Protocol for the Isolation and Super-resolution dSTORM Imaging of RyR2 in Cardiac Myocytes

[Abstract] Since its inception, super-resolution microscopy has played an increasingly important role in the discovery and characterization of nanoscale biological structure. dSTORM, which is one of the most commonly applied methods, relies on stochastic photoswitching of fluorophores to recreate a super-resolution image. The cardiac field has particularly benefitted from the application of this technique, as it has enabled sub-diffraction-limit visualization of calcium release units (CRUs) and the fundamental structures that trigger contraction. Acquisition of such images requires careful, reproducible sample preparation, and consistent imaging conditions maintained for the duration of the experiment. Here we present standardized methods for the production of dSTORM images of the Ca 2+ release channel Ryanodine Receptor type-2 (RyR2) in cardiac myocytes. The presented protocols specifically focus on steps involved in primary cardiac myocyte isolation, sample preparation, and imaging with details provided for experimental solutions and microscope settings. This discussion is followed by an overview of various analysis techniques to discern RyR2 organization within clusters and CRUs.

. Indeed, the RyR is well-suited to such studies, owing to its large size and its tendency to agglomerate into functionally important 'clusters'. Most of these clusters have sizes that are just below the resolution of conventional microscopes. Because of these desirable features, the RyR can also serve as a useful example protein for introducing methods in sample preparation and imaging in a more general context. Here we present standardized methods to produce high-quality dSTORM images using the Carl Zeiss Elyra P1 dSTORM setup, with the RyR2 as a model target. The outlined protocols include methods for primary cardiac myocyte isolation, sample preparation, and imaging. Further discussion is provided regarding the analysis of RyR2 organization, including techniques for discernment of RyR clusters and, in turn, Ca 2+ Release Units (CRUs) which are functional groupings of RyR clusters thought to underlie Ca 2+ sparks (Inui et al., 1987).

Materials and Reagents
A. Consumables

A. Isolation
Note: All prepared solutions should be kept on ice for the duration of the isolation protocol.

Setup
It is important that all animal usage and experimentation are approved by ethics committees with jurisdiction over the facility in which experiments will be carried out.
a. Prior to cell isolation, the animal should be moved to the experiment room ~12 h in advance for acclimatization. If multiple animals are to be used, they should be kept separate to prevent unnecessary stress of witnessing the protocol for heart excision.
Additionally, equipment should be cleaned in between each protocol. b. Begin by rinsing the Langendorff isolation system twice with EtOH; flushing the system at maximal pump settings.  Figure 1). The size of the required canula is dependent on the animal to be used for isolation. For mice, we recommend using a converted 18 gauge disposable needle. It may be blunted at the tip with a small groove cut at ~1-2 mm above the bottom to enable suture placement ( Figure   2A).   i. Make an initial cut across the abdomen into the cavity.
ii. Then make parallel cuts up the ribcage to the sides, making sure not to accidentally cut the heart.
iii. Remove the ribcage or alternatively lift it out of the way to expose the thoracic cavity.
iv. With a pair of curved forceps, lift the heart and excise behind the forceps making sure a significant portion of the aorta is retained for hanging.
v. Rapidly transfer the heart to the cooled CIV in the weigh boat. e. Rinse the heart quickly in CIV and then cannulate the aorta, making sure not to insert the cannula deeper than the coronary ostia. It is essential that the aorta is correctly identified, Copyright  h. Switch the collection dish so that only perfused collagenase is collected. Start a timer and perfuse for a further 7 min.
i. Following completion of digestion, excise the heart just below the atria to ensure that only ventricular cells are present for subsequent isolation steps. Place the ventricular tissue in the collecting dish together with the collagenase-containing perfusate.
j. Dice the ventricular tissue into smaller chunks of roughly 2 x 2 mm using fine scissors.
Then, with tweezers, gently agitate and pull the tissue apart to loosen cells. This should be done within roughly 2 min of excision from the base ( Figure 1D). k. Using a Pasture pipette with the end cut; transport the tissue chunks into a 10 ml Falcon tube with 8 ml buffer (CIV buffer + 500 μl BSA +120 μg DNase). The BSA will stop the digestion procedure. n. Once the 10 ml tube has been filtered, use a further 10 ml of CIV with BSA to dislodge more cells from the main tissue mass on the filter mesh in order to increase yield. o. After straining, discard the filter mesh and set the tube aside for isolated cells to settle.
Typically a pellet can be seen at the end of the procedure and will grow larger over the next few minutes as more cells sediment.
Note: Important for observation during the perfusion period is the dilation and color change observable in the heart being perfused. Generally, there is a dilation of the overall shape as the passive forces provided by the collagen tissue are removed through its dissolution (see Figures   2B and 2C for comparison). The color of the heart also becomes paler, perfusate drips become elongated due to increase in digested collagen, and overall the tissue is softer when tested with forceps.

