked whether KATP channels co-localize with Ankyrins (AnkG or AnkB). Validation of anti-Nav1.5 and anti-Kir6.2 antibodies is shown in Figure 6—figure supplement 1. Immunofluorescence confocal microscopy of isolated rat cardiomyocytes and cardiac cryosections confirmed the presence of AnkB at lateral membranes, whereas expression of AnkG is enriched at (but not restricted to) the ICD (Figure 6—figure supplement 2). We found little evidence for co-localization of Kir6.2 with AnkB. By contrast, consistent with our previous report (Hong et al., 2012), we found that Kir6.2 co-localizes with AnkG, particularly at the ICD region of cardiac myocytes (Figure 6—figure supplement 2). We used STORM super-resolution microscopy to better analyze and quantify the co-localization of Nav1.5 and Kir6.2 with ankyrins. Figure 6 shows images of rat cardiomyocyte intercalated disc regions, co-stained with Kir6.2 and AnkB or AnkG, as well as Nav1.5 co-stained with AnkG. We quantified the distances between cluster edges of channels and ankyrins in the ICD region, which demonstrated a median clustering distance of 150 nm (interquartile range: 0–433 nm) between Nav1.5 and AnkG, which are well characterized to co-localize and interact at the ICD (Mohler et al., 2004; Makara et al., 2014; Knezl et al., 2008). The clustering distance between Kir6.2 and AnkG at the ICD was in the same range (median: 228 nm, interquartile range: 0–563 nm), whereas the clustering distance between Kir6.2 and AnkB was four times larger (median: 886 nm, interquartile range: 102–2205 nm). Thus, both Nav1.5 and Kir6.2 are strongly co-localized with AnkG, but not with AnkB, at the ICD of cardiac myocytes.

Figure 6 with 3 supplements see all
Download asset Open asset
Quantification of inter-cluster distances between KATP channels, Na+ channels and ankyrins.

(A) Enlarged STORM images of the rat cardiomyocyte intercalated disc region, co-stained with antibodies against ankyrin B, ankyrin G, Kir6.2 and Nav1.5, as indicated. Scale bar, 2 μm. (B) Statistical analysis of the distances between Nav1.5 or Kir6.2 to the closest ankyrin clusters. N ≥ 67 clusters from three rats in each group. *p<0.0001 vs. Nav1.5/AnkG group determined by Kruskal-Wallis 1W ANOVA, followed by Dunn’s post-hoc analysis.

Ankyrin binding is necessary to localize Na+ and KATP channels to the ICD

We next examined whether Ankyrin binding promotes trafficking of Na+ channels and KATP channels to the ICD of cardiac myocytes. To address this question, we used peptides corresponding to the Kir6.2 or Nav1.5 ankyrin binding sites to outcompete binding of the channels to ankyrins. The peptides were conjugated to an HIV Tat-derived peptide to enable delivery into cells (Schwarze et al., 1999; Chen et al., 2001). Rat cardiac myocytes were treated for 24 hr with TAT peptides and the INa and IKATP were measured using the duplex patch clamp technique, either at lateral membranes or at the ICD region. Averaged data are shown in Figure 7, which demonstrates that the INa and IKATP were larger at the ICD than at lateral membranes as expected. Peptides corresponding to the Nav1.5 ankyrin binding site caused a reduction of both INa and IKATP at the ICD, but not in lateral membranes. Similarly, peptides corresponding to the Kir6.2 ankyrin binding site caused targeting defects of both INa and IKATP at the ICD, but not in lateral membranes. These peptide experiments demonstrate that ankyrin binding regulates targeting of both Na+ channels and KATP channels to the ICD of cardiac myocytes.

Figure 7 with 1 supplement see all
Download asset Open asset
The IKATP and INa at the ICD is preferentially reduced by peptides corresponding to the Nav1.5 or Kir6.2 ankyrin binding sites.

Rat ventricular cardiac myocytes were incubated for 24 hr with TAT-conjugated peptides corresponding to the ankyrin binding site of Nav1.5 (Nav1.5 peptide, 50 µM; n = 15 cells) or Kir6.2 (Kir6.2 peptide, 50 µM; n = 15 cells). Untreated cardiomyocytes were used as a control (n = 17 cells). Duplex patch clamping was performed to measure IKATP (A) and INa (B) paired recordings at lateral membranes or at the ICD. Shown are cumulative data obtained from cells isolated from four rats. *p=0.030 and p=0.022 respectively for panel A, p=0.024 and p=0.018 respectively for panel B vs. control determined by 1W ANOVA followed by Tukey’s test.

Clinical variants that causing KATP channel trafficking defects affect Nav1.5 surface expression

Variants in the genes encoding Kir6.2 and SUR1, KCNJ11 and ABCC8, are commonly associated with insulin secretion disorders and diabetes (Nichols, 2006) and many of these variants cause trafficking defects of KATP channels. For example, the missense NM_000525.3(KCNJ11):c.776A > G variant, which is rare in gnomAD and ExAC databases and is associated with severe congenital hyperinsulinism (ClinVar ID 8677), causes a p.His259Arg amino acid change in Kir6.2, and a severe trafficking defect (Yang et al., 2017; Marthinet et al., 2005). Given the functional interaction between KATP channels and Na+ channels, the question arose whether a clinically relevant KATP channel gene variant such as this would affect the cardiac Na+ channel. To answer this question, we co-expressed Nav1.5 with either wild-type Kir6.2 or Kir6.2-H259R in HEK293 cells. The Kir6.2-H259R channels neither expressed functional channels in patch clamp assays, nor were detected as surface proteins with biotinylation assays (Figure 8A and B), which is consistent with the trafficking defect previously reported (Marthinet et al., 2005). As before, the whole-cell Nav1.5 current was substantially reduced by co-expression with wild-type Kir6.2/SUR2A (compare Figures 1A and 8D). By contrast, co-expression with Kir6.2-H259R/SUR2A did not reduce the Nav1.5 currents relative to empty vector controls (~100 pA/pF at −20 mV; Figures 1A and 8D) and the surface abundance of Nav1.5 was significantly higher when co-expressed with Kir6.2-H259R compared to wild-type Kir6.2 (Figure 8C). Thus, variants that influence KATP channel surface expression may simultaneously affect Na+ channel surface expression and therefore have the potential to contribute to abnormalities in cardiac excitability and arrhythmias.

Figure 8 with 1 supplement see all
Download asset Open asset
A clinically relevant Kir6.2 trafficking defective mutation (H259R) influences Nav1.5 surface expression.

(A) HEK-293 cells were transfected with Kir6.2/SUR2A or Kir6.2-H259R/SUR2A. The averaged KATP channel mean patch current, recorded in excised patches, are depicted as bar graphs, with WT-Kir6.2 and Kir6.2-H259R respectively depicted as black (n = 4 cells) or gray (n = 4 cells) bars. Data are from three transfections. *p=0.0002 using the Student’s t test. (B) Surface expression was determined by biotinylation assays with cell lysates from HEK293 cells transfected with combinations of Nav1.5, Kir6.2, Kir6.2-H259R, and/or SUR2A. Shown is a representative immunoblot of cell lysates (total) or biotinylated membrane fractions (surface) probed with antibodies as indicated. (C) Summary data (n = 3) of the normalized ratio of surface/total Nav1.5 protein in cells transfected with cDNAs as indicated. *p=0.026 using the Student’s t test. (D) Average current-voltage relationships of whole cell currents in HEK293 cells transfected with Nav1.5 plus empty vector (n = 7), Kir6.2/SUR2A (n = 7) or Kir6.2-H259R/SUR2A (n = 7). Data are from three transfections. *p<0.05 determined by two-way ANOVA followed by Tukey’s test.

Discussion

Our data demonstrate that Na+ channels and KATP channels are functionally coupled, both in heterologous expression systems and in cardiac myocytes. Ankyrin binding appears to underlie functional coupling since it can be disrupted by mutations in the Kir6.2 ankyrin binding site. In cardiomyocytes, Na+ channels and KATP channels co-localize both functionally, demonstrated by duplex patch clamping, and morphologically, specifically at the ICD. We found AnkG, but not AnkB, to be expressed at the ICD. Quantitative super-resolution microscopy shows similar clustering distances between AnkG and Na+ channels or KATP channels at the ICD. Competition experiments with peptides corresponding to Nav1.5 and Kir6.2 ankyrin binding sites dysregulate targeting of both Na+ channels and KATP channels to the ICD, but not to lateral membranes. Finally, we demonstrate that a clinically relevant gene variant that affect KATP channel trafficking also affects Na+ channel surface expression.

