Periodic Reporting for period 4 - MechAGE (In Vivo Single-Cell Mechanomics of Bone Adaptation and Regeneration in the Aging Mouse)
Periodo di rendicontazione: 2022-04-01 al 2023-03-31
Osteoporosis is one of the most prevalent degenerative diseases globally. It is characterized by a reduction in bone mass and increased fracture risk and has been partly attributed to the decrease in mechanical usage of the skeleton. Bone structure is adapted and maintained through the bone remodeling process, where multiple cell types interact adding and removing bone according to mechanical and chemical cues present in their local environment. However, the underlying mechanisms of how bone cells respond to mechanical signals on the molecular level are still unclear. By combining single-cell “omics” technologies with well-established tissue-scale models of bone mechanobiology, MechAGE develops technology for spatially resolved in vivo single-cell mechanomics of bone adaptation and regeneration. CRISPR/Cas technology has been used to generate fluorescent reporter mice in which different cell types have different fluorescent labels. By combining RNA-sequencing of single cells with micro-finite element (micro-FE) analysis and time-lapsed in vivo micro-CT, MechAGE will link the transcriptome of hundreds of single cells to their local mechanical in vivo environment (LivE). This allowed investigation of molecular responses of the cells to LivE changes with aging in established mouse models of bone adaptation and regeneration. MechAGE also developed in silico mechanobiology models to improve understanding of diseases of aging in mice and to maximize the use of the high quality in vivo mechanomic data. These novel models are incorporating cells as individual entities with their own mechanomic profiles, allowing them to react to the chemical and mechanical environment accordingly. Such computational models improve knowledge about bone metabolism enabling clinicians to better predict a person’s risk of an osteoporotic fracture. This greater knowledge may also permit the identification of potential targets for pharmacological treatments of osteoporosis and its associated fractures, where efficacy of existing and new treatments could be assessed in silico.
In work package 1, CRISPR/Cas-mediated genome editing was used to generate fluorescent reporter mice for osteoblasts and osteoclasts. Specifically, osteoblast (Ibsp) and osteoclast-specific targets (Acp-5, Calcr) were labeled with fluorescent proteins (eGFP, mCherry). The phenotyping of the dual-fluorescent reporter mice for bone cells and the prematurely aged PolgA mice was finalized with preparation and submission of manuscripts (Yilmaz et al. submitted to Cell Reports; Singh et al., to be submitted). In order to allow single cell transcriptomics of bone cells considering their local 3D mechanical micro-environment (LivE), both isolation of single cells via laser-capture-microdissection (LCM) and Visium spatial transcriptomics have been used. To enable the integration of organ- and tissue-level data from micro-computed tomography with sub-cellular information from histological sections, a novel correlative multimodal imaging (CMI) pipeline has been developed also integrating Visium spatial transcriptomics data. To study the effect of aging on bone adaptation, we applied cyclic mechanical loading to vertebrae of premature aging PolgA(D257A/D257A) mice, showing prematurely aged PolgA mice to be not mechano-responsive, whereas younger PolgA mice showed similar anabolic bone adaptation compared to wildtype animals. To study trabecular bone regeneration, we established a femur defect loading model and assessed the regeneration potential of biomaterials in this model showing again that aging negatively affected fracture healing in prematurely aged PolgA mice.
In work package 2, computational tools which interface with experimental studies and data were developed. In the mechanically loaded femoral defect studies, it was critical that the healed bone could always support the applied load, and the tissue scale mechanical loading was consistent across the groups. To achieve this, a novel method termed “real-time Finite Element (rtFE)” was developed to determine suitable loading parameters in vivo. In order to accurately understand the local mechanical in vivo environment (LivE), an instrumented external fixator crossbar was developed. Combined with a multiscale FE model it was possible to determine the load transfer through the femoral defect and the external fixator during mouse locomotion, which improved the estimations for LivE mechanics and provided an important input parameter for the in silico models, where a novel hybrid model was developed combining micro-multi-physics with agent based modelling to model the cells. The reactions cause them to modify their environment by releasing chemical signals, or altering the local bone matrix. The mechanical signal sensed by cells is calculated by micro-FE while the chemical signaling is a reaction-diffusion of molecules and binding sites. The novel 3D micro-MPA models for bone adaptation and regeneration were characterized by high fidelity and flexibility for simulating biological processes on the cellular and organ scale. The micro-MPA models for bone adaptation and regeneration have been applied to study the effect of ageing by adapting the behavior and their mechanosensitivity using the in vivo data obtained for the prematurely aging PolgA mice.
