Functionally coupled ion channels begin co-assembling at the start of their synthesis

To guide the reader and prevent confusion on the terms used, we introduce the following nomenclature, which is also illustrated in Figure 1. Molecular complex: an array of several polypeptides with a defined function. In our case, a BK channel is a molecular complex of four α-subunits whose function is to permeate ions. Homo-cluster: we define a homo-cluster as the accumulation of proteins. In our work, a homo-cluster refers to the accumulation of BK channels or the accumulation of calcium channels.

Figure 1

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Hetero-cluster: we define a hetero-cluster as the collection of different types of proteins that facilitate functional coupling and compartmentalization of a signaling complex. In the present work, hetero-cluster refers to a coordinated collection of BK and Ca_V channels. It is also used to refer to the assembly of homo-clusters of BK with homo-clusters of Ca_V channels.

BK and Ca_V hetero-clusters have been observed at the plasma membrane (Berkefeld et al., 2006; Vivas et al., 2017; Prakriya and Lingle, 2000). However, a clear understanding of when and how BK and Ca_V hetero-clusters assemble is lacking. A simple mechanism proposes that these hetero-clusters organize only at the plasma membrane. Here, we tested the alternative hypothesis of BK and Ca_V assembling inside the cell (Figure 2A). To test this idea, we used proximity ligation assay (PLA) and antibodies against BK and Ca_V1.3 channels. When these antibodies are within 40 nm of each other, PLA ligation and amplification can occur, resulting in the formation of fluorescent puncta (Figure 2B), here referred to as PLA puncta. Hence, the PLA puncta in Figure 2C represent BK and Ca_V1.3 hetero-clusters. To confirm specificity, a negative control was performed by probing only for BK using the primary antibody, ensuring that detected signals were not due to nonspecific binding or background fluorescence. We first analyzed Z-projections, in which all the puncta in the cell volume are added, and found a density of 5.8±1.0/10 μm². In a different experiment, we analyzed the puncta density for each focal plane of the cell (step size of 300 nm) and compared the puncta at the plasma membrane to the rest of the cell. We visualized the plasma membrane with a biological sensor tagged with GFP (PH-PLCδ-GFP) and then probed it with an antibody against GFP (Figure 2E). By analyzing the GFP signal, we created a mask that represented the plasma membrane. The mask served to distinguish between the PLA puncta located inside the cell and those at the plasma membrane, allowing us to calculate the number of PLA puncta at the plasma membrane. To our surprise, we found a significant number of puncta localized inside the cell. 46 ± 3% of the puncta were localized intracellularly, whereas 54 ± 3% were at the plasma membrane. This finding is consistent with our supposition that BK and Ca_V1.3 channels colocalize in the cell.

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We next investigated the identity of the intracellular membranes where these PLA puncta were found. A large component of intracellular membranes in the cell is the endoplasmic reticulum (ER), where channels are inserted after translation. To determine whether BK and Ca_V1.3 associate in the ER (Figure 3A), we combined PLA with immunodetection. As before, PLA probed for BK and Ca_V1.3 hetero-clusters, while a (Contreras et al., 2013) KDEL-moxGFP label identified the ER (Figure 3B). To avoid disruption of organelle architecture, we used the monomeric mox version of KDEL-GFP, which is optimized to reduce oligomerization in the ER environment (Costantini et al., 2015). Neither overexpression of KDEL-moxGFP nor fixation altered the ER structure as the tubule width remained around 150 nm for either condition (Figure 3C), a value in agreement with the literature (Georgiades et al., 2017; Nixon-Abell et al., 2016). To assess the percentage of PLA puncta colocalizing with the ER, we employed two different cell lines: our overexpression system (tsA-201 cells) and a rat insulinoma cell line (INS-1) that expresses BK and Ca_V1.3 channels endogenously. In this and following experiments, we analyze one focal plane, in the middle of the cell, to quantify PLA puncta colocalization with ER membrane. Figure 3D shows PLA puncta in the same space as the ER. Comparing the overexpression and endogenous systems, 63 ± 3% vs 50 ± 6% of total PLA puncta were localized at the ER (Figure 3E). To determine whether the observed colocalization between BK-Ca_V1.3 hetero-clusters and the ER was not simply due to the extensive spatial coverage of ER labeling, we labeled ER exit sites using Sec16-GFP and probed for hetero-clusters with PLA. This approach enabled us to test whether the hetero-clusters were preferentially localized to ER exit sites, which are specialized trafficking hubs that mediate cargo selection and direct proteins from the ER into the secretory pathway. In contrast to the more expansive ER network, which supports protein synthesis and folding, ER exit sites ensure efficient and selective export of proteins to their target destinations. By quantifying the proportion of BK and Ca_V1.3 hetero-clusters relative to total channel expression at ER exit sites, we found 28 ± 3% colocalization in tsA-201 cells and 11 ± 2% in INS-1 cells (Figure 3F). While the percentage of colocalization between hetero-clusters and the ER or ER exit sites alone cannot be directly compared to infer trafficking dynamics, these findings reinforce the conclusion that hetero-clusters reside within the ER and suggest that BK and Ca_V1.3 channels traffic together through the ER and exit in coordination.