Targeting of ion channels to discrete subcellular compartments

Many ion channels are compartmentalized within cells. For example, in the highly polarized kidney epithelial cell, channels and transporters can either target to the basolateral or apical membranes (Stoops and Caplan, 2014). In cardiac myocytes, ion channels and transporters are also targeted to specific subcellular compartments for optimal cellular function. The L-type Ca2+ channel (LTCC), for example, is targeted to couplons adjacent to ryanodine receptors to allow for efficient excitation-contraction. Ion channels and transporters are often targeted to caveolae and lipid rafts. Caveolae are generally thought to be present at the mouth of t-tubules and/or the crests between t-tubules and may contain ion channels such as a specific population of LTCCs, Hyperpolarization activated cyclic nucleotide gated potassium channel 4 (HCN4), Kv1.5 and Na+/Ca2+ exchanger (Best and Kamp, 2012; Hong and Shaw, 2017). Caveolae are also enriched with components of molecular signaling pathways, such as β-adrenergic receptors, culminating in local regulation of ion channels. A number of ion channels are targeted to the ICD membrane structure that couple neighboring cardiac myocytes. The Na+ channel was one of the first described to be enriched at the ICD (Cohen and Levitt, 1993). Examples of other channels enriched at the ICD of cardiac myocytes include Kv1.5 (Mays et al., 1995) and the inward rectifying K+ channel subunits, Kir2.1 and Kir2.3 (Melnyk et al., 2002). In our studies, we found an enrichment of KATP channels at the ICD regions of ventricular myocytes, where they co-localize with desmosomal proteins such as PKP2 (Hong et al., 2012). The targeting mechanisms for Na+ channels to the ICD are best understood, and involve forwarding trafficking and anchoring mechanisms that are coordinated by EB1, SAP97, PKP2 and AnkG (Shy et al., 2013; Agullo-Pascual et al., 2014; Gillet et al., 2014; Chen-Izu et al., 2015). Mechanisms responsible for targeting KATP channels to the ICD have not been described.

A role for ankyrin G in targeting channels to the ICD

Ankyrins are cytoskeletal proteins that associate with spectrin-actin networks and bind to integral membrane proteins, thus serving as a sub-membrane scaffold for coordinating the targeting of membrane proteins. Axonal voltage-gated Na+ channels, such as Nav1.6, has long been recognized to be targeted by AnkG (Jenkins and Bennett, 2001). Other ion translocators that are linked to the spectrin-based membrane skeleton by ankyrins include the anion exchanger, the Na+/Ca2+ exchanger, and the Na+/K+ ATPase (Bennett and Baines, 2001). A missense variant in SCN5A (the gene coding for Nav1.5), associated with Brugada syndrome, which causes an amino acid substitution (E1053K) in the Nav1.5 ankyrin-binding domain, has led to the identification of a key role for AnkG in targeting Na+ channels to the ICD of cardiac myocytes (Mohler et al., 2004). Subsequent studies have shown that Na+ channels are targeted to subcellular domains at the ICD that contain desmosomal proteins and N-cadherin (Leo-Macias et al., 2016; Cerrone and Delmar, 2014). KATP channels are also enriched at the ICD and target to contain desmosomal proteins (Hong et al., 2012). Several observations from our current study suggest that AnkG plays a key role in KATP channel targeting to this region. First, the functional interaction that exists between Na+ channels and KATP channels can be prevented by specific amino acid substitutions within the ankyrin binding domain of Kir6.2. Second, the quantitative STORM measurements show similar intermolecular distances between AnkG and Na+ channels or KATP channels. Third, duplex patch clamping shows functional co-localization in all patches obtained at the ICD between Na+ channels and KATP channels. Fourth, conventional fluorescence microscopy shows a remarkable degree of overlap between Nav1.5 and Kir6.2 staining at the ICD regions of cardiomyocytes. Fifth, competition experiments with peptides corresponding to Ankyrin binding motifs disrupt both Na+ channel and KATP channel expression at the ICD, demonstrating a clear role for ankyrins. Finally, consistent with the literature, we find strong expression of AnkG, but not AnkB, at the ICD. Collectively, we interpret these data as evidence that AnkG mediates targeting of both Na+ channels and KATP channels to the ICD.

Although we have observed the AnkG competition mechanism to regulate the surface expression of Nav1.5 and KATP channels in both HEK293 cells and cardiomyocytes, a previous study has reported that the ankyrin binding deficient Nav1.5 E1053K efficiently transports to the membrane in HEK293 cells, but not in rat ventricular cardiomyocytes (Mohler et al., 2004). In the latter study, cells were co-transfected with the Nav-beta subunit, which was previously shown also to interact with AnkG (Malhotra et al., 2002). Thus, an additional role for Nav-beta subunits to regulate the AnkG/Nav1.5/KATP complex is a real but unexplored possibility.

Both Na+ and KATP channels are enriched at the ICD of a cardiac myocyte (Hong et al., 2012; Lin et al., 2011). Previous data suggest that AnkG and Gap junction alpha-1 protein (Cx43) are necessary to preserve the Na+current amplitude, electrical coupling and intercellular adhesion strength (Sato et al., 2011). Since the KATP channel, Na+ channel and AnkG interaction can be demonstrated in HEK-293 cells, which do not express Cx43, we believe that our data demonstrate that Cx43 is not a necessary component for functional interaction. However, we have not investigated this in cardiomyocytes. With immunofluorescence, we found that Nav1.5 and Kir6.2 are spatially localized closer to each other at the ICD compared to the lateral membrane (Figure 6—figure supplement 3). However, we do not think that Na+ channels directly interact with KATP channels. Our STORM imaging data show that the median intermolecular clustering distance from Nav1.5 to closest Kir6.2 at the ICD region is 528 nm (Figure 6—figure supplement 3), which is greater than expected for direct molecular interactions. The distributions of the cluster area of Nav1.5 and Kir6.2 channel subunits can be well fitted with single exponential function (Figure 6—figure supplement 3), indicating a stochastic self-assembly process in the formation of Nav1.5 and Kir6.2 clusters, which later become attached to AnkG in the ICD, as in the case of cardiac Cav1.2 directed by BIN1 (Sato et al., 2019). This observation suggests a model in which Na+ channels and KATP channels bind to closely spaced AnkG proteins. The suppression of Na+ channel surface density by KATP channel overexpression (and vice versa), which can be disrupted by mutagenesis of the Kir6.2 ankyrin binding motif, most likely results from competition of these two channels for the AnkG proteins. Several different proteins, including Nav channels, the Na+/Ca2+ exchanger, the Na+/K+ ATPase, IP3 receptors, KCNQ channels, and Kv3.1 channels all bind to ankyrins, but each protein class has a very different ankyrin binding site, which is evolutionarily highly conserved within the class (Bennett and Healy, 2009). The high sequence similarity of the ankyrin binding motifs of Kir6.2 and Nav1.5 (Figure 3A) is therefore somewhat surprising, but it is easy to visualize how these similar sequences can both bind to AnkG. More surprising, however, is that the corresponding sequence within Kir6.1 is almost identical, but neither supports ankyrin binding (Li et al., 2010), nor confers the ability to interact with Nav1.5 (Figure 3B). Future structural studies would be very helpful to determine the nature and specificity of the binding sites to AnkB and/or AnkG.

Targeting of KATP channels to lateral membranes

This study was not designed to study targeting to lateral membranes in cardiomyocytes, yet some of our findings are relevant. KATP channels interact with AnkB in vitro (Li et al., 2010), and AnkB is expressed mainly at lateral membranes at Z- and M-lines (Wu et al., 2015). In support, when overexpressed in HEK293 cells, we found that Kir6.2 can interact both with AnkB and AnkG (Figure 7—figure supplement 1). We therefore fully expected a role for AnkB to target KATP channels to lateral membranes. However, the peptide competition experiments question whether Kir6.2/AnkB interaction occurs natively. Peptides corresponding to ankyrin binding sites of Nav1.5 and Kir6.2 had identical effects to displace both Na+ channels and KATP channels from the ICD, demonstrating that the peptides were functional. However, the peptides did not influence these two channels at lateral membranes. Data with the duplex patch clamp technique suggest that (at least some of the) Na+ channels and KATP channels may be differently trafficked to the lateral membrane. Within the spatial dimension of duplex patch clamping, about half of the patches contained Na+ channels at the lateral membrane, whereas KATP channels were present in every single patch. Differential trafficking of these two channels in lateral membranes is also suggested from high-resolution scanning ion conductance microscopy (SICM), which demonstrated that the majority of Na+ channels in lateral membranes are clustered in crests of mouse ventricular cardiomyocytes, with hardly any Na+ channels present in the grooves (Rivaud et al., 2017). Early recordings with this technique, combined with whole-cell voltage clamping, by contrast suggested that lateral KATP channels are present as submicrometer clusters in Z-grooves of the sarcolemma (Korchev et al., 2000). The finding is in support of the presence of KATP channels in caveolae (Yang et al., 2018), which are often found at t-tubular structures (Hong and Shaw, 2017). Nevertheless, our duplex patch clamp data demonstrated functional co-localization of Na+ channels an KATP channels in about half of the patches and future studies should be directed at identification of the targeting mechanisms of these co-localized channels.

