Figures and data in Ryanodine receptor dispersion disrupts Ca2+ release in failing cardiac myocytes

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7 figures, 1 table and 3 additional files

Figures

Figure 1

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dSTORM imaging enables quantification of RyR localization within Ca²⁺ release units (CRUs).

RyR imaging was performed with antibody labelling of isolated and fixed rat ventricular cardiomyocytes. (A). Imaging of RyRs with confocal microscopy (left panel) or Structured Illumination Microscopy (SIM, centre panel) revealed a predominantly striated pattern of RyR localization across cells, but individual CRUs could not be discerned (magnified regions in lower panels). dSTORM imaging provided markedly improved spatial resolution enabling identification of RyR clusters (scale bars = 5 µm). (B). Quantification of RyR localization was performed by fitting raw images to a 30 × 30 nm grid (Baddeley et al., 2009), and performing thresholding to create binary images; an RyR was counted as present if > half the area of a 30 nm square was suprathreshold. CRUs were defined as collections of RyR clusters with an edge-to-edge distance < 150 nm (Macquaide et al., 2015) (red boundaries) or < 100 nm (Baddeley et al., 2009; Hou et al., 2015). (Scale bar = 2 µm).

https://doi.org/10.7554/eLife.39427.003

Figure 2 with 1 supplement

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RyRs are dispersed in failing cardiomyocytes.

Alterations in nanoscale RyR organization were examined in cardiomyocytes from rats with post-infarction heart failure (HF). Representative images show that macroscale organization of RyRs was similar in HF and Sham-operated controls (A), upper panels). However, nanoscale examination revealed that RyR clusters were broken apart in HF. For the magnified regions in (A), conversion from raw dSTORM to binary images is shown in the middle and lower panels (saturation levels indicated by high-low look-up table). Mean measurements showed fewer RyRs per cluster in failing cells, with an increased fraction of small clusters (B). Dispersion of RyR clusters into smaller fragments resulted in an increased overall number of clusters (D), reduced inter-cluster distances (E) and inclusion of more clusters in each CRU (F). Overall CRU composition became less solid in failing cells ((G), assessed by convex-hull analysis), as the average CRU contained fewer RyRs (C). See Figure 2—source data 1 for analysis of 100 nm vs 150 nm CRU inclusion criterion (n_cells = 46, 50 in Sham, HF; *=P < 0.05 vs Sham).

https://doi.org/10.7554/eLife.39427.004

Figure 2—source data 1 Quantification of RyR organization using 150 vs 100 nm CRU inclusion criteria. RyR cluster and CRU data were compared in Sham and HF myocytes, with data cumulated across cells or animals. Two CRU definitions were also compared, with maximum edge-to-edge distances of 150 nm or 100 nm. Significant differences within data cumulated across cells were determined by t-test, while data cumulated across animals were tested with linear mixed effects models (Lindstrom and Bates, 1988).: https://doi.org/10.7554/eLife.39427.006
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Figure 2—figure supplement 1

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HF in post-infarction rats is not associated with altered expression of RyR, BIN1, or Junctophilin-2.

Western blotting was performed on homogenates of left ventricles from post-MI HF rats and Sham-operated controls. Representative immunoblots are shown at left, with mean values at right, normalized to Sham. (JPH2 = junctophilin 2; n_hearts = 5, five5 in Sham, HF; P = NS).

https://doi.org/10.7554/eLife.39427.005

Figure 3

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Failing cardiomyocytes exhibit increased ‘silent’ RyR leak.

Total RyR-mediated Ca²⁺ leak was assessed in SR microsomes using fura-2 fluorescence (A). Vesicular Ca²⁺ uptake was initiated by addition of ATP, and halted by addition of thapsigargin. SR Ca²⁺ leak was estimated as the thapsigargin-induced rate of rise of [Ca²⁺], normalized to releasable SR content (rise in [Ca²⁺] induced by the RyR opener 4-chloro-m-cresol, CMC). While the rate of SR Ca²⁺ uptake was reduced in HF relative to Sham (B), total RyR leak was increased (C) even with a slight reduction in the releasable Ca²⁺ store (D). (n = 8 from 3 Sham hearts, 7 from 3 HF hearts; *=P < 0.05 vs Sham). To assess whether elevated SR leak in failing cells could be attributed to Ca²⁺ sparks, line-scan confocal imaging of resting cardiomyocytes was employed (E). Ca²⁺ spark mass was increased in HF relative to Sham (F), due to augmented spark geometry (Figure 5B). However, since spark frequency tended to be reduced (G), overall Ca²⁺ spark-mediated leak was similar in Sham and HF (H). These results are consistent with increased ‘silent’ non-spark-mediated SR leak in HF cardiomyocytes. (FWHM = full width at half maximum, FDHM = full duration at half maximum; n_cells = 43 in Sham, 50 in HF; *=P < 0.05 vs Sham).

https://doi.org/10.7554/eLife.39427.007

Figure 4 with 1 supplement

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CRU dispersion provides the structural basis for silent RyR leak in HF.