B. Fixation and plating
At this stage, it is important that the cells are not dehydrated, so a humidified chamber should be Copyright      c. TIRF uHP, where the intensity is enhanced 8x compared with the standard TIRF setting.
The focusing of TIRF HP and TIRF uHP settings correspondingly reduce the diameter of the overall illumination field, requiring the use of a cropped section of the camera's FOV during imaging.
For a standard imaging run: 1. Sample identification and orientation are achieved with standard trans-illumination using a halogen lamp. A suitable myocyte is one with a rod-like appearance and clear sarcomere striations.
2. Once a cell has been selected, the imaging mode is switched to fluorescence with widefield laser illumination.
3. To obtain an overview and locate the ROI, laser output is reduced to 4% of maximum (as set by ZEN Black software) and the basic TIRF filter is used. The laser angle is maintained at a HiLo level of 55-65 degrees. The camera is set to 50 msec integration time with gain adjustable to produce a clear image without clipping the highlights. 4. With a region selected, the ROI is then constrained to a central 16.5 x 16.5 μm area where even illumination from the TIRF uHP focused laser spot falls. 5. The system is then placed in a dSTORM mode with TIRF uHP filter, 100% laser output, and camera integration of 50 msec. EM gain is set initially at 0 to prevent sensor damage during the bleaching period. The acquisition is set to between 15,000 and 20,000 frames ( Figure 4A). Copyright  8. After the sequence has been acquired, the raw image stack is processed for the identification of individual fluorophores. This can be achieved within the ZEN software by supplying the signal-to-noise threshold for detection, the expected Gaussian spread, and indicating whether the multi-emitter fitting should be applied (default ratio of 6.0). For our images, the default setting is used for the detection thresholds, and the multi-emitter setting is enabled. Standard high-quality images will show > 100 k filtered events although this can depend on the target protein and the size of the area imaged. The values given are typical when staining for RyR2 using the high-quality antibodies specified above. 9. To render the image, the current method is a Gaussian overlay where detection uncertainty of the individual events is turned into a Gaussian intensity distribution, with standard pixel resolution of 10 nm (Complete rendered image seen in Figure 4B and C).

E. Image Segmentation
Segmentation is primarily carried out in ImageJ and when required for additional flexibility and efficient batch processing, by custom python scripts. Here we present the segmentation method used for measurement of cluster sizes in ImageJ.
1. Open ImageJ software and load in the image to be analyzed. 6. Because of potential nonspecific antibody binding, a minimal particle size should be set when examining structures below what is either resolvable or expected to be observed. Depending on the structures to be analyzed, a circularity limitation can also be set, however, in the context for RyR clusters, no such limit is used. 7. Once the measurements are collected, they can then be saved as tab delimited .txt or excel .xls files and further analyzed.

F. Considerations for imaging processing
Possibly the most difficult aspect of the acquisition procedure is deciding the best means to analyze the highly detailed data provided in dSTORM images. Indeed, these images often require additional analysis steps to discern experimentally important observations from acquisition artifacts.
Post-acquisition appraisal of image quality is highly important. Poor quality images with low event counts are often impossible to analyze or require complex processing before robust data can be extracted. Thus, it is highly recommended that poor quality images be filtered and excluded before proceeding with the analysis pipeline. Key parameters to observe are the localization precision of detected events, the event density, and sample movement during the acquisition process (drift).
Each of these variables will directly affect the overall resolution of the final image, as reviewed in Deschout et al. (2014). In this context it is useful to point out that the field of super-resolution www.bio-protocol.org/e2952 DOI:10.21769/BioProtoc.2952 imaging is developing a range of tools with the aim to robustly detect images with poor resolution and artifacts, see Banterle et al. (2013) and Culley et al. (2018).
The analysis pipeline generally begins with the separation of signal from the background by employing thresholding. This can be a contentious topic due to the often subjective nature of selecting the precise threshold point. In our experience, we have found that a modified OTSU method provides a reliable and unbiased approach which produces results in close agreement with what is visually observed. Alternatively, the threshold value can be based on simulations to identify the level necessary to reproduce the dimensions of the underlying object (Hou et al., 2014).
After determining a suitable threshold, another important aspect to consider when proposing analysis methods is the type of structure to be investigated. For cluster-type structures such as the RyRs imaged in our experiments, standard measurements include the size of the clusters, their relative spacing, and density . One employed approach has been to apply a 30 x 30 nm grid to the thresholded image, where a grid pixel corresponds to approximate dimensions of a single RyR. Thus, a grid position can be defined as containing an RyR if it is more than half filled with supra-threshold pixels, and RyR clusters can thereafter be defined by occupied, neighboring

Recipes
Note: Typically reagents are prepared in advance of the date of isolation.

Cell isolation buffer (CIV)
a. CIV is initially made as a 10x stock relative to concentrations listed below: Copyright