Here, we describe a correlative workflow for the excision, pressurization, fixation, and imaging of the murine pulmonary valve to determine the gross conformation and local extracellular matrix structures.
The underlying causes of heart valve related-disease (HVD) are elusive. Murine animal models provide an excellent tool for studying HVD, however, the surgical and instrumental expertise required to accurately quantify the structure and organization across multiple length scales have stunted its advancement. This work provides a detailed description of the murine dissection, en bloc staining, sample processing, and correlative imaging procedures for depicting the heart valve at different length scales. Hydrostatic transvalvular pressure was used to control the temporal heterogeneity by chemically fixing the heart valve conformation. Micro-computed tomography (µCT) was used to confirm the geometry of the heart valve and provide a reference for the downstream sample processing needed for the serial block face scanning electron microscopy (SBF-SEM). High-resolution serial SEM images of the extracellular matrix (ECM) were taken and reconstructed to provide a local 3D representation of its organization. µCT and SBF-SEM imaging methods were then correlated to overcome the spatial variation across the pulmonary valve. Though the work presented is exclusively on the pulmonary valve, this methodology could be adopted for describing the hierarchical organization in biological systems and is pivotal for the structural characterization across multiple length scales.
The pulmonary valve (PV) serves to ensure unidirectional blood flow between the right ventricle and the pulmonary artery. Pulmonary valve malformations are associated with several forms of congenital heart disease. The current treatment for congenital heart valve disease (HVD) is valvular repair or valve replacement, which can necessitate multiple invasive surgeries throughout a patient's lifetime1. It has been widely accepted that the function of the heart valve is derived from its structure, often referred to as the structure-function correlate. More specifically, the geometric and biomechanical properties of the heart dictate its function. The mechanical properties, in turn, are determined by the composition and organization of the ECM. By developing a method for determining the biomechanical properties of murine heart valves, transgenic animal models can be used to interrogate the role of the ECM on heart valve function and dysfunction2,3,4,5.
The murine animal model has long been regarded as the standard for molecular studies because transgenic models are more readily available in mice compared to other species. Murine transgenic models provide a versatile platform for researching heart valve-related diseases6. However, the surgical expertise and instrumentation requirements to characterize both the geometry and ECM organization have been a major hurdle in progressing HVD research. Hstological data in literature provides a picture into murine heart valve extracellular matrix content, but only in the form of 2D images, and are unable to describe its 3D architecture7,8. Additionally, the heart valve is both spatially and temporally heterogeneous, making it difficult to draw conclusions across experiments regarding ECM organization if the sampling and conformation are not fixed. Conventional 3D characterization methods, such as MRI or 3D echocardiography, do not provide the resolution necessary to resolve ECM components9,10.
This work details a fully correlative workflow where the temporal heterogeneity due to the cardiac cycle was addressed by fixing the conformation of the murine PV with hydrostatic transvalvular pressure. The spatial heterogeneity was controlled precisely by sampling regions of interest and registering data sets from different imaging modalities, specifically µCT and serial block face scanning electron microscopy, across different length scales. This method of scouting with µCT for guiding downstream sampling has been proposed previously, but because the pulmonary valve exhibits temporal variation, an additional level of control was needed on the surgical level11.
In vivo studies describing murine heart valve biomechanics are sparse and, instead, rely on computational models when describing the deformation behavior. It is of critical importance that local extracellular data on the nanometer length scale be related to the geometry and location of the heart valve. This, in turn, provides quantifiable, spatially mapped distributions of mechanically contributing ECM proteins, which can be used to reinforce existing biomechanical heart valve models12,13,14.
The use of animals in this study was in accordance with Nationwide Children's Hospital institutional animal care and use committee under protocol AR13-00030.
1. Pulmonary valve excision
2. Pressure fixation of pulmonary valve
3. En bloc sample staining and embedment15,16
CAUTION: The staining reagents used in this section (potassium ferrocyanide, osmium tetroxide, thiocarbohydrazide, lead aspartate, and uranyl acetate) are highly toxic and should be handled with extreme care. Use of a fume hood and proper PPE is advised.