A mathematical model of the dyad was employed to examine the effects of CRU dispersion on Ca²⁺ sparks and non-spark mediated RyR leak. (A). As dSTORM imaging indicated an increased fraction of small CRUs in HF (Figure 2C), small idealized CRUs were initially modelled with as few as 4 RyRs. Simulated Ca²⁺ sparks (300 consecutive simulations) were never detected for the smallest CRUs, based on an experimentally determined spark detection threshold of ΔF/F₀ = 0.4. Higher probability of visible spark generation (fidelity) was observed for larger CRUs. (B). Real CRU geometries obtained by dSTORM imaging were employed to simulate sparks from larger dyads. Four configurations were modelled with varying numbers of constituent RyR clusters, but similar total RyR number (≈55). While the single-cluster CRU exhibited high Ca²⁺ spark fidelity, lower probability of spark generation was observed in dispersed, multi-cluster CRUs (fidelity indicated by colour scale). These data support that CRU rearrangement during HF promotes silent RyR leak, due to an increased fraction of both small CRUs as well as larger CRUs with dispersed, irregular configurations.

https://doi.org/10.7554/eLife.39427.008

Figure 4—source data 1 Morphological characteristics for the 4 dSTORM-generated geometries.: https://doi.org/10.7554/eLife.39427.010
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Figure 4—figure supplement 1

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Development and characterization of the mathematical dyadic model.

(A) Graphical representation of the computational domain of the model. The junctional SR (jSR) was shaped to encompass idealized RyR geometries or dSTORM-based CRU contours. (B) To understand the role of the jSR geometry in determining the maximum inter-cluster distance permissive of functional coupling, and thus CRU definition, we spread two square 16-RyR clusters at variable distances up to 144 nm edge-to-edge (i.e. 4 RyR lengths). Coupling could occur at distances up to ~ 150 nm but only when the jSR was contiguous between clusters. (C) Similar effects could be observed in the realistic 7-cluster geometry, where a fully contiguous jSR was sufficient to functionally couple clusters at distances between 100 and 150 nm.

https://doi.org/10.7554/eLife.39427.009

Figure 5

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Ca²⁺ spark kinetics are slowed in HF.

(A) Representative line-scan images of Ca²⁺ sparks in Sham and HF, selected from the cell-wide scans presented in Figure 3E. Temporal profiles (right panels) show that spark kinetics were generally tightly constrained in Sham, with low values for both time to peak (TTP) and duration (full duration at half maximum, FDHM). Although many sparks were also brief in HF cells, a subset of sparks exhibited slowed kinetics. (B) Distributions of measurements for TTP and FDHM were right-shifted in HF, and mean values were significantly increased. Spark magnitudes tended to be larger in HF than Sham. (n_sparks = 130, 100 from 75, 72 cells in Sham, HF; *=P < 0.05 vs Sham).

https://doi.org/10.7554/eLife.39427.011

Figure 6 with 1 supplement

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RyR dispersion during HF results in slowing of Ca²⁺ sparks.

To examine whether altered CRU morphology could slow Ca²⁺ spark kinetics in HF, spark profiles were simulated for a variety of dSTORM-derived RyR configurations. (A) Sparks were triggered by opening a single RyR (circled) which was randomly placed in consecutive simulations (example RyR opening trajectories are shown in the upper panels, with a family of spark time-courses illustrated below). Time to opening was registered for each RyR in the CRU, and the resultant time course of the Ca²⁺ spark was plotted until the final RyR closure, at which point the simulation was stopped for computational efficiency. Opening times were similar for individual RyRs within a solid, single cluster CRU, and the overall temporal profile of elicited sparks showed rapid kinetics which were rather consistent between consecutive simulations. By contrast, delayed and variable opening times were observed for individual RyRs in multi-cluster CRUs. This resulted in variable and slowed Ca²⁺ spark kinetics with these CRU configurations, as indicated by temporal spark profiles (A), a right-shifted distribution of time-to-peak measurements (B) and mean data (C). (*=P < 0.05 vs single-cluster CRU).

https://doi.org/10.7554/eLife.39427.012

Figure 6—source data 1 CRU size has little effect on Ca²⁺spark characteristics in the reported range. Clusters smaller than 15 – 20 RyR exhibit early spark termination due to stochastic attrition, whereas larger clusters are more capable of supporting regenerative release, for which spark termination becomes relatively consistent in time and dependent on depletion of the releasable Ca²⁺ store. The simulations were started with all RyRs in the open state and allowed to proceed stochastically. For each RyR number, 50 simulations were performed. The plot shows the mean time from the start of the simulation until all RyRs close. Error bars are standard deviations.: https://doi.org/10.7554/eLife.39427.014
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Figure 6—figure supplement 1

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Effect of focal plane on Ca²⁺ spark detection and kinetics.