In work package 2, computational tools which interface with experimental studies and data were developed. In the mechanically loaded femoral defect studies, it was critical that the healed bone could always support the applied load, and the tissue scale mechanical loading was consistent across the groups. To achieve this, a novel method termed “real-time Finite Element (rtFE)” was developed to determine suitable loading parameters in vivo. In order to accurately understand the local mechanical in vivo environment (LivE), an instrumented external fixator crossbar was developed. Combined with a multiscale FE model it was possible to determine the load transfer through the femoral defect and the external fixator during mouse locomotion, which improved the estimations for LivE mechanics and provided an important input parameter for the in silico models, where a novel hybrid model was developed combining micro-multi-physics with agent based modelling to model the cells. The reactions cause them to modify their environment by releasing chemical signals, or altering the local bone matrix. The mechanical signal sensed by cells is calculated by micro-FE while the chemical signaling is a reaction-diffusion of molecules and binding sites. The novel 3D micro-MPA models for bone adaptation and regeneration were characterized by high fidelity and flexibility for simulating biological processes on the cellular and organ scale. The micro-MPA models for bone adaptation and regeneration have been applied to study the effect of ageing by adapting the behavior and their mechanosensitivity using the in vivo data obtained for the prematurely aging PolgA mice.
In work package 1, we generated dual-fluorescent reporter mice for osteoblasts and osteoclasts using CRISPR/Cas genome editing. This approach allows capturing endogenous protein levels of the targets, unlike reporter mouse models with protein overexpression. We crossed the reporter mice with a mouse line of premature aging, PolgA(D257A/D257A), to expedite the assessment of aging effects on bone adaptation and regeneration. This is achieved in 40 weeks, compared to 100 weeks in naturally aged wildtype animals. To enhance our approach, we incorporated the Visium spatial transcriptomics system, which enables measurement of gene activity in a tissue sample while retaining spatial information. We established a tissue preparation protocol for using the Visium system on calcified tissue, allowing mild decalcification while preserving high-quality RNA on bone cryosections.
In work package 2, we developed two experimental tools for studying bone mechanobiology. Firstly, we created an instrumented fixator cross bar to measure the physiological loading of the mouse hind limb during healing. This was the first time such measurements were performed on a mouse model. Secondly, we developed rtFE to reduce fracture risk and homogenize LiVE mechanics in mice subjected to extra physiological loading. rtFE is a subject-specific loading method that reduces variance within groups and fracture risk. We also developed a micro-scale multi-physics framework coupled with an agent-based model to simulate bone healing and remodeling at the cell scale. These models consist of millions of individual agents representing cells, reacting to their local chemical and mechanical environment. The in silico models allow simulation of entire mouse vertebrae (~4mm) at a cell scale (10.5 µm), offering unprecedented scale and physiological detail. We plan to incorporate the physiological loading measurements to create personalized simulations of healing and bone remodeling.
In work package 2, we developed two experimental tools for studying bone mechanobiology. Firstly, we created an instrumented fixator cross bar to measure the physiological loading of the mouse hind limb during healing. This was the first time such measurements were performed on a mouse model. Secondly, we developed rtFE to reduce fracture risk and homogenize LiVE mechanics in mice subjected to extra physiological loading. rtFE is a subject-specific loading method that reduces variance within groups and fracture risk. We also developed a micro-scale multi-physics framework coupled with an agent-based model to simulate bone healing and remodeling at the cell scale. These models consist of millions of individual agents representing cells, reacting to their local chemical and mechanical environment. The in silico models allow simulation of entire mouse vertebrae (~4mm) at a cell scale (10.5 µm), offering unprecedented scale and physiological detail. We plan to incorporate the physiological loading measurements to create personalized simulations of healing and bone remodeling.