The proposed protocol entails a global approach to assess bone formation in the context of bone regeneration using multimodal analyses. It aims to provide qualitative and quantitative information on new bone formation, enhancing the rigor and validity of basic and pre-clinical investigations.
The extensive characterization of tissue mineralization in the context of bone regeneration represents a significant challenge, given the numerous modalities that are currently available for analysis. Here, we propose a workflow for a comprehensive evaluation of new bone formation using a relevant large animal osseous ex vivo explant. A bone defect (diameter = 3.75 mm; depth = 5.0 mm) is created in an explanted sheep femoral head and injected with a macroporous bone substitute loaded with a pro-osteogenic growth factor (bone morphogenetic protein 2 – BMP2). Subsequently, the explant is maintained in culture for a 28-day period, allowing cellular colonization and subsequent bone formation. To evaluate the quality and structure of newly mineralized tissue, the following successive methods are set up: (i) Characterization and high-resolution 3D images of the entire explant using micro-CT, followed by deep learning image analyses to enhance the discrimination of mineralized tissues; (ii) Nano-indentation to determine the mechanical properties of the newly formed tissue; (iii) Histological examinations, such as Hematoxylin/Eosin/Saffron (HES), Goldner’s trichrome, and Movat’s pentachrome to provide a qualitative assessment of mineralized tissue, particularly with regard to the visualization of the osteoid barrier and the presence of bone cells; (iv) Back-scattering scanning electron microscopy (SEM) mapping with internal reference to quantify the degree of mineralization and provide detailed insights into surface morphology, mineral composition, and bone-biomaterial interface; (v) Raman spectroscopy to characterize the molecular composition of the mineralized matrix and to provide insights into the persistence of BMP2 within the cement through the detection of peptide bonds. This multimodal analysis will provide an effective assessment of newly formed bone and comprehensive qualitative and quantitative insights into mineralized tissues. Through the standardization of these protocols, we aim to facilitate interstudy comparisons and improve the validity and reliability of research findings.
Bone defects, whether caused by trauma, tumor resection, congenital anomalies, or infection, represent a major challenge for regenerative medicine. These alterations compromise the structural integrity of the skeletal system, leading to discomfort, functional impairment, and a reduction in patients' quality of life.
To overcome these challenges, innovative bone repair strategies have emerged, with a focus on enhancing osteogenesis and bone tissue regeneration. These approaches include the use of implantable, injectable, or 3D-printable bone substitutes, which can be of natural origin (e.g., bio-sourced macromolecules, animal-derived hydroxyapatite) or synthetic (e.g., bioglasses, calcium phosphates)1. To enhance their low inherent ability to guide and stimulate bone regeneration, bone substitutes can be loaded with osteoinductive factors, such as bone morphogenetic proteins (BMPs), to promote osteogenic differentiation of progenitor cells and enhance bone formation2.
Bone formation is based on the initial formation of a collagen matrix, which is then mineralized by hydroxyapatite crystals, thereby reinforcing the bone structure3. This process confers specific stiffness and strength to the bone. The quality of the mineralized tissue is intricately governed by its microstructural attributes and degree of mineralization4. This quality plays a pivotal role in bone healing and the functionality of the regenerated bone5. However, characterizing bone mineralization remains a challenging task due to the inherent variability across multivariate studies6,7,8.
In addition, initial evaluations of the biocompatibility, cytocompatibility, and differentiation potential of bone graft substitutes are typically conducted in vitro. However, methodological disparities impede the seamless comparison of outcomes. Furthermore, these in vitro studies do not fully capture the multicellular interactions and complex dialogue between cell populations, including bone marrow cells, which are essential for regulating the bone regeneration process9. This lack of accurate representation of the bone microenvironment may compromise the accuracy of subsequent preclinical studies10.
Although in vivo assessments provide a more accurate representation of physiological contexts, they are constrained by ethical, logistical, and financial considerations. Consequently, ex vivo evaluations play a pivotal role as an interface between in vitro and in vivo studies, serving as a necessary intermediate step before moving on to experiments on living subjects11,12,13.
In this context, the implementation of comprehensive characterization methodologies is needed to appraise the quality of regenerated bone tissue and to ensure the relevance of the strategy before moving on to a preclinical model. Consequently, we propose a protocol based on the analysis of an explant model using sheep knee joint tissue. This innovative methodology involves implanting BMP2-loaded cement into the explants and conducting a detailed analysis of tissue mineralization after 28 days of culture.