To examine whether out-of-focus Ca²⁺ release events could artefactually alter assessment of Ca²⁺ spark parameters, simulated Ca²⁺ release profiles were compared in ‘linescans’ collected at various depths of the 2 × 2 µm computational domain (54 RyR single cluster model). Vertical, stepwise displacement from the central plane resulted in a rapid decrease in measured spark amplitude (A). Indeed, events > 0.5 µm displaced from the focal plan were undetectable. While displacement of the focal plane also slowed apparent Ca²⁺ spark kinetics, such effects were negligible within the range where sparks were detectable (B).

https://doi.org/10.7554/eLife.39427.013

Figure 7 with 1 supplement

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Slow Ca²⁺ sparks promote slow, desynchronized Ca²⁺ transients in HF.

(A) Representative confocal linescan images of Ca²⁺ transients in field-stimulated cells (stimulus illustrated as a horizontal line). The overall Ca²⁺ transient was slowed in HF compared to Sham, as indicated by plots of spatially-averaged Ca²⁺ transients (A), right panel), and measurements of half rise time (TTF₅₀, (B)) and time to peak (C). Slowed Ca²⁺ transient kinetics included de-synchronization of Ca²⁺ release across HF cells, as indicated by profiles of local TTF₅₀ (lower panels in A). The standard deviation of these values, defined as the *dyssynchrony index,* (Louch et al., 2006) showed a right-shifted distribution in HF compared to Sham (D). To examine the relationship between slowed Ca²⁺ spark kinetics and de-synchronized Ca²⁺ transients in HF, local Ca²⁺ transients were examined within 2 µm regions of the linescan centered at the location of recorded sparks. Paired representative recordings of sparks and local Ca²⁺ transients are shown in (E and F), respectively, corresponding to indicated positions in A) (vertical arrows). Local Ca²⁺ release at ‘slow’ spark locations (rise time > 13 ms) was protracted during the action potential, in comparison with local transients with ‘fast’ sparks in both HF and Sham (F). This association is demonstrated by clustering of locations with slow Ca²⁺ spark and local transient kinetics in ‘heat maps’ (G), and links slowing of Ca²⁺ release kinetics at the level of the single CRU and whole cell. (Ca²⁺ transients: n_cells = 43 in Sham, 57 in HF; n_{fast sparks}= 18 in Sham, 19 in HF; n_{slow sparks}= 18 in HF; *=P < 0.05 vs Sham).

https://doi.org/10.7554/eLife.39427.015

Figure 7—figure supplement 1

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T-tubule structure is disrupted during HF.

Isolated cardiomyocytes were stained with di-8-ANEPPS and examined by confocal microscopy (A) zoomed regions enlarged in (B). In agreement with previous work employing the same post-infarction rat model (Frisk et al., 2016), we observed marked remodeling of t-tubular structure in HF. Skeletonized images (**C, D**) indicate that this reorganization included a loss of transverse t-tubule elements (colored white) and the appearance of additional longitudinal tubules running in the axial, perpendicular orientation (colored red). Scale bar = 5 µm.

https://doi.org/10.7554/eLife.39427.016

Tables

Key resources table

Reagent type (species) or resource	Designation	Source or reference	Identifiers	Additional information
Strain, strain background (Rattus norvegicus, M)	Male Wistar- Hannover rats	Janvier-labs	RjHan: WI; RGD: 13792727
Antibody	Mouse-anti-RyR2 primary antibody	ThermoFischer Scientific	Cat# MA3-916; RRID:AB_2183054	IHC, 1:100; WB, 1:1000
Antibody	Alexa Fluo 647 conjugated goat-anti-mouse secondary Ab	Molecular Probes/Invitrogen	Cat# A-21237; RRID:AB_2535806	IHC, 1:200
Antibody	Anti-goat IgG-HRP linked whole antibody	R and D Systems	Cat# HAF109; RRID:AB_357236	WB, 1:3000
Antibody	Mouse IgG HRP linked Whole Ab	GE Healthcare	Cat# NA931V; RRID:AB_772210	WB, 1:3000
Antibody	Rabbit IgG HRP linked Whole Ab	GE Healthcare	Cat# NA934V; RRID: AB_772206	WB, 1:3000
aAntibody	Goat Anti-GAPDH Polyclonal antibody	Santa Cruz Biotechnology	Cat# sc-20357; RRID:AB_641107	WB, 1:500
Antibody	Goat Anti- Junctophilin-2 Polyclonal Antibody	Santa Cruz Biotechnology	Cat# sc-51313; RRID:AB_2296391	WB, 1:1000
Antibody	BIN1 (Amphiphysin II (2F11) Antibody)	Santa Cruz Biotechnology	Cat# sc-23918; RRID:AB_667901	WB, 1:500
Software, algorithm	Dense Stochastic Sampling Imaging (DSSI) algorithm	SoftWoRx, GE Healthcare
Software, algorithm	dSTORM image post-processing algorithm	PMID: 26490742		Described in the Github repository (Kolstad, 2018; copy archived at https://github.com/elifesciences-publications/Ryanodine_Receptor_Dispersion_during_Heart_Failure)
Software, algorithm	Mathematical Model	PMID: 22495592; PMID: 23708355; this paper		Described in the Github repository (Kolstad, 2018; copy archived at https://github.com/elifesciences-publications/Ryanodine_Receptor_Dispersion_during_Heart_Failure)
Software, algorithm	SigmaPlot	SigmaPlot	RRID:SCR_003210