What might be the physiological relevance and pathophysiological implications?

It is not clear what the role of KATP channels at the ICD might be, and why they are functionally coupled to Na+ channels. We have not examined action potential characteristics, since we believe that these local changes may not reflect global electrophysiological properties of the cell. Rather, we emphasize that our findings support the growing body of evidence that cardiac ion channels do not travel and organize as lone entities, but as complexes. Our data are fully supported by recent studies, such as the finding of co-translational 'microtranslatomes' that contain both K+ channels and Na+ channels (Eichel et al., 2019), and findings that K+ and Na+ channels can co-traffic in cardiac cells (Ponce-Balbuena et al., 2018). Given its small size (nanometers in scale) and convoluted nature, the ICD cleft space is severely diffusion restricted. Therefore, with repetitive electrical activity, Na+ entering the cell via Na+ channels may cause local intracellular Na+ accumulation and Na+ depletion in the ICD cleft, which is counteracted by ATP-driven Na+ extrusion via the Na+/K+ pump in exchange for K+ influx. This, in turn, may lead to K+ depletion in the ICD cleft space. A K+ flux coupling mechanism must exist to maintain homeostasis. In addition to their functional coupling to Na+ channels (this study), KATP channels and the Na+/K+ pump are also functionally coupled, such that an increased Na+/K+ pump activity activates KATP channels (Priebe et al., 1996), which is thought to occur because of local sub-membrane ATP depletion (and ADP accumulation). We propose therefore that at high heart rates, the elevated Na+/K+ pump activity may locally activate the ICD KATP channels in order to balance K+ fluxes and maintain the ionic hemostasis in the ICD cleft (Figure 8—figure supplement 1). From genetic studies, the overwhelmingly predominant clinical phenotype of KCNJ11 (Kir6.2) variants is insulin secreting disorders. Arrhythmias may well be a secondary and understudied phenotype. We know from pharmacological studies (with both humans and animals) that cardiac arrhythmias are a very real phenomenon associated with KATP channel openers and blockers (Foster and Coetzee, 2016). In the model proposed, a relationship between KATP channel activation and cardiac conduction is predicted, which is evident from the literature. For example, while studying KATP channels in the cardiac specialized conduction system, we have observed that conduction slowing in ischemic Langendorff-perfused mouse hearts was essentially prevented by the KATP channel blocker glibenclamide (Bao et al., 2011). This finding was in keeping with the literature that glibenclamide decreases conduction delays during ischemia in open-chest dogs (Bekheit et al., 1990), prevents the beneficial effect of IPC on electrical uncoupling during ischemia (Tan et al., 1993), and prevents asymmetric conduction slowing during acute ischemia in canine interventricular septum (Morita et al., 2008). Our data additionally demonstrate another level of pathophysiological relevance. We found that genetic variants associated with insulin disorders that cause KATP channel trafficking defects may also affect Na+ channel surface expression. These suggest that there may be implications for heart disease and conduction disorders in diabetic patients with KATP channel trafficking mutations. Conversely, genetic defects resulting in Na+ channel trafficking alterations have the potential to affect KATP channel surface expression, and therefore the susceptibility of patients with inherited forms of arrhythmias to ischemia/reperfusion injury. These possible relationships need to be explored in future studies given the clinical relevance and therapeutic potential of our findings.

Study limitations

At present, the physiological or pathophysiological implications of the functional interactions between Na+ and KATP channels are unknown. Human iPSC-derived cardiomyocytes are a poor substitute to study this question since these cells have an immature electrophysiology phenotype with little KATP channel expression. These cells also lack fully developed intercalated disks. These limitations are shared by other cardiac cellular models, such as HL-1 cells and cultured primary neonatal cardiac myocytes. An in vivo model with disrupted AnkG/Nav1.5/KATP interaction would be ideal to address effects in cardiomyopathies or in clinically relevant arrhythmias. Unfortunately no such model is currently available. Such an in vivo model would also be able to address the question of whether disrupted AnkG/Nav1.5/KATP interaction affects the ICD structure. We deem this to be unlikely, though, given that patients with mutations in the Nav1.5 AnkG binding domain (and disrupted trafficking of Nav1.5 to the ICD) develop arrhythmias (Brugada syndrome) but not cardiomyopathies (Mohler et al., 2004), which would be expected to occur if structural disorder of the ICD occurred.

Materials and methods

Key resources table
Reagent type
(species) or resource		DesignationSource or referenceIdentifiersAdditional information
Cell line (Homo-sapiens)HEK293ATCCCat# CRL-1573, RRID:CVCL_0045Mycoplasma contamination negative
Recombinant DNA reagentNav1.5Tan et al., 2018
Recombinant DNA reagentKir6.2Yang et al., 2018
Recombinant DNA reagentKir6.2-mycYang et al., 2018
Recombinant DNA reagentAvi-Kir6.2-mycYang et al., 2018
Recombinant DNA reagentKir6.2-KKKThis paperGenscript
Recombinant DNA reagentKir6.2-H259RThis paperGenscript
Recombinant DNA reagentKir6.1This paperGenscript
Recombinant DNA reagentKir6.2-AAATong et al., 2006
Recombinant DNA reagentSUR2AYang et al., 2018
Recombinant DNA reagentAnkyrin-BAddgeneRRID:Addgene_31057
Recombinant DNA reagentAnkyrin-GAddgeneRRID:Addgene_31059
Transfected constructAdenovirus mCherryThis paperVector Biolabs
Transfected construct (human)Adenovirus Kir6.2-mEos3.2This paperVector Biolabs
Peptide, recombinant proteinKir6.2 ankyrin binding motifGenscriptVPIVAEEDGGGGGRKKRRQRRRPQ
Peptide, recombinant proteinNav1.5 ankyrin binding motifGenscriptVPIAVAESDGGGGGRKKRRQRRRPQ
AntibodyAnti-Nav1.5 (Mouse monoclonal)Sigma AldrichCat# S8809, RRID:AB_477552WB (1:2000)
AntibodyAnti-Nav1.5 (Rabbit polyclonal)Sigma AldrichCat# S0819, RRID:AB_261927IF(1:200), STORM (1:50)
AntibodyAnti-Kir6.2 (Goat polyclonal)Santa CruzCat# sc-11226,
RRID:AB_2130475		WB (1:500)
AntibodyAnti-Kir6.2 (Chicken polyclonal)Hong et al., 2012C62IF(1:50), STORM (1:50)
AntibodyAnti-Kir6.2 (Rabbit polyclonal)Hong et al., 2012Lee62STORM (1:50)
AntibodyAnti-AnkyrinG (Mouse monoclonal)NeuromabCat# N106/20, RRID:AB_2750699IF(1:500), STORM (1:50), WB (1:2000)
AntibodyAnti-AnkyrinB (Mouse monoclonal)NeuromabN105/17IF(1:500), STORM (1:50), WB (1:2000)
AntibodyAnti-myc (Mouse monoclonal)Sigma Aldrich9E10WB (1:6000)
AntibodyAnti-GAPDH (Mouse monoclonal)Sigma AldrichCat# G8795, RRID:AB_1078991WB (1:20000)
AntibodyAnti-caveolin3 (Mouse monoclonal)Transduction LaboratoriesC38320WB (1:50000)
Antibodydonkey anti-mouse-HRPJackson ImmunoResearchCat# 715-035-150, RRID:AB_2340770WB (1:10000)
Antibodydonkey anti-goat-HRPJackson ImmunoResearchCat# 705-035-147, RRID:AB_2313587WB (1:10000)
Antibodygoat anti-chicken Alexa Fluor568Thermo ScientificCat# A-11041, RRID:AB_2534098IF(1:200)
Antibodydonkey anti-rabbit Alexa Fluor488Jackson ImmunoResearchCat# 711-545-152, RRID:AB_2313584IF(1:200)
Antibodydonkey anti-mouse Cy3Jackson ImmunoResearchCat# 715-165-151, RRID:AB_2315777IF(1:200)
Software, algorithmGraphPad PrismGraphPad PrismRRID:SCR_002798

cDNA constructs and mutagenesis

Request a detailed protocol

Wild-type Nav1.5, Kir6.2, SUR2A constructs, Kir6.2-AAA, Kir6.2-myc and Avi-Kir6.2 cDNAs were previously used (Tong et al., 2006; Yang et al., 2018; Tan et al., 2018). Kir6.1, Kir6.2-KKK and Kir6.2-H259R were synthesized by Genscript. Ankyrin-G (#31059) and ankyrin-B (#31057) constructs were from AddGene.