The technical approaches employed in this study are diverse and complementary, collectively providing a comprehensive approach to evaluating the quality of regenerated bone tissue (Figure 1). High-resolution micro-CT imaging enables detailed 3D visualization of the bone structure, providing valuable insights into the mineral density, morphology, and integrity of the newly formed tissue. This technique is crucial for assessing the efficacy of bone regeneration and monitoring the progression of mineralization over time. Nanoindentation is a precise approach for determining the mechanical properties of the tissue, such as its hardness and strength. By measuring the response of the material to a force applied on a nanometric scale, this method enables the assessment of the robustness and quality of the mineralized tissue. Histological examinations using common staining such as hematoxylin/eosin/saffron (HES), Goldner's trichrome, and Movat's pentachrome provide invaluable insights into tissue structure and composition. These stainings' allow differentiation of the various tissue components, including cells, extracellular matrix, and mineral deposits, thereby enabling a comprehensive qualitative assessment of the bone regeneration process. Backscatter scanning electron microscopy (SEM) mapping offers a high-resolution visualization of the surface of the samples, allowing detailed analysis of the degree of mineralization of the bone matrix, as well as the interfaces between the implanted material and the host tissue. Finally, Raman spectroscopy provides information regarding the molecular composition of the tissue, particularly through the identification of specific components such as proteins, lipids, and minerals. This approach enables the characterization of the mineralized matrix and the detection of growth factors such as BMP2, thereby providing crucial information on the persistence of pro-osteogenic stimuli in the regeneration medium.
Using a multi-disciplinary approach, integrating various analytical techniques, our study aims to provide a thorough and comprehensive assessment of the quality of regenerated bone tissue, thus providing a solid basis for the evaluation of bone graft substitutes and their potential clinical application.
This study has been approved by an ethics and animal welfare committee and by the French National Veterinary and Food Administration under number G44171.
1. Preparation and culture of osteochondral explants
2. Micro-CT analysis
3. Deep-learning image analyzes
4. Embedding
5. Scanning electron microscopy (SEM) – quantitative backscattered electron imaging (qBEI)
6. Histology
7. Raman microspectroscopy
8. Nanoindentation
NOTE: Due to the destructive nature of nanoindentation, it is usually performed at the end of the sample analysis routine. The nanoindentation system that we own is equipped with a pyramidal Berkovitch diamond indenter. However, several indenter shapes exist, and no consensus in the literature has been determined for bone or biomaterial specimens.
A micro-CT image of the explant is shown in Figure 2. Using Manual segmentation cannot optimally separate bone from cement, present in the central canal, using global thresholding. To improve the recognition of trabecular bone and cement, we propose to use deep learning. Deep learning is powerful for recognizing biomaterial characteristics and helps to improve the separation between bone and cement, enabling a better assessment of cement-bone interactions. This is of the utmost importance in order to accurately quantify the amount of bone formed at the interface with cement and not to incorporate false pixels in this calculation.
However, simply quantifying bone at the interface is not enough to characterize newly formed bone. A more in-depth study of bone matrix quality and cellular composition is required to better understand the strength of the new bone and the cellular mechanisms that led to the formation of this new matrix. The bone matrix can be characterized using two complementary approaches: qBEI and Raman microspectroscopy. An example of a qBEI image is presented in Figure 3. With qBEI, each grayscale-encoded pixel is transformed into a calcium concentration. This is a prerequisite for assessing the distribution of calcium content in trabecular bone and for understanding (i) the degree of mineralization of newly-formed bone at the interface with cement and (ii) whether the presence of cement disrupts trabecular bone mineralization. The advantage of qBEI is its ability to acquire a high-resolution image in a very short time, unlike Raman microspectroscopy which requires a longer acquisition time. qBEI parameters such as Camean, Capeak and Cawidth can then be derived from the calcium distribution and used to compare the response between two cements or biomaterials.