Figure 3

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Channels are modified in the Golgi after synthesis (Figure 4A), so we asked whether PLA puncta formed by BK and Ca_V1.3 hetero-clusters can be found in the Golgi. Using the same strategy, we labeled Golgi with Gal-T-mEGFP (Figure 4B) and detected BK-Ca_V1.3 hetero-clusters using PLA. To confirm that the overexpressed Gal-T-mEGFP labels the Golgi specifically without altering its structure, we compared the region detected by the antibody against GFP to the region detected by a primary antibody against the Golgi protein 58K (Figure 4C). 58K is a specific peripheral protein that localizes to the cytosolic face of Golgi (Bashour and Bloom, 1998). The overlay shows that the GFP signal labels the same region as the antibody against 58K. When assessing the presence of BK-Ca_V1.3 hetero-clusters in the Golgi, we found that 31 ± 5% of PLA puncta were localized at the Golgi in the overexpression system and 25 ± 4% in the endogenous cell model (Figure 4E).

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We performed controls to confirm that the formation of hetero-clusters between the two channels was not coincidental but rather the result of structural coupling. We tested the formation of PLA puncta between BK channels and the Golgi protein 58K. We also tested for Ca_V1.3 and 58K. We did not find PLA puncta when the proximity between the channels and 58K was probed (Figure 4F), supporting the idea that PLA puncta between BK and Ca_V1.3 channels found at the Golgi represent specific coupling. We selected the Golgi as a control because it represents the final stage of protein trafficking, ensuring that hetero-cluster interactions observed at this point reflect specificity maintained throughout earlier trafficking steps, including within the ER. As an additional control, we tested the formation of PLA puncta between Ca_V1.3 channels and RyR₂, a protein localized in the ER. The number of PLA puncta between Ca_V1.3 and RyR₂ was significantly lower than the number observed between Ca_V1.3 and BK channels (Figure 4—figure supplement 1), further supporting the specificity of BK-Ca_V1.3 interactions.

It is important to clarify that the percentages provided in this work cannot be added up to understand the distribution of hetero-clusters along the biosynthetic pathway of the channels. The percentage in each membrane compartment was compared to the total percentage of hetero-clusters observed in each cell for that particular experiment. Therefore, there is expected overlap between our measurements due to (1) optical resolution and (2) the effect of not comparing all the organelles in the same cell. Considering these limitations, we interpreted our results as follows: about one half of hetero-clusters are found inside the cell. The other half corresponds to hetero-clusters at the plasma membrane. From the half inside the cell, roughly one third of hetero-clusters is found in the Golgi, and another third is found in ER exit sites (Figure 4G). The remaining hetero-clusters are found in other regions of the ER and in membranes that we did not probe, such as vesicles. Finally, a key limitation of this approach is that we cannot quantify the proportion of total BK or Ca_V1.3 channels engaged in hetero-clusters within each compartment. The PLA method provides proximity-based detection, which reflects relative localization rather than absolute channel abundance within individual organelles.

How is it that BK and Ca_V1.3 proteins come in close proximity in membranes of the ER, ER exit sites, and the Golgi? To explore the origins of the initial association, we hypothesized that the two proteins are translated near each other, which could be detected as the colocalization of their mRNAs (Figure 5A and B). The experiment was designed to detect single mRNA molecules from INS-1 cells in culture. We performed multiplex in situ hybridization experiments using an RNAscope fluorescence detection kit to be able to image three mRNAs simultaneously in the same cell and acquired the images in a confocal microscope with high resolution. To rigorously assess the specificity of this potential mRNA-level organization, we used multiple internal controls. GAPDH mRNA, a highly expressed housekeeping gene with no known spatial coordination with channel mRNAs, served as a baseline control for nonspecific colocalization due to transcript abundance. To evaluate whether the spatial proximity between BK mRNA (KCNMA1) and Ca_V1.3 mRNA (CACNA1D) was unique to functionally coupled channels, we also tested for Na_V1.7 mRNA (SCN9A), a transmembrane sodium channel expressed in INS-1 cells but not functionally associated with BK. This allowed us to determine whether the observed colocalization reflected a specific biological relationship rather than shared expression context. Finally, to test whether this proximity might extend to other calcium sources relevant to BK activation, we probed the mRNA of ryanodine receptor 2 (RyR2), another Ca²⁺ channel known to interact structurally with BK channels (Lifshitz et al., 2011). Together, these controls were chosen to distinguish specific mRNA colocalization patterns from random spatial proximity, shared subcellular distribution, or gene expression level artifacts. Figure 5—figure supplement 2 shows images completely void of fluorescent signal from INS-1 cells probed for bacterial mRNA (negative control, Figure 5—figure supplement 2A) and shows images of INS-1 cells probed for mammalian mRNAs expected to be in these cells (positive control, Figure 5—figure supplement 2B). We confirmed the specificity of the probes by performing in situ hybridization against KCNMA1, CACNA1D, RyR2, and SCN9A in non-transfected cell lines (Figure 5—figure supplement 2C and D).