4. Micro-computed tomography imaging
5. Sample processing and image correlation
6. Serial block face scanning electron microscopy18
Anastomosis of the pulmonary artery to the pressurization tubing is shown in Figure 1A. Following the application of hydrostatic pressure, the pulmonary trunk distends radially (Figure 1B) indicating that the pulmonary valve leaflets are in a closed configuration. Pulmonary valve conformation was confirmed by µCT. In this case, the leaflets were coapt (closed) and the annulus was circular (Figure 2A). Figure 2B,C shows varying degrees of inadequate pulmonary valve pressurization by either fixation (Figure 2B) or arterial collapse (Figure 2C).
Sample block trimming was guided by the µCT volume rendering. In this case, the plane parallel to the sino-tubular junction was chosen as the slicing direction. Using anatomical landmarks, the µCT volume rendering virtual cross sections was correlated with optical images (Figure 3) to confirm the slicing direction and location.
Once the specimen block was at the desired location and orientation, high-resolution SBF-SEM images were taken at a local region within a leaflet. Image correlation was done between the µCT volume rendering virtual slice (Figure 4A), low-resolution SBF-SEM images (Figure 4B), and high-resolution SBF-SEM images (Figure 4C). Because of the manual sample mounting, requisite slices of the specimen block were needed to create a flat surface before acquiring images in the SBF-SEM; hence, the different locations between Figure 3 and Figure 4.
A full image correlation between µCT and SBF-SEM data sets can be seen in Video 1. The pulmonary valve specimen in the µCT volume rendering can be easily discerned from the surrounding embedding resin because of the staining of heavy metal atoms. Lengths and angles are measured in the image to guide the slicing. In this example, the plane parallel to the sino-tubular junction was used. A virtual slice through emulates the removal of the material until the depth of interest is reached. High-resolution images taken by SBF-SEM were taken at this cross section and registered to the µCT data set.
Once acquired, high-resolution images taken by SBF-SEM can be imported into an image processor and compiled into a 3D representation (Figure 5) where extracellular components can be identified.
Figure 1: Representative images of anastomosed pulmonary trunk. The excised pulmonary trunk (A) before and (B) after hydrostatic pressurization. The dotted line indicates the ventriculo-arterial junction where the annulus of the pulmonary trunk resides. Note the pulmonary trunk distention upon pressurization. Please click here to view a larger version of this figure.
Figure 2: Representative µCT volume rendering pulmonary valve. (A) The pulmonary valve is in a closed position with the leaflets adequately stretched and coapt (circle). (B,C) Inadequate pressurization of the pulmonary valve. Note that the leaflets are not properly coapt (B) and that the annulus is not circular (C). Please click here to view a larger version of this figure.
Figure 3: Image correlation of pulmonary valve specimen block. (A) µCT volume rendering virtual slice and (B) physical specimen block after trimming taken by optical microscopy. Sections of pulmonary valve leaflets are circled in red and were used as landmarks to correlate the two different imaging methods. Scale bar corresponds to 500 µm. Please click here to view a larger version of this figure.
Figure 4: Image correlation of imaged pulmonary valve cross section. (A) Virtual cross section generated by µCT volume rendering. Red box indicates the region that was imaged using SBF-SEM in (B). (B) Low-resolution overview images to correlate with µCT cross section. Blue box represents the location of (C) high-resolution SBF-SEM imaging. Scale bars correspond to (B) 100 µm and (C) 10 µm. Please click here to view a larger version of this figure.
Figure 5: Segmented region of the pulmonary valve taken by SBF-SEM. Cross-sectional images were stacked and compiled to form a 3D representation of a local pulmonary valve region. Labels were assigned to endothelial cells (green), valvular interstitial cells (blue), and extracellular fibers (yellow). The approximate dimensions of the imaged region are 30 µm x 20 µm x 100 µm. Please click here to view a larger version of this figure.
Tube potential | 70 kV |
Tube current | 75 μA |
Focus mode | M |
Trajectory | Circular |
Projections/Revolution | 2880 |
Mode | 3040 x 3040 px |
Averaging | 1 |
Exposure time | 1.0 s |
Sample-to-gun distance | 15 mm |
Detector-to-gun distance | 725 mm |
Voxel size | 2.9 μm |
Field of view | 8.4 x 8.4 x 6.3 mm |
Table S1: Imaging parameters for µCT.