On the other hand, qBEI does not provide any information on the quality of the organic phase of the bone matrix at the interface with the biomaterial. Additional information regarding the material properties of the organic phase is derived from Raman microspectroscopy. Raman microspectroscopy is performed on the same specimen as used for qBEI after a quick surface grinding and polishing in order to remove the conductive carbon layer. In Raman microspectroscopy, spectra are acquired at each pixel location. Examples of raw unprocessed and processed Raman spectra are provided in Figure 4. Each spectrum contains information on the composition of the pixel analyzed and includes peaks related to the embedding resin, in this case, pMMA, the mineral phase, peaks v1PO4 and v1CO3, and the organic phase, peaks Pro, Hyp, CML, Amide III, PG, CH2, Pen. and Amide I. In the example in Figure 4, the untreated spectrum shows the contribution of the coating resin at ~812 cm-1 and a non-zero curved baseline due to fluorescence, although a near-infrared red laser is used. Spectrum processing is a prerequisite for ensuring accurate calculation of the various Raman parameters, in particular the elimination of background fluorescence. When acquiring data, the user should ensure both accurate positioning and avoidance of detector saturation to confirm the presence of the v1PO4 peak located ~960 cm-1. Following post-processing, peak intensity ratios are computed according to the location of the characteristic vibrational mode.
However, it is questionable whether changes in material composition led to changes in biomechanical response. To gather information on the biomechanics of newly formed bone, we systematically carry out nanoindentation investigations on the same sample used for Raman microspectroscopy. Tissue mechanical information is obtained from nanoindentation curves represented by load versus depth curves (Figure 5). It is worth noting that the depth does not go back to zero at the end of the test, representing the plastic deformation and the permanent damage created to the material. The indentation creep rate is derived from the depth versus time curve.
Finally, histological staining is used to assess the tissue response to the biomaterial at the cellular level (Figure 6). The histological stains proposed allow us to determine the presence of osteoid tissue, but also the identification of cells (macrophages, multinucleated giant cells, osteoclasts, osteoblasts) and the possible presence of a fibrous capsule at the interface with the biomaterial. This is very important for understanding the biocompatibility of a biomaterial, but also the persistence of new bone when the biomaterial is degraded.
Overall, the multi-method approach enables an in-depth study of bone formation, the quality of newly formed bone, and cellular composition. When carried out in the proposed sequential order, all investigations can be performed on the same sample, reducing cost and processing time.
Figure 1: Graphical abstract. A summary of the protocol steps is provided here. Please click here to view a larger version of this figure.
Figure 2: Micro-CT and deep learning analyses. (A) 3D reconstruction of micro-CT images. (B) Bone and cement segmentation: comparison between manual segmentation and deep learning. Scale bar = 5 cm. Please click here to view a larger version of this figure.
Figure 3: Quantitative backscattered electron imaging for determining calcium content. (A) The backscattered image composed of grey levels obtained in the scanning electron microscopy (SEM) is converted by the image analysis software into (B) a calcium map showing the hot spots of the bone sample. (C) The distribution of the calcium content versus bone area is plotted, and the three major qBEI parameters, Camean, Capeak, and Cawidth, are computed. Please click here to view a larger version of this figure.
Figure 4: Example of Raman spectra. (A) Raw unprocessed Raman spectrum obtained in the spectral range 800 – 1800 cm-1. The fluorescence background is clearly visible as the spectra do not start from 0. The resin contribution (pMMA) is clearly visible at ~812 cm-1. (B) Processed spectrum. The position of the different vibrational modes of interest is indicated on the spectrum. Please click here to view a larger version of this figure.
Figure 5: Investigation of tissue mechanical properties by nanoindentation. (A) The nanoindentation device is composed of an optical part used to define the location of the region of interest at the surface of the specimen block, and then the block is translated under the indentation part. (B) Load versus time and depth versus time are plotted during indentation test and are used to generate the (C) load versus depth curve. In this example the chosen depth was fixed at 400 nm. The maximum load (Lm), the depth at the end of loading (hl), the depth after the pause period (hm), the slope of the unloading segment (S) and the area under the loading-unloading phase of the test (Wplast) are derived from the load versus depth curve and are used to compute the different nanoindentation parameters. Please click here to view a larger version of this figure.
Figure 6: Histological analysis of osteochondral explants treated with cement after 28 days of culture. (A) Movat staining demonstrates the tissue structure, including bone and the cement filling the defect. (B) HES staining illustrates the tissue integration and cellular response around the cement. Scale bar: 2.5 mm. (C) Magnification of the highlighted area in (B), which details the interface between the cement and the surrounding tissue, where cells can be observed invading the cement. Scale bar: 500 µm. Please click here to view a larger version of this figure.
