The protocol utilizes advanced light-sheet microscopy along with adapted tissue clearing methods to investigate intricate cardiac structures in rodent hearts, holding great potential for the understanding of cardiac morphogenesis and remodeling.
Light-sheet microscopy (LSM) plays a pivotal role in comprehending the intricate three-dimensional (3D) structure of the heart, providing crucial insights into fundamental cardiac physiology and pathologic responses. We hereby delve into the development and implementation of the LSM technique to elucidate the micro-architecture of the heart in mouse models. The methodology integrates a customized LSM system with tissue clearing techniques, mitigating light scattering within cardiac tissues for volumetric imaging. The combination of conventional LSM with image stitching and multiview deconvolution approaches allows for the capture of the entire heart. To address the inherent trade-off between axial resolution and field of view (FOV), we further introduce an axially swept light-sheet microscopy (ASLM) method to minimize out-of-focus light and uniformly illuminate the heart across the propagation direction. In the meanwhile, tissue clearing methods such as iDISCO enhance light penetration, facilitating the visualization of deep structures and ensuring a comprehensive examination of the myocardium throughout the entire heart. The combination of the proposed LSM and tissue clearing methods presents a promising platform for researchers in resolving cardiac structures in rodent hearts, holding great potential for the understanding of cardiac morphogenesis and remodeling.
Heart failure remains the leading cause of mortality worldwide, primarily due to the lack of regenerative capacity of mature cardiomyocytes1. The intricate architecture of the heart plays a crucial role in its function and provides insights into developmental processes. A profound understanding of cardiac structure is essential for elucidating the fundamental processes of cardiac morphogenesis and remodeling in response to myocardial infarction. Recent progress has demonstrated that neonatal mice can restore cardiac function following injury, while adult mice lack such regenerative capacity2. This establishes a foundation for investigating cues associated with structural and functional abnormalities in mouse models. Traditional imaging methods, such as confocal microscopy, have technical limitations, including restricted penetration depth, slow point-scanning scheme, and photo damage from prolonged exposure to laser light. These hinder comprehensive three-dimensional (3D) imaging of the intact heart. In this context, light-sheet microscopy (LSM) emerges as a powerful solution, offering the advantages of high-speed imaging, reduced photo damage, and exceptional optical sectioning capabilities3,4,5. The unique features of LSM position it as a promising method to overcome the limitations of conventional techniques, providing unprecedented insights into cardiac development and remodeling processes6,7,8.
In this protocol, we introduce an imaging strategy that combines advanced LSM with adapted tissue clearing approaches9, allowing for the imaging of entire mouse hearts without the need for specific labeling and mechanical sectioning. We further propose that conventional LSM imaging can be enhanced through multiview deconvolution10 or axially swept light-sheet microscopy (ASLM) techniques11,12,13,14,15 to improve axial resolution. Additionally, the integration of image stitching with either of these methods can effectively overcome the trade-off between spatial resolution and field of view (FOV), thereby advancing the imaging of adult mouse hearts. The incorporation of numerous tissue clearing approaches, including hydrophobic, hydrophilic, and hydrogel-based methods, enables deeper light penetration for capturing the morphology of the entire heart16,17,18,19.
While multiple clearing methods are compatible with current LSM systems, the goal is to minimize photon scattering and enhance light penetration in tissues, like the heart, by replacing lipids with a medium that closely matches its refractive index. iDISCO was chosen as the representative20,21 and adapted for autofluorescence imaging in this protocol due to its rapid processing and high transparency (Figure 1A). Collectively, the integration of the advanced LSM approach with tissue clearing techniques offers a promising framework to unravel intricate cardiac anatomy in rodent hearts, holding significant potential for advancing our understanding of cardiac morphogenesis and pathogenesis.
Animal protocols and experiments have been approved and conducted under the oversight of the University of Texas at Dallas Institutional Animal Care and Use Committee (IACUC #21-03). C57BL6 mice, including neonates at postnatal day 1 (P1) and 8-week-old adults, were used in this study. No difference was observed between males and females. All data acquisition and image post-processing were carried out using open-source software or platforms with research or educational licenses. The resources are available from the authors upon reasonable request.
1. Sample preparation and tissue clearing (6 – 10 days)
2. Sample mounting (1 day)
NOTE: In case a commercial LSM system is used, follow its specific protocol provided by the company to fix the heart and skip steps 2.1 – 2.9.