Landing energy | 2 – 2.5 kV |
Beam current | 100 – 400 pA |
Working distance | 6.5 – 7 mm |
Detector | VS-DBS |
Dwell time | 1 – 2 μs |
Table S2: Imaging parameters for SBF-SEM.
Video 1: Image correction of µCT and SBF-SEM data sets. Please click here to download this Video.
Removal of the ventricles serves two purposes. First, exposing the ventricle side to the atmospheric pressure, thereby only needing to apply a transvalvular pressure from the arterial side of the pulmonary valve to close, and second, providing a stable base to prevent twisting of the pulmonary trunk. During pressurization, the pulmonary trunk distends radially and inferiorly, making it prone to twisting, causing the collapse of the pulmonary trunk. Preloading the pulmonary valve with a saline solution offers an additional quality check to ensure that the pressurization is adequate and if there are any leaks in the system. The action of the primary fixative is quick, in the order of a few seconds, and without hydrostatic preloading with the saline solution, the pulmonary valve is fixed in a random conformation. Without preloading, the success rate for a closed pulmonary valve was around 10%-20%. With the preloading step, the success rate was above 90%.
The µCT and SBF-SEM imaging conditions were tuned for this application. The pulmonary valve, when fully stretched, can be less than 10 µm thick. As a rule of thumb, a threshold of 3 voxels is required for being able to resolve a feature; so the µCT volume renderings were scanned with a voxel size of 2.9 µm with a field of view of 8.4 x 8.4 x 6.3 mm. Smaller voxel sizes can be achieved in µCT but this requires either sample trimming and/or longer scan times. A smaller sample would allow higher resolution by placing it closer to the x-ray source. Smaller voxels can also be achieved by placing the x-ray detector further back from the sample; however, this will decrease the total flux on the detector and compromise the signal-to-noise ratio. As a reference, our µCT scans were approximately 5-6 h in duration. Specific imaging conditions used in this study are in Supplementary Table S1 and Supplementary Table S2).
There are limitations to this method. The surgical portion of this procedure requires expertise in animal handling to not compromise the pulmonary valve structure while handling. Additionally, the imaging is time-intensive and requires multiple imaging instruments. As a reference, the high-resolution SBF-SEM imaging was approximately 1 week of continuous imaging for a depth of around 100 µm. This is a demanding task for the instrument to remain stable and consistent for long imaging sessions. A more practical approach would be to devise a sampling strategy to precisely portray the heterogeneity of the pulmonary valve without the time investment. This is yet to be determined. To date, the entire correlative workflow has been done on one mouse but has shown the feasibility and potential of the correlative workflow in investigating the pulmonary valve across length scales.
Future iterations of this correlative approach may involve in situ µCT experiments, such that the same sample can be exposed to different transvalvular pressure to remove sample-to-sample variation. This is currently limited by sample and instrument stability for extended scan times, a pressurization apparatus integrated into imaging systems, and contrast due to similar attenuation coefficients of water and tissue. Additionally, though the transvalvular pressures were reflective of physiological conditions, it is not representative of the pulsatile flow that is characteristic of cardiac contraction. However, it has been shown that strain rate has little effect on the conformation of the leaflet. In future iterations, it might prove more relevant to engineer a device capable of administering pulsatile flow9. Additionally, much of the work requires manual interrogation of the sample, as currently there is no automated workflow. Locating the pulmonary valve, sample processing toward the region of interest, image correlation, and registration were done manually, but would prove useful in the future to streamline processing and mitigate subjectivity.
The work presented is a correlative workflow for fixing the conformation of the pulmonary valve and registering imaging in µCT and SBF-SEM. The information obtained using this method will ultimately be utilized to determine the underlying biomechanics of the pulmonary valve in murine animal models, which have yet to be elucidated. Valvular biomechanics can be completely described by its geometry and extracellular matrix, but these are on two different length scales. To do this, precise control of the heterogeneity of the valve and accurate mapping of high-resolution images of the extracellular matrix with respect to its location within the pulmonary valve is needed. This correlative workflow is already being implemented into other experiments to draw comparisons between wild-type and transgenic osteogenesis imperfecta mice to compare fibrillar extracellular matrix differences and can readily be extrapolated to other congenital defects such as bicuspid valve formation19,20. This information coupled with possible proteomics will provide a complete picture of how the biomechanics will differ between the two murine animal models.