Repair of bone defects is a major challenge in regenerative medicine to restore mobility, reduce pain, and improve the quality of life of affected individuals. The use of explant models offers a number of advantages compared to in vivo studies for the investigation of bone defect repair. In addition to ethical considerations, this model allows for the rigorous control of experimental conditions and the reduction of biological variability, thereby facilitating the generation of more accurate and reproducible results. Furthermore, the mechanical and biological properties of sheep bone are closely aligned with those of human bone in comparison to other animals23,24. This makes the sheep explant model a particularly relevant choice for preclinical studies and a representative model of human clinical conditions.
Along with the development of imaging and material sciences methodology, the explant model described here represents a good model to investigate the effects of regenerative medicine on skeletal tissues in a controlled environment reducing experimental bias. The dimensions and morphology of the explant are optimal for detailed analysis of neo-osteogenesis and material properties, enabling comprehensive assessment and characterization25. These findings emphasize the model’s potential for clinical translation, offering a robust framework for evaluating bone graft substitutes and enhancing the likelihood of successful clinical outcomes in bone regeneration therapies. Furthermore, the model facilitates precise evaluation of osteointegration and biomaterial performance, which are critical factors in developing effective bone repair strategies.
To ensure the success of the study, it is critical to follow the protocol’s key steps meticulously. One of the most important aspects is ensuring the sample is fully dehydrated during the embedding process. Any remaining moisture can hinder proper resin embedding, leading to a blurred and non-transparent resin, which could compromise the clarity and accuracy of the results and could also result in holes during histology sectioning. This careful attention to detail is essential for producing reliable and reproducible findings. In order to ensure accurate conversion of grey levels into a calcium content map, it is essential to employ calibration using a Faraday cup and C, Al, and Si standards for SEM analysis. It is crucial to ensure consistency in the use of the same SEM for all samples, as differences in backscattered electron detectors can lead to variability in the results. In Raman spectroscopy, calibration of the wavenumber and thorough baseline correction are essential to exclude fluorescence background and differentiate between peaks from the embedding resin and the sample. For nanoindentation, achieving a perfectly smooth surface is critical, given the displacement limits of indenters, and calibration with a known standard, such as fused silica, is necessary to ensure reliable measurements.
The modifications and troubleshooting of these techniques frequently address the anisotropic nature of bone material, which has the potential to influence measurement consistency. To illustrate, in Raman spectroscopy, the polarization of the incident laser can have a considerable impact on the recorded intensity. The use of a 20x objective with a low numerical aperture can assist in the mitigation of this issue. It is also of paramount importance to ensure consistent calibration and measurement conditions across all samples in order to maintain data integrity. The inherent anisotropy of bone represents a limitation of these methodologies, as it can affect the uniformity of measurements, particularly in techniques such as Raman spectroscopy. Furthermore, the necessity for precise calibration and environmental control may limit the general applicability if these aspects are not meticulously managed.
The potential applicability of these approaches extends significantly to the evaluation of novel biomaterials and therapeutic strategies for bone repair. The model’s capacity to closely mimic human bone physiology provides a robust platform for preclinical testing, enabling a thorough assessment of the safety and efficacy of new treatments in a controlled setting. This model’s utility is particularly relevant for accelerating the translational pathway from laboratory research to clinical practice, facilitating the early identification of promising candidates for bone regeneration therapies. By providing a reliable and reproducible method for evaluating bone repair materials, this technique supports the advancement of regenerative medicine and the development of clinically viable solutions.
The authors have nothing to disclose.
We want to thank the technical facilities involved in the collection and processing of specimens, including SC3M (SFR Francois Bonamy (UMS 016), University of Nantes), SFR ICAT (University of Angers), BIO3, HiMolA, and SC4BIO. The Inserm UMR_S 1229 RMeS is supported by grants from the French Government through Inserm, Nantes Université, Univ Angers and Oniris VetAgroBio institutions. CL is also grateful to HTL Biotechnology.