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Probes against GAPDH mRNA were used as a control in the same cells that we probed for KCNMA1 and CACNA1D using the multiplex capability of this design. Transcripts were detected at different expression levels. GAPDH and CACNA1D mRNAs were more abundant (134 and 33 mRNA/100 μm², respectively) than KCNMA1 mRNA (12 mRNA/100 μm², Figure 5C). Interestingly, the abundance of KCNMA1 transcripts correlated more with the abundance of CACNA1D transcripts than with the abundance of GAPDH, though with a modest R² value (Figure 5D and E). Furthermore, KCNMA1 and CACNA1D mRNA colocalized by 60 ± 4%, which was 20% more than with GAPDH mRNA (Figure 5F). As an additional control and to rule out the potential influence of differences between CACNA1D and KCNMA1 abundance, we assessed CACNA1D colocalization against randomized, computer-generated KCNMA1 mRNA signals, where localization was randomized while maintaining the same overall transcript count. The significantly lower (20%) colocalization observed in scrambled conditions compared to genuine BK-Cav1.3 mRNA interactions confirms that proximity is not an artifact of expression levels but reflects a specific spatial association. These results suggest that some fraction of mRNAs for BK and Ca_V1.3 channels are translated nearby, so the channel proteins potentially could be inserted into the same regions of the ER. We suggest that the newly synthesized proteins remain together during trafficking through the ER and the Golgi.

Next, we compared the proximity between KCNMA1 and SCN9A. We detected SCN9A in the same cells where KCNMA1 was found (Figure 6A). The colocalization between KCNMA1 and SCN9A was only 18 ± 2% (Figure 6C), which was less than what was observed with KCNMA1 and CACNA1D (60%, Figure 5F). Notably, we observed comparable levels of co-localization between KCNMA1 and SCN9A transcripts in both directions (data not shown), with no statistically significant difference. These findings support the specificity of mRNA co-localization and that KCNMA1 tends to localize closer to CACNA1D than to SCN9A or GAPDH, supporting the specificity of KCNMA1 and CACNA1D mRNA association.

Figure 6

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With the goal of understanding if this concept could apply to other channels, we used the same approach to test a second protein known to provide calcium for BK channel opening. Similar to the coupling between BK and Ca_V1.3 channels, RyR2 also can be structurally coupled to BK channels (Lifshitz et al., 2011). Figure 6B shows high-resolution images of single-molecule in situ hybridization for RyR2 probed together with KCNMA1 in INS-1 cells. In the same population of cells, KCNMA1 and RyR2 colocalization was 27 ± 3%, which is 1.5 times that with SCN9A mRNA. We also assessed RyR2 colocalization with randomized, computer-generated KCNMA1 mRNA signals. We found that colocalization between randomized KCNMA1 and genuine RyR2 was 87% less colocalized compared to the analysis of genuine KCNMA1 and genuine RyR2 (Figure 6C), suggesting that KCNMA1 not only colocalizes with CACNA1D but also with mRNA of other known calcium sources.

To further investigate whether KCNMA1 and CACNA1D are localized in regions of active translation (Figure 7A), we performed RNAscope targeting KCNMA1 and CACNA1D alongside immunostaining for BK protein. This strategy enabled us to visualize transcript-protein colocalization in INS-1 cells with subcellular resolution.

Figure 7

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By directly evaluating sites of active BK translation, we aimed to determine whether newly synthesized BK protein colocalized with CACNA1D mRNA signals (Figure 7A). Confocal imaging revealed distinct micro-translational complexes where KCNMA1 mRNA puncta overlapped with BK protein signals and were located adjacent to CACNA1D mRNA (Figure 7B). Quantitative analysis showed that 71 ± 3% of all KCNMA1 colocalized with BK protein signal, which means that they are in active translation. Interestingly, 69 ± 3% of the KCNMA1 in active translation colocalized with CACNA1D (Figure 7C), supporting the existence of functional micro-translational complexes between BK and Ca_V1.3 channels.