Despite this work only portraying the pulmonary valve, this workflow is readily amendable to other heterogeneous, hierarchical biological systems. We utilized 3D imaging techniques to capture the architectural organization of the ECM, but higher resolution techniques, such as transmission electron microscopy or scanning transmission electron microscopy, can be appended depending on the information desired.
The authors have nothing to disclose.
This work is supported, in part, by R01HL139796 and R01HL128847 grants to CKB and RO1DE028297 and CBET1608058 for DWM.
25% glutaraldehyde (aq) | EMS | 16210 | Primary fixative component |
0.9% sodium chloride injection | Hospira Inc. | NDC 0409-4888-10 | |
1 mL syringe | BD | 309659 | |
10 mL syringe | BD | 309604 | |
200 proof ethanol | EMS | 15055 | |
22G needle | BD | 305156 | |
3 mL syringe | BD | 309657 | |
3-way stopcock | Smiths Medical ASD, Inc. | MX5311L | |
4% osmium tetroxide | EMS | 19150 | Staining component |
4% paraformaldehyde (aq) | EMS | 157-4-100 | Primary fixative component |
Absorbable hemostat | Ethicon | 1961 | |
Acetone | EMS | 10012 | |
Black polyamide monofilament suture, 10-0 | AROSurgical instruments Corporation | TI38402 | |
Black polyamide monofilament suture, 6-0 | AROSurgical instruments Corporation | SN-1956 | |
C57BL/6 mice | Jackson Laboratories | 664 | Approximately 1 yo |
Calcium chloride | Sigma-Aldrich | 10043-52-4 | |
Clamp applying forcep | FST | 00072-14 | |
Cotton tip applicators | Fisher Scientific | 23-400-118 | |
DPBS | Gibco | 14190-144 | |
Dumont #5 forcep | FST | 11251-20 | |
Dumont #5/45 forceps | FST | 11251-35 | |
Dumont #7 fine forcep | FST | 11274-20 | |
Durcupan ACM resin | EMS | 14040 | For embedding |
Fine scissor | FST | 14028-10 | |
Heliscan microCT | Thermo Fisher Scientific | Micro-CT | |
Ketamine hydrochloride injection | Hospira Inc. | NDC 0409-2053 | |
L-aspartic acid | Sigma-Aldrich | 56-84-8 | Staining component |
Lead nitrate | EMS | 17900 | Staining component |
low-vacuum backscatter detector | Thermo Fisher Scientific | VSDBS | SEM backscatter detector |
Micro-adson forcep | FST | 11018-12 | |
Millex-GP filter, 0.22 um, PES 33mm, non-sterile | EMD Millipore | SLGP033NS | |
Non-woven songes | McKesson Corp. | 94442000 | |
Potassium hexacyanoferrate(II) trihydrate | Sigma-Aldrich | 14459-95-1 | Staining component |
Potassium hydroxide | Sigma-Aldrich | 1310-58-3 | |
Pressure monitor line | Smiths Medical ASD, Inc. | MX562 | |
Saline solution (sterile 0.9% sodium chloride) | Hospira Inc. | NDC 0409-0138-22 | |
Size 3 BEEM capsule | EMS | 69910-01 | Embedding container |
Sodium cacodylate trihydrate | Sigma-Aldrich | 6131-99-3 | Buffer |
Solibri retractors | FST | 17000-04 | |
Sputter, carbon and e-beam coater | Leica | EM ACE600 | Gold coater |
Surgical microscope | Leica | M80 | |
Thiocarbohydrazide (TCH) | EMS | 21900 | Staining component |
Tish needle holder/forcep | Micrins | MI1540 | |
Trimmer | Wahl | 9854-500 | |
Uranyl acetate | EMS | 22400 | Staining component |
Volumescope scanning electron microscope | Thermo Fisher Scientific | VOLUMESCOPESEM | Serial Block Face Scanning Electron Microscope |
Xylazine sterile solution | Akorn Inc. | NADA# 139-236 |