0.20 filters | VWR | 28145-501 | |
18 G needle (1,2×40 mm) | Sterican | 4665120 | |
3 mL syringe | HENKE-JECT | 8300005762 | |
37% hydrochloric acid | VWR | 1.00317.1000 | |
Acetic acid (glacial) | Sigma | A6283 | |
Acetone | VWR | 20063-365 | |
Alcian Blue 8GX | VWR | 361186 | |
Ammonium hydroxide | VWR | 318612 | |
Apatitic tricalcium phosphate | Centre for Biomedical and Healthcare Engineering (Mines Saint Etienne, France) | TV26U | |
Azophloxine | Sigma | 210633 | |
Benzoyl peroxide | Sigma | 8.01641.0250 | |
BMP2 | Medtronic | InductOs 1.5 mg/mL | |
Brillant crocein | Aldrich | 2107507 | |
CTVox | Bruker | – | |
DataViewer | Skyscan | – | |
Diamond blade | Struers | MOD13 | |
Diamond saw | Struers | Accutom-50 | |
DiaPro Mol B3 diamond solution | Struers | 40600379 | |
DiaPro Nap B1 diamond solution | Struers | 40600373 | |
Dibasic sodium phosphate (Na2HPO4) | Sigma | 102404598 | |
Dibutyl Phtalate | Chimie-Plus Laboratoires | 28656 | |
DragonFly software | ORS | 2022.1.0.1231. | |
Dulbecco's Modified Eagle Medium (DMEM) high glucose, GlutaMAX(TM), pyruvate | ThermoFisher Scientific | 31966-021 | |
Eosine Y- Surgipath | Sigma | 1002830105 | |
Erythrosin B | Sigma | 102141057 | |
Ethanol absolute | VWR | 20820362 | |
Eukitt | Dutscher | 6.00.01.0003.06.01.01 | |
Falcon 50 mL | Sarstedt | 62.547.254 | |
Ferric chloride hexahydrate (FeCl3, 6H2O) | Merck | 1.03943.0250 | |
Fetal Bovine Serum (FBS) | Eurobio | CVFSVF00 | |
Fuchsine acid | Merck | 1.05231.0025 | |
Hank's Balanced Salt Solution (HBSS) | Biosera | MS01NG100J | |
Hematoxylin | Sigma | 86.118.9 | |
Isostatic press | Nova Suisse | Pmax 1500 bars | |
Laser diffraction granulometry | Malvern | Mastersizer 3000 | |
Light green | Prolabo | 28947135 | |
Lithium carbonate | Sigma | A13149 | |
MD-Mol polishing cloth | Struers | 40500077 | |
Methylcyclohexane | VWR | 8.06147.1000 | |
Methylcyclohexane | VWR | 8.06147.1000 | |
Methylcyclohexane | VWR | 8.06147.1000 | |
Methylmethacrylate | Sigma | 8.00590.2500 | |
Micro-CT, micro-scanner | Bruker | Skyscan 1272 | |
Monobasic sodium phosphate (NAH2PO4) | Sigma | 71496 | |
Mortar | Fritsch | Pulverisette 6 | |
N,N, Dimethylanilin | Sigma | 803060 | |
Nanoindentation station | Anton Paar | NHT2 | |
ND-Nap polishing cloth | Struers | 40500080 | |
OATS Osteochondral Autograft Transfer System Set, 4,75 mm | Arthrex | AR-1981-04S | |
OATS Osteochondral Autograft Transfer System Set, 8 mm | Arthrex | AR-1981-08S | |
Orange G | Ral | M15 | |
Paraformaldehyde (PFA) | Sigma | P6148 | |
Peel-a-way disposable embbedding moulds | Polysciences, Inc | 18646C-1 | |
Penicillin/Streptomycin (P/S) | ThermoFisher Scientific | 15140122 | |
Phosphate Buffered Saline (PBS) | ThermoFisher Scientific | 10010023 | |
Phosphomolybdic acid | Sigma | 221856-100 g | |
Phosphotungstic acid | Aldrich | 12863-5 | |
Polishing machine | Sturers | Dap V | |
Poupinel | MEMMERT | TV26U | |
Raman microspectrometer | Renishaw | InVia Qontor | |
Safran du Gâtinais | Labonord | 11507737 | |
Scanning electron microscope | Carl Zeiss | Evo LS 10 | |
SEM | Zeiss | Carl Zeiss Evo LS10 | |
SiC foils/Grinding papers | Struers | 40400008 (#320), 40400011 (#1000), 40400122 (#2000), 40400182 (#4000) | |
Silver paint | Electron microscopy sciences | 12686-15 | |
Standard stub with Faraday cup, carbon, aluminium and silicon standards | Micro-Analysis Consultants Ltd | 8602 | |
T25 flask | Corning | 430639 | |
Xylene | VWR | 28975.325 | |
Xylidine Ponceau | Aldrich | 19.976-1 |