3. Image stitching (4-8 h)
4. Multiview deconvolution (5 days)
5. Axially swept light-sheet system hardware (1 day)
6. Axially swept light-sheet system synchronization (7 days)
LSM has been demonstrated to foster cardiac studies31,32,33,34,35,36,37 due to the minimal risk of photo damage, high spatial resolution, and optical sectioning as opposed to other optical imaging methods such as brightfield and point-scanning techniques6,8,38,39,40. Thus, to better understand the 3D myocardial architecture, we have established the protocol based on primary approaches including adapted iDISCO clearing, image stitching, multiview deconvolution, and ASLM. While we presented results using mouse models, it is important to note that rats and other rodent models are also suitable for the proposed methods. The adapted tissue clearing protocol enables the rendering of the P1 mouse heart transparent within 4 days and the 8-week-old mouse heart transparent within 7 days (Figure 1B). This step serves as a starting point for minimizing photon absorption and scattering in the intact heart. Multiview deconvolution enables the improvement of axial resolution by fusing images from multiple perspectives into a single model. After sequentially recording images from 6 views of the same heart, the multiview deconvolution method achieves near-isotropic resolution with a lateral of 4.68 µm and axial of 5.06 µm, following 15 h of computation (Figure 8A). To obviate the computational complexity, we further customized an ETL-based ASLM to image from neonatal to adult mouse hearts. This method allows us to scan the myocardium with a tightly focused laser beam, minimizing the out-of-focus background and enhancing the image contrast in comparison to the conventional LSM methods (Figure 8B). With the current ASLM design, the averaged lateral and axial resolutions of the system achieve 2.18 µm and 2.88 µm, respectively, enabling in-depth exploration of myocardial trabeculation in ventricles. In addition, image stitching can be utilized independently, or in combination with multiview deconvolution or ASLM to expand the FOV for larger sample sizes. Integrating stitching with ASLM allows us to cover the entire 8-week-old mouse heart with uniform resolution (Figure 8C), providing an effective solution to investigate the cross-section of the entire heart.
Figure 1: Tissue clearing process. (A) The hydrophobic method involves tissue dehydration, lipid extraction, and refractive index matching using dibenzyl ether (DBE) as the organic solvent. (B) Submerge the heart in a mixture of 4% formaldehyde (PFA) solution and dehydrate it with a gradient of methanol and deionized (DI) water mixtures. Bleach the heart using 5% H2O2 in methanol at 4 °C. Delipidate the heart with dichloromethane (DCM) and methanol solution until the sample sinks to the bottom of the tube. Lastly, incubate the heart in DBE in order to obtain the desired refractive index. Grid lines 5 mm. Please click here to view a larger version of this figure.
Figure 2: Schematic of axially swept light-sheet microscopy. (A) Customized 3D printed chamber, (B) chamber magnet, (C) clamp holder, and (D) ASLM system. Abbreviations: CL: cylindrical lens; ETL: electronic tunable lens; IL: illumination lens; DL: detection lens; FW: filter wheel; TL: tube lens. This figure has been modified from Ref16. Please click here to view a larger version of this figure.
Figure 3: Image stitching and multiview deconvolution. (A-B) Image stitching is used to cover the entire mouse hearts, with each tile having a 10% FOV overlap with its adjacent tiles. (C) Movement pattern of the mouse heart for image stitching. (D) Fluorescent beads are affixed to the end of the glass tube to facilitate image registration, while the heart is positioned inside the glass tube containing DBE, enabling concurrent imaging of both the mouse heart and fluorescent beads. (E) Multiview deconvolution involves the acquisition of images from six distinct perspectives, each gathering images from unique directions. (F) Raw data of P1 mouse heart and beads at different angles of 0°, 60°, 120°, 180°, 240°, and 300°. Scale bars: 500 µm. This figure has been modified from16. Please click here to view a larger version of this figure.
Figure 4: Block diagram of ASLM system. Utilizing DAQ card for synchronizing ETL and sCMOS camera. The housing of the ETL driver has been opened for soldering of signal and ground wires to the PCB. Please click here to view a larger version of this figure.
Figure 5: LabView control panel. LabVIEW control panel for generating triggers to synchronize ETL and activated pixels of sCMOS camera. Please click here to view a larger version of this figure.
Figure 6: Synchronizing the focus of light-sheet with activated pixels. (A) The identification of the starting and ending points of the light-sheet scanning range is achieved by configuring the appropriate voltage for the ETL trigger. (B) The synchronous result of fluorescent beads is evident along the diagonal of the image. (C-F) The non-uniform spatial resolution across the entire FOV arises from the asynchronous operation of the ETL with the sCMOS camera. The ETL initiates scanning (C) later or (D) earlier than the activated pixel. (E-F) The focal area is not parallel to the diagonal of the image, indicating an incompatibility between scanning and activation speeds. ETL scans (E) faster or (F) slower than the sweeping of active pixels in sCMOS. Scale bar: 200 µm. Please click here to view a larger version of this figure.