Cell culture and transfection

Request a detailed protocol

HEK-293 cells (ATCC CRL-1573), negative in mycoplasma contamination test, were cultured in EMEM with 10% fetal bovine serum. Lipofectamine 2000 (ThermoFisher, Waltham, MA) was used to transfect ankyrins, Nav1.5 and KATP channel subunit cDNAs. When cells were transfected with multiple cDNAs, the empty vector (pcDNA3) was included to keep the total cDNA amount equal in transfection reactions. Nav1.5 and KATP channels were co-transfected with the cDNA amount ratio of Nav1.5:Kir6.2:SUR2A to be 10:1:9. Rat ventricular cardiomyocytes were enzymatically isolated as previously described (Hong et al., 2011). All procedures conformed to the Guide for Care and Use of Laboratory Animals of the National Institutes of Health and were approved by the NYU IACUC committee (protocol s17-00352). Cells were plated on laminin-coated coverslips and cultured in EMEM. Adenovirus carrying mEos3.2 labeled Kir6.2 (Vector Biolabs, Malvern, PA, USA) were added at an MOI of 1000 for 12 hr incubation. An mCherry expressing adenovirus was used as control. Cultured cardiomyocytes were used for experiments 72 hr post-infection. Peptides corresponding to the ankyrin binding sites of Kir6.2 (VPIVAEEDGGGGGRKKRRQRRRPQ) or Nav1.5 (VPIAVAESDGGGGGRKKRRQRRRPQ) were synthesized by Genscript, and incubated cardiomyocytes for 24 hr before patch clamp.

Patch clamp electrophysiology

Request a detailed protocol

Standard patch-clamping was performed using an Axopatch-200B amplifier and recording data with a Digidata 1550A and Clampex 10 software. For inside-out KATP current recordings, the pipette resistance was 3 ~ 4 MΩ when filled with pipette solution consisting of (in mM): 110 potassium gluconate, 30 KCl, 2 CaCl2, 1 MgCl2, 10 HEPES, and pH 7.4. The bath solution consisted of (in mM): 110 potassium gluconate, 30 KCl, 1 EGTA, 1 MgCl2, 10 HEPES, and pH 7.2. Following patch excision, the pipette potential was held at +80 mV and current was digitized at 1 kHz. Currents were recorded immediately after patch excision and recordings with any sign of rundown were discarded. The ‘cytosolic’ ATP concentration was changed by a rapid solution changer (RSC160, BioLogic SAS, Seyssinet-Pariset, France). For whole-cell Nav1.5 current recordings in HEK293 cells, the pipette resistance was 2 ~ 3 MΩ when filled with pipette solution consisting of (in mM): 50 CsCl, 60 CsF, 10 TEA·Cl, 20 EGTA, 5 Na2ATP, 10 HEPES, and pH 7.2 with CsOH. The bath solution consisted of (in mM): 30 NaCl, 110 CsCl, 4 KCl, 1 CaCl2, 1 MgCl2, 10 HEPES, 5 Glucose and pH 7.35 with CsOH. NaCl in bath solution dropped to 5 mM and compensated by CsCl when recording in cardiomyocytes.

For duplex recording of Na+ and KATP current from the same patch in cardiomyocytes, the pipette resistance was ~2 MΩ when filled with pipette solution consisting of (in mM): 125 NaCl, 5.4 KCl, 10 TEA·Cl, 1 MgCl2, 0.33 NaH2PO4, 1 4-aminopyridine, 10 HEPES, and pH 7.35 with NaOH. The bath solution consisted of (in mM): 140 KCl, 0.33 NaH2PO4, 1 EGTA, 1 MgCl2, 10 HEPES and pH 7.2 with KOH. Nav1.5 current was first measured by a voltage step protocol with P/N substraction in cell-attached mode, Nav1.5 channel was activated by depolarizations from −100 mV to voltages between −80 mV to +80 mV, then membrane under the pipette tip was excised and KATP current was measured with rapid ATP perfusion in inside-out mode with holding potential of +80 mV.

Electrophysiological recordings with angle SICM

Request a detailed protocol

Scanning ion conductance microscopy (SICM) is a non-contact scanning probe microscopy technique based on the principle that the flow of ions through the tip of a nanopipette filled with electrolytes decreases when the pipette approaches the surface of the sample (Hansma et al., 1989; Korchev et al., 1997a; Korchev et al., 1997b). In this study, we used a variant of SICM called angular approach scanning ion conductance microscopy described in detail by Shevchuk et al. (2016). The system was used in the same configuration as Leo-Macias et al. (2016). Briefly, the scanning probe was mounted in a PatchStar micromanipulator (Scientifica, UK) that allows to adjust the angle for the scanning, selected as 33° in this work for the purpose of scanning the ICD of adult cardiomyocytes with nanoscale resolution. Borosilicate glass nanopipettes pulled from 1.0 mm outer diameter, 0.4 mm ID capillary were used in all experiments. Axopatch 200B patch clamp amplifier (Axon Instruments; Molecular Devices) was used to measure the pipette current as well as to record ion channel activity. Cell-attached currents were digitized using Digidata 1440A and a pClamp 10 data acquisition system (Axon Instruments; Molecular Devices).

After the ICD region was recognized by the scanning, the pipette was moved to the area of sealing, the feedback of the hoping mode was switched off and a gigaseal was formed by lowering the pipette until it makes contact with the surface of the ICD. Cell-attached patch-clamp configuration was then used to record of Na+ and KATP channels simultaneously. Recordings were performed at room temperature using the following solutions; external solution containing (in mM): 145 KCl; 1 MgCl2; 1 CaCl2; 2 EGTA; 10 glucose; 10 HEPES; and pH 7.4 with KOH; internal recording solution containing (in mM): 135 NaCl; 0.4 NaH2PO4; 1 MgCl2; 5.4 KCl; 1 CaCl2; 5.5 glucose; 5 HEPES; 20 TEA-Cl; 0.2 CdCl2; 10 CsCl; 10, 4-AP; and pH 7.4 with NaOH. Pinacidil was added to both solutions at a concentration of 200 µM to activate KATP channels. The pipette used for cell-attached recordings had an average resistance of ~30 MΩ. To generate a current–voltage (I–V) relationship that allow the simultaneous recording of Na+ and KATP channels, the membrane under the patch was held at a voltage of −120 mV and incremental steps of 10 mV were applied from −100 to +90 mV. Data were low-pass filtered at 1 kHz using the built-in Bessel filter of the amplifier and sampled at 20 kHz.

Biotinylation assay

Request a detailed protocol

HEK293 cells expressing Nav1.5 and Avi-Kir6.2-myc were incubated with 0.33 mM biotin for 1 hr at 4°C. After washing with PBS, cells were homogenized in RIPA buffer. Equal amount of biotinylated proteins was incubated with Neutravidin agarose beads (Thermo Scientific) at 4°C overnight. The supernatants were discarded and biotinylated proteins were eluted by a mixture of loading buffer and 200 mM DTT. Western blots were quantified by ImageJ.

Membrane fractionation

Request a detailed protocol

Flash-frozen hearts were ground to a fine powder in liquid nitrogen using a pestle and mortar. Samples were homogenized on ice with 30 strokes of a glass-glass homogenizer, followed by 30 strokes in a Dounce homogenizer in (in mM) 250 sucrose, 1 EDTA, 10 HEPES, 1 DTT and pH 7.4 supplemented with protease inhibitor cocktail (Roche Applied Science). Following brief centrifugation (1000 g for 5 min at 4°C), the pellet was re-homogenized in fresh homogenization buffer with 25 strokes of a tight-fitting Dounce and cleared by brief centrifugation (1000 g, 5 min, 4°C). The resulting supernatant was combined with that of the previous step. The supernatant was centrifuged at 50,000 rpm using a 90 Ti rotor (Beckman Coulter, Brea, CA) for 1 hr at 4°C. The resulting membrane pellets were solubilized with rotation overnight at 4°C in 20 mM HEPES, 0.5% Triton X100, pH 7.4.