We previously showed the organization of BK and Ca_V1.3 channels in hetero-clusters in tsA-201 cells and neurons, including hippocampal and sympathetic motor neurons (Vivas et al., 2017). Our present study utilizes INS-1 cells. We detected single microscopy and determined their degree of colocalization. Figure 8A shows a representative image of the localizations of antibodies against BK and Ca_V1.3 channels. Maps were rendered at 5 nm, the pixel size for the images presented. BK-positive pixels formed multi-pixel aggregates, which have been interpreted as homo-clusters of molecules in INS-1 cells. It is important to note that this technique does not allow us to distinguish between labeling of four BK α-subunits within a tetramer and labeling of multiple BK channels in a cluster. Hence, particles smaller than ~1680 nm² may represent either a single tetramer or a cluster. This limitation applies to Figures 8C and 9D and does not affect measurements of BK-Ca_V1.3 proximity. Ca_V1.3 channels also formed homo-clusters. When looking at the formation of BK and Ca_V1.3 hetero-clusters, no fixed geometry or stoichiometry was observed. On the contrary, maps showed a distribution of distances between BK and Ca_V1.3 detected pixels. In some cases, BK and Ca_V1.3 channels were perfectly overlapping, as if the detection of the antibodies could not be separated by the 20 nm resolution. In other cases, BK and Ca_V1.3 channels were adjacent (less than 5 nm), and in other cases, BK homo-clusters were surrounded by a variable number of Ca_V1.3 channels.

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Figure 9

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To provide a more quantitative description of the maps, we measured cluster density, cluster size, and colocalization. We used the particle analysis tool of the software ImageJ for these measurements. In this analysis, a particle represents positive pixels irrespective of the number of pixels composed. INS-1 cells showed four times as many Ca_V1.3 particles as BK particles (Figure 8B). Figure 8C shows the frequency distribution of particle size, where the median area is 1691 nm² for BK and 975 nm² for Ca_V1.3. The colocalization between BK and Ca_V1.3 clusters (Figure 8D) was 7.5%, a value higher than that obtained from scrambled image controls. Notably, 37±3% BK channels are at 200 nm or less from one or more Ca_V1.3, while 15 ± 2% of Ca_V1.3 channels are at 200 nm or less from one or more BK (Figure 8—figure supplement 1A). Furthermore, the distribution of the nearest distance between BK and Ca_V1.3 in INS-1 cells (Figure 8—figure supplement 1B, magenta) shows a large proportion of BK channels (around 40%) at <50 nm from any Ca_V1.3 channels. Together, these results suggest that INS-1 cells also exhibit nanodomains containing BK-Ca_V1.3 hetero-clusters at the plasma membrane.

In light of our results, our current model is that BK and Ca_V1.3 hetero-clusters form prior to their insertion into the plasma membrane. One prediction based on this model is that channels inserted in the plasma membrane would appear as hetero-clusters already at early time points after the start of their synthesis. To test this prediction, we transfected tsA-201 cells with BK and Ca_V1.3 channels and performed a chase experiment to detect their presence at the plasma membrane using super-resolution microscopy. We measured particle size, density, and colocalization at 18, 24, and 48 hr after transfection. Notably, although the channels were transfected simultaneously, BK particles were detected in the plasma membrane 18 hr after transfection, whereas Ca_V1.3 particles were detected 24 hr after transfection (Figure 9A–C). The distribution of BK and Ca_V1.3 particle size did not change with the time after transfection (Figure 9D and E), in agreement with Sato et al., 2019.

In support of our prediction, we found particles of Ca_V1.3 near BK particles as soon as the expression of Ca_V1.3 channels was detected in the plasma membrane (24 hr after transfection, enlarged Figure 9B). To test this hypothesis further, we compared plots of localization preference at 24 and 48 hr. These plots were constructed by measuring the percentage of Ca_V1.3 area occupying concentric regions of 20 nm width around BK particles. Values were normalized to the percentage of colocalization found at 200 nm from BK. Figure 9F shows that the localization preference plots are identical at 24 and 48 hr, consistent with the hypothesis that both channels are inserted together into the plasma membrane already as hetero-clusters.

Previous work from our group has revealed the organization of hetero-clusters of large-conductance calcium-activated potassium (BK) channels and voltage-gated calcium channels, particularly Ca_V1.3, within nanodomains (Vivas et al., 2017). This spatial organization is crucial for the functional coupling that enables BK channels to respond promptly to calcium influx, thereby modulating cellular excitability. While physical details of BK-Ca_V1.3 interactions are not fully elucidated, the evidence suggests that BK channels interact with both the Ca_V α1-subunit and its auxiliary subunits (Rehak et al., 2013; Zhang et al., 2018).