Figure 7: Troubleshooting of ASLM. (A) The light-sheet is placed exactly at the focal distance of the detection lens. The ETL scans the focus of the light-sheet along the propagation direction while synchronizing with the activated pixel of the sCMOS sensor. (B) XY view of fluorescent beads when the ETL is correctly aligned and synchronized. (C-D) Results of fluorescent beads on the focal plane and out-of-focus in cross-sectional images, indicating the misalignment between the ETL scanning and laser propagation. Scale bars: 200 µm and 10 µm in the inset. Please click here to view a larger version of this figure.
Figure 8: Light-sheet imaging of mouse hearts. (A) Volume-rendered image of the multiview deconvolution P1 mouse heart highlighting the trabeculation within the ventricular cavity. (B) Cross-sectional images of the 8-week-old mouse heart generated by conventional LSM (left) and ASLM (right). Images are presented as raw data. (C) Combination of Image stitching and ASLM for imaging an 8-week-old mouse heart, comprising 12 tiles arranged in 3 tiles horizontally and 4 tiles vertically. Scale bar: 500 µm. Abbreviations: LV: left ventricle, LA: left atrium, RV: right ventricle, and RA: right atrium. This figure has been modified from Ref16. Please click here to view a larger version of this figure.
Procedure | Time (P1 mouse heart) | Time (8-week-old mouse heart) | Temperature | |||
Fix in 4% PFA | Overnight | Overnight | 4°C | Sample preparation | ||
Wash with 1x PBS | 30 min | 30 min | RT | |||
Wash with 1x PBS | 30 min | 30 min | RT | |||
Wash with 1x PBS | 30 min | 30 min | RT | |||
Embed with agarose gel | 1 h | 2 h | RT | |||
Incubate in 20% methanol/80% DI water | 1 h | 2 h | RT | Dehydration | ||
Incubate in 40% methanol/60% DI water | 1 h | 2 h | RT | |||
Incubate in 60% methanol/40% DI water | 1 h | 2 h | RT | |||
Incubate in 80% methanol/20% DI water | 1 h | 2 h | RT | |||
Incubate in 100% methanol | 1 h | 2 h | RT | |||
Incubate in fresh 100% methanol | 1 h | 2 h | RT | |||
Incubate in fresh 100% methanol | 10 min | 10 min | 4°C | Depigmentation | ||
Bleach with 5% H2O2/methanol | Overnight | Overnight | 4°C | |||
Incubate in 100% methanol | 1 h | 1 h | RT | |||
Delipidate with 66% DCM/33% methanol on the shaker | 3 h | 3 h | RT | Delipidation | ||
Incubate in DBE on the shaker | 2 days | 5 days | RT | RI matching |
Table 1: Customized tissue clearing steps for autofluorescence imaging.
The advancement of imaging, computation, and tissue clearing methods has provided an unparalleled opportunity to extensively investigate cardiac structure and function. This holds great potential for deepening our understanding of cardiac morphogenesis and pathogenesis using an intact rodent heart model. In contrast to in vivo studies of zebrafish heart using a similar approach40,41,42,43, the integration of advanced LSM techniques and tissue clearing methods enables us to overcome challenges between spatial resolution and penetration depth when imaging the rodent model9,44. Tissue clearing techniques render hearts optically transparent by removing lipids and other light-scattering elements, enabling deeper imaging penetration45. When coupled with LSM, we are able to image the myocardium. This combination enhances the imaging depth and allows for the observation of intricate myocardial micro-structure. While numerous clearing methods have been established18, we adapted the iDISCO20 to rapidly render the intact heart transparent in comparison with other tissue clearing methods15, making it readily available for the imaging of autofluorescence from the myocardium. For specific fluorescence labeling, the original iDISCO and Adipo-Clear46 protocols can be combined with immunostaining in this customized imaging system, despite the longer incubation. Meanwhile, methods that preserve endogenous fluorescence and require shorter processing time are preferred for the proposed study. In contrast to other methods, this platform offers the following advantages. Firstly, we utilize an adapted iDISCO protocol for tissue clearing, enabling rapid rendering of the heart transparent in less than 1 week while retaining myocardium autofluorescence. Secondly, we incorporate computational methods such as image stitching and multiview deconvolution into this established light-sheet system for cardiac imaging. Lastly, we design and synchronize the ASLM system to enhance axial resolution across a large FOV, enabling multiscale imaging and analysis of myocardial compaction and trabeculation at a near isotropic resolution.