Immunocytochemistry and immunohistochemistry

Request a detailed protocol

As previously described (Yang et al., 2018), isolated rat cardiomyocytes or rat heart slices were fixed with 4% paraformaldehyde. Cells or tissue were permeabilized with 0.1% Triton X-100 and blocked with 5% donkey serum in PBS. Primary and secondary antibodies buffered in blocking solution were sequentially applied. After washing and mounting, images were obtained by Zeiss 700 confocal microscope (Zeiss, Jena, Germany).

Stochastic optical reconstruction microscopy (STORM)

Request a detailed protocol

Freshly isolated rat cardiomyocytes were plated on laminin-coated coverslips for 1 hr before fixation with 4% paraformaldehyde. Cells were then permeabilized with 0.1% Triton in PBS for 10 min, and incubated in blocking solution (PBS based 2% Glycine, 2% BSA and 0.2% Gelatin) for 30 min. Primary antibodies diluted 1:50 in blocking solution incubated the cells for 1 hr at room temperature. After three washes with PBS, secondary antibodies against a combination of mouse conjugated with Alexa Fluor 647 and rabbit conjugated with Alexa Fluor 568 or a combination of rabbit conjugated with Alexa Fluor 647 and chicken conjugated with Alexa Fluor 568 (1:10000, Invitrogen) were incubated for 15 min at room temperature. Imaging conditions were achieved by addition of 200 mmol/L mercaptoethylamine and an oxygen scavenging system (0.4 mg/ml glucose oxidase, 0.8 µg/mL catalase and 10% (wt/wt) glucose) to the fluorophore-containing sample.

As previously described (Kim et al., 2019), samples were imaged using a custom-built platform based on an inverse microscopy setup (Leica DMI3000). Sample emission was split into two channels through proper dichroic and emission narrow-band bandpass filters (green channel 580/60, red channel 680/40, Semrock), in conjunction with a Dual View (DV2-Photometrics) to image two colors simultaneously, onto a single EM-CCD camera (Andor iXon+ 897). For accurate alignment and mapping of the two color channels, we first imaged diffraction-limited fluorescent beads that have a wide emission spectra spanning both channels (Invitrogen). The location of the beads was matched for both channels based on the use of a polynomial morph-type mapping function, whereby mapping coefficients are generated by Gaussian and centroid fits to the sub-diffraction limit point-spread functions of the fluorescence beads. The two-color image was reconstructed at 20 nm/pixel using the following QuickPALM parameters, FWHM = 4 and S/N = 2.00. The reconstructed super-resolved images of each channel were then super-imposed to generate a two color super-resolved image. The mapping error in the super-resolved image was 20 nm. ROIs of intercalated disc were manually drawn for each reconstructed super-resolution images and further cluster detection were obtained using ImageJ and cluster distance analysis accomplished by a home-built Python script that utilized the image processing packages scikit-image (van der Walt et al., 2014), and ‘Mahotas,’ an open source software for scriptable computer vision (http://dx.doi.org/10.5334/jors.ac). Please refer to our previous studies (Agullo-Pascual et al., 2013) for extensive methodological details of our custom-developed analysis pipeline, its technical specifications and limitations, as well as specifics of its resolution both in the X-Y and in the Z planes.

Antibodies

Primary antibodies used were: mouse anti-GAPDH (G8795, Sigma-Aldrich; 1:10000 for western blot), mouse anti-c-Myc (M4439, Sigma-Aldrich; 1:6000 for western blot), mouse anti-Nav1.5 (S8809, Sigma-Aldrich; 1:2000 for western blot), rabbit anti-Nav1.5 (S0819, Sigma-Aldrich; 1:200 for immunostaining, 1:50 for STORM), chicken anti-Kir6.2 (C62; 1:50 for immunostaining and STORM), rabbit anti-Kir6.2 (Lee62; 1:50 for STORM), goat anti-Kir6.2 (N18, Santa Cruz; 1:500 for western blot), mouse anti-ankyrin-B (105/17, Neuromab; 1:2000 for western blot, 1:50 for STORM) and mouse anti-ankyrin-G (106/20, Neuromab; 1:2000 for western, 1:50 for STORM). Secondary antibodies used were donkey anti-mouse-HRP (715-035-150, Jackson, 1:10000), donkey anti-goat-HRP (705-035-147, Jackson, 1:10000), goat anti-chicken Alexa Fluor568 (A-11041, Thermo Scientific; 1:200), donkey anti-rabbit Alexa Fluor488 (711-545-152, Jackson; 1:200), and donkey anti-mouse Cy3 (715-165-151, Jackson; 1:200). All antibodies used in this study have been fully validated, either experimentally or in the literature. Details can be found in Figure 6—figure supplement 1 and Supplementary file 1.

Statistical analysis

Request a detailed protocol

The sample size was determined using power analysis. The number of biological replicates are indicated in the figure legends. Single random sampling was used for all experiments. When comparing two groups, we used the Student’s t-test. A one-way or two-way ANOVA was used for comparison of multiple groups, followed by the Tukey's post-hoc analysis for comparisons to a single control. A value of p<0.05 was considered significant.

Data availability

All data generated or analysed during this study are included in the manuscript and supporting files.

References

    1. Hong M
    2. Kefaloyianni E
    3. Bao L
    4. Malester B
    5. Delaroche D
    6. Neubert TA
    7. Coetzee WA
    (2011) Cardiac ATP-sensitive K+ channel associates with the glycolytic enzyme complex
    FASEB Journal : Official Publication of the Federation of American Societies for Experimental Biology 25:2456–2467.
    https://doi.org/10.1096/fj.10-176669
    1. Knezl V
    2. Bacova B
    3. Kolenova L
    4. Mitasikova M
    5. Weismann P
    6. Drimal J
    7. Tribulova N
    (2008)
    Distinct lethal arrhythmias susceptibility is associated with sex-related difference in myocardial connexin-43 expression
    Neuro Endocrinology Letters 29:798–801.
  44. Book
    1. Sakmann B
    2. Neher E
    (1995) Geometric Parameters of Pipettes and Membrane Patches
    In: Sakmann B, Neher E, editors. Single-Channel Recording. Plenum Press. pp. 637–650.
    https://doi.org/10.1007/978-1-4615-7858-1_2

Decision letter

  1. Baron Chanda
    Reviewing Editor; University of Wisconsin-Madison, United States
  2. Kenton J Swartz
    Senior Editor; National Institute of Neurological Disorders and Stroke, National Institutes of Health, United States
  3. Baron Chanda
    Reviewer; University of Wisconsin-Madison, United States

In the interests of transparency, eLife publishes the most substantive revision requests and the accompanying author responses.

Acceptance summary:

Emerging evidence in the cardiac ion channel field challenges the traditional idea that treats ion channels as isolated entities. The cardiac ICD is a complex protein network, which contains ion channels and structural proteins. Its function is to maintain mechanical and electrical coupling among neighboring cardiomyocytes in the tridimentional myocardium. AnkG plays a role in Nav1.5 organization (Lowe et al., 2008; Leterrier et al., 2014) and in this manuscript, Yang provides additional evidence for NaV1.5 interactions with Kir6.2 mediated by Ankyrin-G, but not Ankyrin-B, in the cardiomyocyte. The authors investigate Nav1.5 and KATP channel distribution at the intercalated disc (ICD) and their reciprocal interaction mediated by the intracellular structural platforms. They conducted a functional analysis of such interactions using two models: transfected HEK293 cells (5 cell groups: Na+ KATP channels, Na+, KATP, and empty) and isolated rat cardiomyocytes. Their data suggests that Na+ and KATP channels are paired-located at the ICD and have a functional interaction that is mediated by the anchoring protein Ankirin-G (AnkG).

Decision letter after peer review:

Thank you for submitting your article "Ankyrin-G mediates targeting of both Na+ and KATP channels to the cardiac intercalated disc" for consideration by eLife. Your article has been reviewed by three peer reviewers, including Baron Chanda as the Reviewing Editor and Reviewer #1, and the evaluation has been overseen by Kenton Swartz as the Senior Editor.

The reviewers have discussed the reviews with one another and the Reviewing Editor has drafted this decision to help you prepare a revised submission.

Essential revisions:

1) While two different models were used, none of them accurately illustrates human physiology. It would be of interest to use hiPSC-CM or a genetically modified mouse model to address the aim of this manuscript. Furthermore, it is well known that the integrity of the ICD components is important for normal heart function and structure. An in vivo model of this AnkG-Nav1.5-KATP disruption could address its implication in cardiomyopathy or clinically relevant arrhythmia development. We ask that the authors clearly discuss the limitations of their current approach in the Discussion.