Our findings highlight the intracellular assembly of BK-Ca_V1.3 hetero-clusters, though limitations in resolution and organelle-specific analysis prevent precise quantification of the proportion of intracellular complexes that ultimately persist on the cell surface. While our data confirms that hetero-clusters form before reaching the plasma membrane, it remains unclear whether all intracellular hetero-clusters transition intact to the membrane or undergo rearrangement or disassembly upon insertion. Future studies utilizing live-cell tracking and high-resolution imaging will be valuable in elucidating the fate and stability of these complexes after membrane insertion.

A stochastic model of ion channel homo-cluster formation in the plasma membrane proposes that random yet probabilistic interactions between ion channels contribute to their formation (Sato et al., 2019). These clusters are stabilized and organized within specific membrane regions through biophysical mechanisms such as membrane curvature. Recent findings on spatial organization of G-protein-coupled receptors provide additional support for this framework, demonstrating that the coupling of membrane proteins to the curvature of the plasma membrane acts as a driving force for their clustering into functional domains (Kockelkoren et al., 2024). Yet, the mechanisms regulating the spatial organization of hetero-clusters remain less known.

The colocalization of BK and Ca_V1.3 channels in the ER and at ER exit sites before reaching the Golgi suggests a coordinated trafficking mechanism that facilitates the formation of multichannel complexes. This functional coupling is crucial for calcium signaling and membrane excitability (Berkefeld et al., 2010; Loane et al., 2007). Given the distinct roles of these compartments, colocalization at the ER and ER exit sites may reflect transient proximity rather than stable interactions. Their presence in the Golgi further suggests that posttranslational modifications and additional assembly steps occur before plasma membrane transport, providing further insight into hetero-cluster maturation and sorting events. By examining BK-Ca_V1.3 hetero-cluster distribution across these trafficking compartments, we ensure that observed colocalization patterns are considered within a broader framework of intracellular transport mechanisms (Boncompain and Perez, 2013). Previous studies indicate that ER exit sites exhibit variability in cargo retention and sorting efficiency (Kurokawa and Nakano, 2019), emphasizing the need for careful evaluation of colocalization data. Accounting for these complexities allows for a robust assessment of signaling complexes formation and trafficking pathways.

BK surface expression in the absence of Ca_V1.3 indicates that its trafficking does not strictly rely on Ca_V1.3-mediated interactions. Since BK channels can be activated by multiple calcium sources, their presence in intracellular compartments suggests that their surface expression is governed by intrinsic trafficking mechanisms rather than direct calcium-dependent regulation. While some BK and Ca_V1.3 hetero-clusters assemble into signaling complexes intracellularly, other BK channels follow independent trafficking pathways, demonstrating that complex formation is not obligatory for all BK channels. Differences in their transport kinetics further reinforce the idea that their intracellular trafficking is regulated through distinct mechanisms. Studies have shown that BK channels can traffic independently of Ca_V1.3, relying on alternative calcium sources for activation (Shah et al., 2021; Chen et al., 2023c). Additionally, Ca_V1.3 exhibits slower synthesis and trafficking kinetics than BK, emphasizing that their intracellular transport may not always be coordinated. These findings suggest that BK and Ca_V1.3 exhibit both independent and coordinated trafficking behaviors, influencing their spatial organization and functional interactions. Future experiments using inducible constructs to precisely control transcription timing will enable more precise quantification of hetero-cluster formation in the ER compartment prior to plasma membrane insertion and reduce the variability introduced by differences in expression timing after plasmid transfection.

The colocalization of mRNAs encoding BK and Ca_V1.3 channels suggests a coordinated translation mechanism that facilitates their proximal synthesis and subsequent assembly into functional complexes. As a mechanism, mRNA localization enhances protein enrichment at functional sites, coordinating with translational control to position ion channels at specific subcellular domains; ion channel positioning is especially critical for neurons and cardiomyocytes (Vacher et al., 2008; Medioni et al., 2012). By synthesizing these channels in close proximity, channels can be efficiently assembled into functional units, making this process crucial for precise targeting and trafficking of ion channels to specific subcellular domains, thereby ensuring proper cellular function and efficient signal transduction (Blandin et al., 2021; Dai, 2023; Wang et al., 2023). Disruption in mRNA localization or protein trafficking can lead to ion channel mislocalization, resulting in altered cellular function and disease (Wang et al., 2016; Jameson et al., 2023). In cardiac cells, precise trafficking of ion channels to specific membrane subdomains is crucial for maintaining normal electrical and mechanical functions, and its disruption contributes to heart disease and arrhythmias (Anderson et al., 2006; Smyth and Shaw, 2010; Basheer and Shaw, 2016). Similarly, in neurons, the localization and translation of mRNA at synaptic sites are essential for synaptic plasticity, and disturbances can lead to neurological disorders (Eliscovich et al., 2017; Yoon et al., 2016).