To capture cardiac images of the rodent model, we have provided four approaches based on LSM: i) the conventional method for screening purposes19, ii) image stitching, iii) multiview deconvolution, and iv) ASLM scanning. Considering the variation in heart size across different models, we sought to address the fundamental trade-off in spatial resolution, acquisition speed, and FOV. While image stitching enables the large FOV with compromised spatial resolution, combining it with multiview deconvolution or ASLM provides near-isotropic resolution across the extended FOV to cover the entire adult mouse heart. Furthermore, the integration of these methods enhances image quality and contrast in the deep tissue, allowing for a comprehensive digital reconstruction of 3D models of micro-structures such as myocardial trabeculation and compaction inside ventricles. However, the deluge of datasets, extensive computational processing cost, the need for precise image registration, and the potential for artifacts in multiview deconvolution and imaging stitching hinder their broad applications. While ASLM is an emerging alternative, the complexity of the system synchronization, laser scanning strategies, and reliance on tissue transparency pose challenges that may affect system robustness and increase the risk of photo damage to the heart.
Collectively, this methodology including LSM imaging and tissue clearing provides a starting point to explore cardiac structure from neonates to adults. It holds the potential to localize the distribution of specialized cardiac lineages and their functions during cardiac development47. With the development of computational analysis tailored for cardiac applications6,48,49,50,51,52,53 , this framework can be extended to investigate cardiac remodeling processes, particularly in response to myocardial infarction. Ultimately, this holistic strategy holds the potential to unravel the underlying mechanism of cardiac morphogenesis and advance the development of therapeutic interventions.
The authors have nothing to disclose.
We express our gratitude to Dr. Eric Olson's group at UT Southwestern Medical Center for generously sharing the animal models. We appreciate all the constructive comments provided by D-incubator members at UT Dallas. This work was supported by NIH R00HL148493 (Y.D.), R01HL162635 (Y.D.), and UT Dallas STARS program (Y.D.).
1% Agarose | |||
Low melting point agarose | Thermo Fisher | 16520050 | |
Deionized water | – | – | |
Chemicals for tissue clearing | |||
5-Amino-1,3,3-trimethylcyclohexanemethylamine, mixture of cis and trans | Sigma-Aldrich | 118184 | |
D.E.R.™ 332 | Sigma-Aldrich | 31185 | |
D.E.R.™ 736 | Sigma-Aldrich | 31191 | |
Dibenzyl ether (DBE) | Sigma-Aldrich | 33630 | |
Dichloromethane (DCM) | Sigma-Aldrich | 270997 | |
Fluorescent beads | Spherotech | FP-0556-2 | |
Hydrogen peroxide (H2O2) | Sigma-Aldrich | 216736 | |
Methanol | Sigma-Aldrich | 439193 | |
Paraformaldehyde (PFA) | Thermo Fisher | 47392 | |
Phosphate Buffered Saline (PBS) | Sigma-Aldrich | 79383 | |
Potassium Chloride (KCl) | Sigma-Aldrich | P3911 | |
Software and algorithms | |||
Amira | Thermo Fisher Scientific | 2021.2 | |
BigStitcher | Hörl et al.22 | ||
Fiji-ImageJ | Schindelin et al.20 | 1.54f | |
HCImage Live | Hamamatsu Photonics | 4.6.1.2 | |
LabVIEW | National Instruments Corporation | 2017 SP1 | |
Key components of the customized light-sheet system | |||
0.63 – 6.3X Zoom body | Olympus | MVX-ZB10 | |
10X Illumination objective | Nikon | MRH00105 | |
1X detection objective | Olympus | MV PLAPO 1X/0.25 | |
473nm DPSS Laser | Laserglow Technologies | LRS-0473-PFM-00100-05 | |
532nm DPSS laser | Laserglow Technologies | LRS-0532-PFM-00100-05 | |
589 nm DPSS laser | Laserglow Technologies | LRS-0589-GFF-00100-05 | |
BNC connector | National Instrument | BNC-2110 | |
Cylindrical lens | Thorlabs | ACY254-050-A | |
DC-Motor Controller, 4 axes | Physik Instrumente | C-884.4DC | |
ETL | Optotune | EL-16-40-TC-VIS-5D-1-C | |
ETL Cable | Optotune | CAB-6-300 | |
ETL Lens Driver | Optotune | EL-E-4i | |
Filter | Chroma | ET525/30 | |
Filter | Chroma | ET585-40 | |
Filter | Chroma | ET645-75 | |
Filter wheel | Shutter Instrument | LAMBDA 10-B | |
Motorized translation stage | Physik Instrumente | L-406.20DG10 | |
Motorized translation stage | Physik Instrumente | L-406.40DG10 | |
Motorized translation stage | Physik Instrumente | M-403.4PD | |
NI multifunction I/O | National Instrument | PCIe-6363 | |
sCMOS camera | Hamamatsu | C13440-20CU | |
Stepper motor | Pololu | 1474 | |
Tube lens | Olympus | MVX-TLU |