2) Related to the above point – Previous literature shows that the trafficking machinery in the HEK cells exhibits significant differences compared to cardiomyocytes (Nav1.5 E1053K in HEK cells transports to membrane but does not in the rat ventricular cardiomyocytes- Mohler et al., 2004). The authors should discuss the caveats of their findings which are primarily obtained using heterologous expression system.

3) It has been demonstrated that Ank-G and Cx43 are necessary to preserve INA amplitude, electrical coupling and intercellular adhesion strength (Sato et al., 2011). The authors should clarify the possible role of Cx43 in the protein-protein interactions they are studying: can the authors demonstrate a Cx43-independent relation between KATP, Na+ and AnK-G interaction in the cardiomyocyte? In other words, is Cx43 affected in rat ventricular cardiomyocytes?

4) The suggested impaired Na+, KATP and Ank-G macromolecular complex may lead to disruption of the ICD organization. This would lead to functional consequences on proteins, such as plakophilin-2, which regulates the function of ion channels responsible for the action potential. Is there any evidence for structural disorder of the ICD when the Nav15-KATP-AnkG complex is disrupted? Can the authors provide information on the consequences of the above interactions on action potential characteristics in rat ventricular cardiomyocytes?

5) The KCNJ11 gene encodes the inwardly rectifying potassium channel Kir6.2, which has been related mainly endocrine disorders, including diabetes mellitus. To the knowledge of this reviewer, there is no previous evidence suggesting that Kir6.2 is involved in cardiac arrhythmic disorders. The authors must be aware of the limited clinical implications of their data in terms of patient management and therapeutic options.

6) Isabelle Deschenes' lab has described quite convincingly that Nav1.5 channels form dimers that gate cooperatively. I am surprised her papers are not cited in this study and discussed in the context of the current findings.

7) The authors must include histograms of the cluster area distributions of KATP and Nav1.5 channels. Should the distributions be exponential, the authors should at least discuss the possibility of stochastic self-assembly mechanism for cluster formation. Sato et al., 2019 is a good starting point.

8) Do KATP and Nav1.5 negatively regulate their cluster size? What ratios of cDNA (Nav 1.5 to KATP) were used to transfect the HEK cells? Is there a particular ratio of the channels that has to be transfected to see the functional interaction? This part is not clear from the Materials and methods section.

Following up on that, the Materials and methods section for heterologous expression does not state whether that Ankyrin-G was transfected along the two ion channels. It is not clear why AnkG was specifically transfected for the coimmunoprecipitation experiments (Figure 6—figure supplement 3). Please clarify.

9) The authors should discuss in great detail validation of Abs.

10) The authors should provide nano ruler data to validate the lateral resolution of their STORM system. Pritchard et al., 2012 PNAS provides guidance on how to do that.

11) The authors mention that the Kir6.2/KKK mutant does not functionally interact with the Nav 1.5, however the immunoblots shown in Figure 3—figure supplement 1 shows a decrease in the Nav1.5 expression with increasing amounts of KATP 6.2-KKK cDNA transfection. This needs to be clarified. Was total cell lysate used to the experiment in Figure 3—figure supplement 1 and do the authors see a similar decrease on the surface expression as well?

12) The co-IP experiment in Figure 7—figure supplement 1 is an important piece of work considering that the authors claim that a common scaffolding protein underlies the functional interaction. Prior research does show that Kir6.2 binds to AnkB, do the authors think that the binding of Kir6.2 to AnkG also occurs through the same binding Ankyrin binding site? Please clarify.

https://doi.org/10.7554/eLife.52373.sa1

Author response

Essential revisions:

1) While two different models were used, none of them accurately illustrates human physiology. It would be of interest to use hiPSC-CM or a genetically modified mouse model to address the aim of this manuscript. Furthermore, it is well known that the integrity of the ICD components is important for normal heart function and structure. An in vivo model of this AnkG-Nav1.5-KATP disruption could address its implication in cardiomyopathy or clinically relevant arrhythmia development. We ask that the authors clearly discuss the limitations of their current approach in the Discussion.

We fully agree that an in vivo model of the AnkG/Nav1.5/KATP disruption would address its implication in cardiomyopathy or clinically relevant arrhythmia development. Unfortunately no such model is currently available. hiPSC cardiomyocytes are a poor substitute since in our experience these cells have an immature electrophysiology phenotype with little or no KATP channel expression. These cells also lack t-tubules and fully developed intercalated disks. These limitations are shared by other cardiac cellular models, such as HL-1 cells and cultured primary neonatal cardiac myocytes. A new section (“Study Limitations”) has been added to clearly discuss these limitations in the Discussion section.

2) Related to the above point – Previous literature shows that the trafficking machinery in the HEK cells exhibits significant differences compared to cardiomyocytes (Nav1.5 E1053K in HEK cells transports to membrane but does not in the rat ventricular cardiomyocytes- Mohler et al., 2004). The authors should discuss the caveats of their findings which are primarily obtained using heterologous expression system.

Our data with peptides against Ank binding sites suggest that the trafficking events that we detect in HEK293 cells also occur in isolated cardiomyocytes (Figure 7). Nevertheless, this is an excellent point that is now discussed.

3) It has been demonstrated that Ank-G and Cx43 are necessary to preserve INA amplitude, electrical coupling and intercellular adhesion strength (Sato et al., 2011). The authors should clarify the possible role of Cx43 in the protein-protein interactions they are studying: can the authors demonstrate a Cx43-independent relation between KATP, Na+ and AnK-G interaction in the cardiomyocyte? In other words, is Cx43 affected in rat ventricular cardiomyocytes?

Since the KATP, Na+ and AnK interaction can be demonstrated in HEK-293 cells, which do not express Cx43, our data demonstrate that Cx43 is not a necessary component for functional interaction. However, we have not investigated this in cardiomyocytes. Current experimental models do not allow us to directly investigate this question. The peptide experiments require isolated cardiomyocytes and it is well documented that Cx43 is rapidly internalized from the ICD following enzymatic cell isolation. An in vivo model of the AnkG/Nav1.5/KATP disruption may address this question, but such a model is not currently available. We have addressed this limitation in the revised Discussion.

4) The suggested impaired Na+, KATP and Ank-G macromolecular complex may lead to disruption of the ICD organization. This would lead to functional consequences on proteins, such as plakophilin-2, which regulates the function of ion channels responsible for the action potential. Is there any evidence for structural disorder of the ICD when the Nav15-KATP-AnkG complex is disrupted? Can the authors provide information on the consequences of the above interactions on action potential characteristics in rat ventricular cardiomyocytes?

Dr. Mohler’s laboratory has demonstrated that patients with mutations in the Nav1.5 AnkG binding domain (and disrupted trafficking of Nav1.5 to the ICD) develop arrhythmias (Brugada syndrome) but not cardiomyopathies. The latter would be expected to occur if structural disorder of the ICD occurred. Therefore, we deem it unlikely that disruption of Nav1.5/KATP localization to the ICD would result in structural disorder of the ICD. This issue is now discussed. We have not examined action potential characteristics, since we believe that these are local changes that may not reflect global electrophysiological properties of the cell. Rather, we emphasize that our findings support the growing body of evidence that cardiac ion channels do not travel and organize as lone entities, but as complexes. Our data are fully supported by recent studies, such as Gail Robertson’s finding of co-translational 'microtranslatomes' that contain both K channels and Na channels, and Pepe Jalife’s finding that K+ and Na+ channels can co-traffic in cells. We have made a better attempt in the revised manuscript to convey this message.

5) The KCNJ11 gene encodes the inwardly rectifying potassium channel Kir6.2, which has been related mainly endocrine disorders, including diabetes mellitus. To the knowledge of this reviewer, there is no previous evidence suggesting that Kir6.2 is involved in cardiac arrhythmic disorders. The authors must be aware of the limited clinical implications of their data in terms of patient management and therapeutic options.

Genetic studies are not necessarily the de facto standard for an involvement in arrhythmias. For example, a recent report of the NIH Clinical Genome Resource Consortium concluded that, when performing a systematic evaluation of the evidence supporting the causality of gene variants associated with Brugada syndrome, clinical validity was demonstrated for only one gene (SCN5A), even though over 20 genes have previously been implicated with Brugada syndrome [PMID:29959160]. In the case of KCNJ11, the overwhelmingly predominant clinical phenotype is insulin secreting disorders and arrhythmias may well be a secondary understudied phenotype. We know from pharmacological studies (with both humans and animals) that cardiac arrhythmias are a very real phenomenon associated with the use of KATP channel openers and blockers. We are therefore very aware of the potential clinical implications of our data in terms of patient management and therapeutic options. We have expanded this topic in the revised manuscript.