The potential co-translational association of transcripts encoding BK and Ca_V1.3 ion channels, as well as other known calcium sources like RyR2, may serve as a mechanism to ensure the precise stoichiometry and assembly of functional channel complexes. It is important to note that while our data suggest mRNA coordination, additional experiments are required to directly assess co-translation. In parallel, the spatial organization of BK channels with other calcium sources such as RyR2—particularly in airway myocytes—has been shown to facilitate efficient BK activation by localized Ca²⁺ sparks (Rehak et al., 2013). Co-translational association of transcripts encoding K_V1.3 channels was the first example in which the interaction of nascent K_V1.3 N-termini facilitates proper tertiary and quaternary structure required for oligomerization (Robinson and Deutsch, 2005; Tu and Deutsch, 1999). Similarly, co-translational heteromeric association of hERG1a and hERG1b subunits ensures that cardiac IK_r currents exhibit the appropriate biophysical properties and magnitude necessary for normal ventricular action potential shaping (Liu et al., 2016). The precise mechanism by which BK transcripts are associated with the transcripts of calcium sources like Ca_V1.3 and RyR2 channels remains to be elucidated. While it is conceivable that complementary base pairing or tertiary structural interactions play a role, RNA-binding proteins (RBPs) are likely key mediators of these associations.

This study provides novel insights into the organization of BK and Ca_V1.3 channels in hetero-clusters, emphasizing their assembly within the ER, at ER exit sites, and within the Golgi. Our findings suggest that BK and Ca_V1.3 channels begin assembling intracellularly before reaching the plasma membrane, shaping their spatial organization and potentially facilitating functional coupling. While this suggests a coordinated process that may contribute to functional coupling, further investigation is needed to determine the extent to which these hetero-clusters persist upon membrane insertion. While our study advances the understanding of BK and Ca_V1.3 hetero-cluster assembly, several key questions remain unanswered. What molecular machinery drives this colocalization at the mRNA and protein level? How do disruptions to complex assembly contribute to channelopathies and related diseases? Additionally, a deeper investigation into the role of RBPs in facilitating transcript association and localized translation is warranted.

We used tsA-201 cells to co-express BK and Ca_V1.3 channels heterologously. Cells were grown in DMEM (Gibco) supplemented with 10% fetal bovine serum and 0.2% penicillin/streptomycin. We used rat insulinoma (INS-1) cells to study endogenous levels of transcripts and proteins of channels. INS-1 cells were cultured in RPMI high glutamate medium (Gibco) with 10% fetal bovine serum, 0.2% penicillin/streptomycin, 10 mM HEPES (Gibco), 1 mM sodium pyruvate (Gibco), and 50 μM 2-mercaptoethanol. Both cell types were passaged twice a week and incubated in 5% CO₂ at 37°C. Cell lines tsA-201 (human) and INS-1 (rat) were purchased from Sigma. According to the manufacturer, these cell lines were authenticated and tested for mycoplasma contamination prior to shipment. No additional authentication or contamination testing was performed by the authors.

Cells were transfected with 0.1–0.4 μg DNA per plasmid and plated for 24 hr on poly-D-lysine-coated coverslips. Lipofectamine 3000 (Invitrogen, RRID:L30000) was used for the transfection. DNA clones of Ca_V1.3, BK channels, PH-PLCδ GFP, ER moxGFP, pmGFP-Sec16S, and Golgi-mGFP were obtained from Addgene (RRID:SCR_002037). The Ca_V1.3 α-subunit construct used in our study corresponds to the rat Ca_V1.3e splice variant containing exons 8a, 11, 31b, and 42a, with a deletion of exon 32. The BK channel construct corresponds to the VYR splice variant of the mouse BKα-subunit (KCNMA1). Auxiliary subunits for Ca_V1.3 channels, Ca_Vβ3 and Ca_Vα2δ1 (from Diane Lipscombe, Brown University, RI, USA), were transfected as well. No BK channel auxiliary subunits were transfected.

Ca_V1.3 channels were immuno-detected with a rabbit primary antibody recognizing residues 809–825 located at the intracellular II-III loop of the channel (DNKVTIDDYQEEAEDKD), kindly provided by Drs. William Catterall and Ruth Westenbroek (Hell et al., 1993). BK channels were detected using the anti-Slo1 mouse monoclonal antibody clone L6/60. The goat polyclonal GFP antibody was against the recombinant full-length protein corresponding to Aequorea victoria GFP. Anti-58K Golgi protein antibody was used to mark the Golgi. Specificity of antibodies was tested in untransfected tsA-201 cells (Figure 2—figure supplement 1). The secondary antibodies tagged with Alexa Fluor dyes were donkey anti-mouse Alexa Fluor 647, donkey anti-rabbit Alexa Fluor 555, donkey anti-goat Alexa Fluor 488 (Molecular Probes).

Cells were fixed with freshly prepared 4% paraformaldehyde for 10 min. After washing, aldehydes were reduced with 0.1% NaBH₄ for 5 min and then washed again. Nonspecific binding was blocked with 3% bovine serum albumin (Thermo Scientific). Cells were permeabilized with 0.25% vol/vol Triton X-100 in PBS for 1 hr. Primary antibodies were used at 10 μg/ml in blocking solution and incubated overnight at 4°C. After washing, secondary antibodies at 2 μg/ml were incubated for 1 hr at 21°C. Washing steps indicated in all methods include 3 cycles of rinsing and rocking for 5 min with PBS at 21°C. Cells were imaged using an inverted AiryScan microscope or an ONI Nanoimager with super-resolution capabilities, in total internal reflection fluorescence mode, and with a Z-resolution of 50 nm.

Cells were fixed with freshly prepared 4% paraformaldehyde for 10 min. After washing, aldehydes were reduced with 50 mM glycine for 15 min. After another round of washes, PLA was performed according to the manufacturer’s instructions (Duolink In Situ Red Starter Kit). Cells were blocked and permeabilized with Duolink blocking solution. Primary antibodies were used at 10 μg/ml in Duolink antibody diluent and incubated overnight at 4°C. The Duolink In Situ PLA probe anti-rabbit PLUS and anti-mouse MINUS were used as secondary antibodies, followed by ligation and amplification. For PLA combined with immunostaining, PLA was followed by a secondary antibody incubation with Alexa Fluor 488 at 2 μg/ml for 1 hr at 21°C. Since GFP fluorescence fades significantly during the PLA protocol, resulting in reduced signal intensity and poor image resolution, GFP was labeled using an antibody rather than relying on its intrinsic fluorescence. Coverslips were mounted using ProLong Gold Antifade Mountant with DAPI. Cells were imaged using an inverted Zeiss AiryScan microscope.

Manual RNAscope assay was performed using RNAscope Multiplex Fluorescent V2 Assay according to the manufacturer’s protocol. The RNAscope assay consists of target probes and a signal amplification system composed of a preamplifier, amplifier, and label probe. A schematic RNAscope assay procedure is shown in Figure 5—figure supplement 1. The probes against the mRNAs of interest and tested in this work were designed by Advanced Cell Diagnostics. Briefly, cells were fixed with 4% paraformaldehyde for 30 min, washed, dehydrated, and then rehydrated with ethanol, and permeabilized with 0.1% Tween-20 in PBS. Next, cells were quenched with H₂O₂ and treated with Protease III. Probes were hybridized for 2 hr at 40°C followed by RNAscope amplification and then fluorescence detection. Coverslips were mounted using ProLong Gold Antifade Mountant with DAPI. We used the following RNAscope probes: RNAscope 3-plex Positive Control Probes, RNAscope 3-plex negative control probes, RNAscope Probe-Rn-Ryr, RNAscope Probe-Rn-Scn9a, RNAscope Probe-Rn-Kcnma1-C3, RNAscope Probe-Rn-Cacna1d-C2, and RNAscope Probe-Rn-Gapdh. Cells were imaged on the inverted AiryScan microscope. For PLA and RNAscope experiments, we used custom-made macros written in ImageJ. Processing of PLA data included background subtraction. To assess colocalization, fluorescent signals were converted into binary images, and channels were multiplied to identify spatial overlap. Specificity of RNAscope probes was tested in untransfected tsA-201 cells (Figure 5—figure supplement 2). For RNAscope combined with immunostaining, RNAscope was followed by blocking in PBS supplemented with 0.01% Tween-20 and 3% BSA for 1 hr at 21°C. Samples were then probed for BK protein using primary antibody overnight at 4°C followed by secondary antibody incubation with Alexa Fluor 488 at 2 μg/ml for 1 hr at 21°C. Coverslips were mounted using ProLong Gold Antifade Mountant. Cells were imaged using an inverted Zeiss AiryScan microscope.