6) Isabelle Deschenes' lab has described quite convincingly that Nav1.5 channels form dimers that gate cooperatively. I am surprised her papers are not cited in this study and discussed in the context of the current findings.

With all due respect and at the risk of sounding ignorant, we are unclear as to the reason behind the reviewer’s surprise. The fact that sodium channels cluster together was actually first demonstrated in adult cardiac myocytes by the Delmar lab (PMID:26787348). That the channels gate cooperatively, though beautifully demonstrated by the paper of the Deschenes lab, seems outside of the realm of relevance for the present manuscript. Yet, if the reviewer considers this to be of critical importance, and if he/she were kind enough to provide us a rationale for inclusion of this paper in our Discussion, we would be happy to oblige.

7) The authors must include histograms of the cluster area distributions of KATP and Nav1.5 channels. Should the distributions be exponential, the authors should at least discuss the possibility of stochastic self-assembly mechanism for cluster formation. Sato et al., 2019 is a good starting point.

We now show these data as Figure 6—figure supplement 3, and have discussed it in the revised manuscript. We apologize for the omission of these important data.

8) Do KATP and Nav1.5 negatively regulate their cluster size? What ratios of cDNA (Nav 1.5 to KATP) were used to transfect the HEK cells? Is there a particular ratio of the channels that has to be transfected to see the functional interaction? This part is not clear from the Materials and mmethods section.

Following up on that, the Materials and methods section for heterologous expression does not state whether that Ankyrin-G was transfected along the two ion channels. It is not clear why AnkG was specifically transfected for the coimmunoprecipitation experiments (Figure 6—figure supplement 3). Please clarify.

The cDNA ratios used are now clearly indicated in the revised Materials and methods section and/or Figure legends. We have not been sufficiently clear to point out that we have not transfected cells with AnkB or AnkG, with the exception of testing the validity of the antibodies and in the co-IP experiment (Figure 7—figure supplement 1). In all other cases, we have relied on the endogenous expression of Ankyrins in HEK-293 cells or in cardiomyocytes.

9) The authors should discuss in great detail validation of Abs.

The details of antibody validation are now added as a supplement file (Supplementary file 1). Antibodies used in HEK293 cells are validated by transfected vs. untransfected cell samples (Figure 2, Figure 3—figure supplement 1 and Figure 7—figure supplement 1). Antibodies used in cardiomyocytes are validated by knockout tissue samples either in this paper (Figure 6—figure supplement 1) or from the literature.

10) The authors should provide nano ruler data to validate the lateral resolution of their STORM system. Pritchard et al, 2012 PNAS provides guidance on how to do that.

We thank the reviewer for this suggestion. Unfortunately, we are unable to find the article that the reviewer would like us to consult. PubMed does not list any article authored by Pritchard et al. that is published in PNAS in 2012 and addresses lateral resolution of STORM. That being said, the point of the reviewer (namely, to provide validation of the lateral resolution of our STORM system), is well taken. In this regard, the reviewer is invited to consult the previous work from the Rothenberg/Delmar labs (a total of 12 papers, starting in 2012; the first one in close collaboration with Dr. Coetzee) in which we have applied STORM methods. Of particular relevance to this conversation is the paper by Agullo-Pascual et al., published in Cardiovascular Research 2013 (PMID:23929525). In the Supplemental material of that paper we provide extensive methodological details of our custom-made analysis system, its technical specifications and limitations, as well as specifics of its resolution both in the X-Y and in the Z planes. In that paper (and in the technical supplement) we cite additional reference materials, including several papers of Dr. Rothenberg dealing with single-molecule localization microscopy, starting in 2010. We believe that the previous work provides enough details on the characterization of the technical aspects of our system, our methods of measurement and the resolution in the X-Y plane. We do agree that these details were not specified in the present manuscript and therefore we have included additional references and wording.

11) The authors mention that the Kir6.2/KKK mutant does not functionally interact with the Nav 1.5, however the immunoblots shown in Figure 3—figure supplement 1 shows a decrease in the Nav1.5 expression with increasing amounts of KATP 6.2-KKK cDNA transfection. This needs to be clarified. Was total cell lysate used to the experiment in Figure 3—figure supplement 1 and do the authors see a similar decrease on the surface expression as well?

The apparent decrease of Nav1.5 expression by Kir6.2-KKK is a result of the experimental conditions used. By raising the Kir6.2-KKK cDNA amount relative to that of Nav1.5, we believe that less Nav1.5 cDNA was taken up into the cell during transfection because there is more of the other cDNAs. Indeed, we have now performed an experiment which demonstrated that less Nav1.5 expression takes place even when increasing the overall amount of empty vector (pcDNA3) in the transfection reaction (Figure 3—figure supplement 1). This explanation now provided in the figure legend.

12) The co-IP experiment in Figure 7—figure supplement 1 is an important piece of work considering that the authors claim that a common scaffolding protein underlies the functional interaction. Prior research does show that Kir6.2 binds to AnkB, do the authors think that the binding of Kir6.2 to AnkG also occurs through the same binding Ankyrin binding site? Please clarify.

Our data demonstrate that peptides against a region of Kir6.2, previously identified as an AnkB binding site, and peptides against the Nav1.5 AnkG binding site have similar effects. They each affect expression of Na and KATP channels at the ICD, but not at the lateral membrane. Since AnkB is not readily detected at the ICD, our conclusion is that these peptides disrupt interaction with AnkG at the ICD. This is a plausible conclusion given the near sequence identity of these peptide sequences. We assume that the editorial panel refers to the binding site(s) within AnkB or AnkG. Unfortunately, we do not have information about the nature of these sites, not have we addressed these experimentally.

https://doi.org/10.7554/eLife.52373.sa2

Article and author information

Author details

  1. Hua-Qian Yang

    Pediatrics, NYU School of Medicine, New York, United States
    Contribution
    Conceptualization, Resources, Data curation, Software, Formal analysis, Validation, Investigation, Visualization, Methodology
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-9402-6222

  2. Marta Pérez-Hernández

    Medicine, NYU School of Medicine, New York, United States
    Contribution
    Software, Formal analysis, Validation, Investigation, Visualization, Methodology
    Competing interests
    No competing interests declared

  3. Jose Sanchez-Alonso

    National Heart and Lung Institute, Imperial Centre for Translational and Experimental Medicine, Imperial College London, London, United Kingdom
    Contribution
    Formal analysis, Investigation, Methodology
    Competing interests
    No competing interests declared

  4. Andriy Shevchuk

    Department of Medicine, Imperial College London, London, United Kingdom
    Contribution
    Data curation, Software, Formal analysis, Investigation, Methodology
    Competing interests
    No competing interests declared

  5. Julia Gorelik

    National Heart and Lung Institute, Imperial Centre for Translational and Experimental Medicine, Imperial College London, London, United Kingdom
    Contribution
    Conceptualization, Data curation, Software, Formal analysis, Supervision, Funding acquisition, Investigation, Methodology
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-1148-9158

  6. Eli Rothenberg

    Biochemistry and Molecular Pharmacology, NYU School of Medicine, New York, United States
    Contribution
    Data curation, Software, Formal analysis, Investigation, Methodology
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-1382-1380

  7. Mario Delmar

    1. Medicine, NYU School of Medicine, New York, United States
    2. Cell Biology, NYU School of Medicine, New York, United States
    Contribution
    Conceptualization, Resources, Supervision, Investigation, Methodology
    Competing interests
    No competing interests declared

  8. William A Coetzee

    1. Pediatrics, NYU School of Medicine, New York, United States
    2. Biochemistry and Molecular Pharmacology, NYU School of Medicine, New York, United States
    3. Neuroscience and Physiology, NYU School of Medicine, New York, United States
    Contribution
    Conceptualization, Resources, Data curation, Formal analysis, Supervision, Funding acquisition, Validation, Investigation, Methodology, Project administration
    For correspondence
    william.coetzee@nyu.edu
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-1522-8326

Funding

National Institutes of Health (HL126905)

  • William A Coetzee

Fondation Leducq

  • Eli Rothenberg
  • Mario Delmar

Rafael del Pino Foundation

  • Marta Pérez-Hernández

Biotechnology and Biological Sciences Research Council (BB/M022080)

  • Andriy Shevchuk

British Heart Foundation (RG/17/13/33173)

  • Jose Sanchez-Alonso
  • Julia Gorelik

American Heart Association (17POST33370050)

  • Hua-Qian Yang

National Institutes of Health (HL146514)

  • William A Coetzee

National Institutes of Health (HL134328)

  • Mario Delmar

National Institutes of Health (HL136179)

  • Mario Delmar

National Institutes of Health (HL145911)

  • Mario Delmar

National Institutes of Health (HL126802)

  • Julia Gorelik

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Acknowledgements

This work was supported by R01 HL126905 (WAC), R01 HL146514 (WAC), RO1 HL134328, RO1 HL136179, RO1 HL145911 and a Fondation Leducq Transatlantic Network (MD), an Excellence Scholarship from the Rafael del Pino Foundation (MP-H), BBSRC BB/M022080/1 (AS), ROI HL126802 (JG) British Heart Foundation RG/17/13/33173 (JG and JSA), and an AHA Postdoctoral Fellowship award 17POST33370050 (HQY).