Cells were imaged using an inverted AiryScan microscope (Zeiss LSM 880) run by ZEN black v2.3 software and equipped with a plan apochromat 63× oil immersion objective with 1.4 NA. Fluorescent dyes were excited with a 405 nm diode, 458–514 nm argon, 561 nm, or 633 nm laser. Emission light was detected using an Airyscan 32 GaAsP detector and appropriate emission filter sets. The point spread functions were calculated using ZEN black software and 0.1 μm fluorescent microspheres. The temperature inside the microscope housing was 22°C. Images were analyzed using ImageJ (NIH).

Direct stochastic optical reconstruction microscopy (dSTORM) images of BK and Ca_V1.3 overexpressed in tsA-201 cells were acquired using an ONI Nanoimager microscope equipped with a 100× oil immersion objective (1.4 NA), an XYZ closed-loop piezo 736 stage, and triple emission channels split at 488, 555, and 640 nm. Samples were imaged at 35°C. For single-molecule localization microscopy, fixed and stained cells were imaged in GLOX imaging buffer containing 10 mM β-mercaptoethylamine, 0.56 mg/ml glucose oxidase, 34 μg/ml catalase, and 10% wt/vol glucose in Tris-HCl buffer. Single-molecule localizations were filtered using NImOS software (v.1.18.3, ONI). Localization maps were exported as TIFF images with a pixel size of 5 nm. Maps were further processed in ImageJ (NIH) by thresholding and binarization to isolate labeled structures. To assess colocalization between the signal from two proteins, binary images were multiplied. Particles smaller than 400 nm² were excluded from the analysis to reflect the spatial resolution limit of STORM imaging (20 nm) and the average size of BK channels. To examine spatial localization preference, binary images of BK were progressively dilated to 20 nm, 40 nm, 60 nm, 80 nm, 100 nm, and 200 nm to expand their spatial representation. These modified images were then multiplied with the Ca_V1.3 channel to quantify colocalization and determine BK occupancy at increasing distances from Ca_V1.3. To ensure consistent comparisons across distance thresholds, data were normalized using the 200 nm measurement as the highest reference value, set to 1.

Images were binarized as TIFF images, and their respective cell perimeter coordinates were exported as CSV files by ImageJ. Processed binary images were then analyzed by our SpotScrambler (https://github.com/jehuang2/SpotScrambler, copy archived at Huang, 2025) Python program. SpotScrambler first extracts the areas of fluorescent particles in the binary image. SpotScrambler then redraws the fluorescent particles as circles at randomized coordinates within cell perimeter boundaries. SpotScrambler accurately preserves particle number and particle sizes, averaging less than 1% difference in total area of fluorescent particles between pre-SpotScrambler and post-SpotScrambler images. To ensure reliable randomization for each experiment, results were averaged between three trials of SpotScrambler.

Excel (Microsoft) and Prism (GraphPad) were used to analyze data. ImageJ was used to process images. One-way ANOVA and non-parametric statistical test (Mann-Whitney-Wilcoxon) were used to test for statistical significance. p-Values<0.05 were deemed statistically significant. The number of cells used for each experiment is detailed in each figure legend.

All newly created materials used in this study are available for public access. Plasmid constructs have been deposited in Addgene (repository links and RRIDs are provided in the Materials and methods section). RNA probes utilized for in situ hybridization are proprietary to ACD Biotechnology and are not accessible for redistribution. Complete details regarding materials, including catalog numbers and RRIDs, are provided in the Materials and methods section and in the Supporting Data Excel sheet.

All datasets supporting the findings of this study have been deposited in Dryad and are publicly available (https://doi.org/10.5061/dryad.63xsj3vfq).

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

We thank Gail Robertson for her immense support and influence in designing and conducting this project. We thank Alexey Merz for his support and feedback through this project. We thank Bertil Hille for his contribution to editing the writing of this project. We thank Martina Hunt, Maria Elena Danoviz, Paula Martinez-Feduchi, Wendy Piñon-Teal, and Raul Riquelme for reading and providing feedback on the manuscript. We thank William Catterall and Ruth E Westenbroek for providing the antibody against Ca_V1.3. This study was supported by the National Institutes of Health MIRA R35 GM142690 to OV CM was supported by HL162609 and the Freeman Hrabowski HHMI Scholars program.

1. Sent for peer review: April 8, 2025
2. Preprint posted: April 10, 2025
3. Reviewed Preprint version 1: June 26, 2025
4. Reviewed Preprint version 2: October 31, 2025
5. Reviewed Preprint version 3: December 15, 2025
6. Version of Record published: January 15, 2026

You can cite all versions using the DOI https://doi.org/10.7554/eLife.106791. This DOI represents all versions, and will always resolve to the latest one.

© 2025, Pournejati et al.

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