Ethics

Animal experimentation: This study was performed in strict accordance with the recommendations in the Guide for the Care and Use of Laboratory Animals of New York University School of Medicine (protocol s17-00352).

Senior Editor

  1. Kenton J Swartz, National Institute of Neurological Disorders and Stroke, National Institutes of Health, United States

Reviewing Editor

  1. Baron Chanda, University of Wisconsin-Madison, United States

Reviewer

  1. Baron Chanda, University of Wisconsin-Madison, United States

Publication history

  1. Received: October 2, 2019
  2. Accepted: January 11, 2020
  3. Accepted Manuscript published: January 14, 2020 (version 1)
  4. Version of Record published: January 24, 2020 (version 2)

Copyright

© 2020, Yang et al.

This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.

Metrics

  • 1,506
    Page views
  • 285
    Downloads
  • 16
    Citations

Article citation count generated by polling the highest count across the following sources: Crossref, PubMed Central, Scopus.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. Hua-Qian Yang
  2. Marta Pérez-Hernández
  3. Jose Sanchez-Alonso
  4. Andriy Shevchuk
  5. Julia Gorelik
  6. Eli Rothenberg
  7. Mario Delmar
  8. William A Coetzee
(2020)
Ankyrin-G mediates targeting of both Na+ and KATP channels to the rat cardiac intercalated disc
eLife 9:e52373.
https://doi.org/10.7554/eLife.52373

Categories and tags

Research organism

Further reading

    1. Medicine

    An herbal drug combination identified by knowledge graph alleviates the clinical symptoms of plasma cell mastitis patients: A nonrandomized controlled trial

    Caigang Liu, Hong Yu ... Yongliang Yang
    Research Article Updated

    Background:

    Plasma cell mastitis (PCM) is a nonbacterial breast inflammation with severe and intense clinical manifestation, yet treatment methods for PCM are still rather limited. Although the mechanism of PCM remains unclear, mounting evidence suggests that the dysregulation of immune system is closely associated with the pathogenesis of PCM. Drug combinations or combination therapy could exert improved efficacy and reduced toxicity by hitting multiple discrete cellular targets.

    Methods:

    We have developed a knowledge graph architecture toward immunotherapy and systematic immunity that consists of herbal drug–target interactions with a novel scoring system to select drug combinations based on target-hitting rates and phenotype relativeness. To this end, we employed this knowledge graph to identify an herbal drug combination for PCM and we subsequently evaluated the efficacy of the herbal drug combination in clinical trial.

    Results:

    Our clinical data suggests that the herbal drug combination could significantly reduce the serum level of various inflammatory cytokines, downregulate serum IgA and IgG level, reduce the recurrence rate, and reverse the clinical symptoms of PCM patients with improvements in general health status.

    Conclusions:

    In summary, we reported that an herbal drug combination identified by knowledge graph can alleviate the clinical symptoms of PCM patients. We demonstrated that the herbal drug combination holds great promise as an effective remedy for PCM, acting through the regulation of immunoinflammatory pathways and improvement of systematic immune level. In particular, the herbal drug combination could significantly reduce the recurrence rate of PCM, a major obstacle to PCM treatment. Our data suggests that the herbal drug combination is expected to feature prominently in future PCM treatment.

    Funding:

    C. Liu’s lab was supported by grants from the Public Health Science and Technology Project of Shenyang (grant: 22-321-32-18); Y. Yang’s laboratory was supported by the National Natural Science Foundation of China (grant: 81874301), the Fundamental Research Funds for Central University (grant: DUT22YG122), and the Key Research project of ‘be Recruited and be in Command’ in Liaoning Province (2021JH1/10400050).

    Clinical trial number:

    NCT05530226.

    1. Genetics and Genomics
    2. Medicine

    Phenome-wide Mendelian randomization study of plasma triglyceride levels and 2,600 disease traits

    Joshua K Park, Shantanu Bafna ... Ron Do
    Research Article

    Background: Causality between plasma triglyceride (TG) levels and atherosclerotic cardiovascular disease (ASCVD) risk remains controversial despite more than four decades of study and two recent landmark trials, STRENGTH and REDUCE-IT. Further unclear is the association between TG levels and non-atherosclerotic diseases across organ systems.

    Methods: Here, we conducted a phenome-wide, two-sample Mendelian randomization (MR) analysis using inverse-variance weighted (IVW) regression to systematically infer the causal effects of plasma TG levels on 2,600 disease traits in the European ancestry population of UK Biobank. For replication, we externally tested 221 nominally significant associations (p < 0.05) in an independent cohort from FinnGen. To account for potential horizontal pleiotropy and the influence of invalid instrumental variables, we performed sensitivity analyses using MR-Egger regression, weighted median estimator, and MR-PRESSO. Finally, we used multivariable MR controlling for correlated lipid fractions to distinguish the independent effect of plasma TG levels.

    Results: Our results identified 7 disease traits reaching Bonferroni-corrected significance in both the discovery (p < 1.92 × 10-5) and replication analyses (p < 2.26 × 10-4), suggesting a causal relationship between plasma TG levels and ASCVDs, including coronary artery disease (OR 1.33, 95% CI 1.24-1.43, p = 2.47 × 10-13). We also identified 12 disease traits that were Bonferroni-significant in the discovery or replication analysis and at least nominally significant in the other analysis (p < 0.05), identifying plasma TG levels as a novel potential risk factor for 9 non-ASCVD diseases, including uterine leiomyoma (OR 1.19, 95% CI 1.10-1.29, p = 1.17 × 10-5).

    Conclusions: Taking a phenome-wide, two-sample MR approach, we identified causal associations between plasma TG levels and 19 disease traits across organ systems. Our findings suggest unrealized drug repurposing opportunities or adverse effects related to approved and emerging TG-lowering agents, as well as mechanistic insights for future studies.

    Funding: RD is supported by the National Institute of General Medical Sciences of the National Institutes of Health (NIH) (R35-GM124836) and the National Heart, Lung, and Blood Institute of the NIH (R01-HL139865 and R01-HL155915).

    1. Medicine

    Study of efficacy and longevity of immune response to 3rd and 4th doses of COVID-19 vaccines in patients with cancer: a single arm clinical trial

    Astha Thakkar, Kith Pradhan ... Balazs Halmos
    Research Article

    Background: Cancer patients show increased morbidity with COVID-19 and need effective immunization strategies. Many healthcare regulatory agencies recommend administering 'booster' doses of COVID-19 vaccines beyond the standard 2-dose series, for this group of patients. Therefore, studying the efficacy of these additional vaccine doses against SARS-CoV-2 and variants of concern is of utmost importance in this immunocompromised patient population.

    Methods: We conducted a prospective single arm clinical trial enrolling patients with cancer that had received two doses of mRNA or one dose of AD26.CoV2.S vaccine and administered a 3rd dose of mRNA vaccine. We further enrolled patients that had no or low responses to three mRNA COVID vaccines and assessed the efficacy of a 4th dose of mRNA vaccine. Efficacy was assessed by changes in anti-spike antibody, T-cell activity and neutralization activity were again assessed at baseline and 4 weeks.

    Results: We demonstrate that a 3rd dose of COVID-19 vaccine leads to seroconversion in 57% of patients that were seronegative after primary vaccination series. The immune response is durable as assessed by anti-S antibody titers, T-cell activity and neutralization activity against wild-type SARS-CoV2 and BA1.1.529 at 6 months of follow up. A subset of severely immunocompromised hematologic malignancy patients that were unable to mount an adequate immune response (titer <1000 AU/mL) after the 3rd dose and were treated with a 4th dose in a prospective clinical trial which led to adequate immune-boost in 67% of patients. Low baseline IgM levels and CD19 counts were associated with inadequate seroconversion. Booster doses induced limited neutralization activity against the Omicron variant.

    Conclusions: These results indicate that 3rd dose of COVID vaccine induces durable immunity in cancer patients and an additional dose can further stimulate immunity in a subset of patients with inadequate response.

    Funding: Leukemia lymphoma society, National Cancer Institute.

    Clinical trial identifier: NCT05016622.