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In Vivo Single-Cell Mechanomics of Bone Adaptation and Regeneration in the Aging Mouse

Periodic Reporting for period 2 - MechAGE (In Vivo Single-Cell Mechanomics of Bone Adaptation and Regeneration in the Aging Mouse)

Reporting period: 2019-04-01 to 2020-09-30

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 will allow investigation of molecular responses of the cells to LivE changes with aging in established mouse models of bone adaptation and regeneration. MechAGE is also developing 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. To achieve this, the 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 will 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). For all targets, complete reporter integration at the intended locus was achieved and confirmed by sequencing. 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 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 tail defect loading model and assessed the regeneration potential of biomaterials.

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 determin suitable loading parameters in vivo. In order to accurately understand the local mechanical in vivo environment (LivE) of the unloaded femoral defects, 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 in individual mice, 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 microscale multi-physics with agent based modelling. In the model, cells are represented using an agent based paradigm. 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. Currently, the model has demonstrated efficacy in the modelling of bone healing and that similar rules can be applied to the remodeling of bone.
In work package 1, we generated dual-fluorescent reporter mice for osteoblasts and osteoclasts using CRISPR/Cas genome editing. We integrated the reporters before the stop codon of the respective targets allowing capturing of endogenous protein levels of the targets, which is an advantage compared to reporter mouse models with protein overexpression. Based on successful genotypic confirmation of the reporter mice, we are now crossing the mouse line with an established mouse line of premature aging, PolgA(D257A/D257A). This will allow faster assessment of aging associated effects on bone adaptation and regeneration (40 weeks) compared to naturally aged wildtype animals (100 weeks). Based on the availability of novel technologies, we decided to incorporate the Visium spatial transcriptomics system into our approach for developing a novel mechanomics framework. In the Visium system, intact tissue cryosections are placed on the capture areas and eluded mRNA is reverse transcribed into cDNA. Thus, the Visium technique permits measurement of all gene activity in a tissue sample and retains spatial information on the sites at which the activity is occurring. In order to use the Visium system on calcified tissue, we have now established a tissue preparation protocol enabling mild sample decalcification while allowing maintenance of high quality RNA on bone cryosections.

In work package 2, we developed two novel experimental tools for the mechanobiological study of bone. Firstly, in order to determine the physiological loading of the mouse hind limb over the course of healing, an instrumented fixator cross bar was developed. This allowed in vivo measurements of loading during locomotion of the mouse. To our knowledge this is the first time such measurements have been performed on a mouse model. Secondly, for mice which received extra physiological loading, rtFE was developed to reduce fracture risk and homogenize LiVE mechanics. This is a novel method allowing subject specific loading, reducing variance within groups and reducing the risk of fracture. We developed a micro-scale multi-physics framework linked with an agent based model, capable of simulating bone healing and remodeling at the cell scale. These models consist of millions of individual agents representing cells, reacting to their chemical and mechanical local environment, represented by hundreds of millions of degrees of freedom solved using a bespoke multi-physics solver. The in silico models allows entire mouse vertebrae (~4mm) to be simulated at cell scale (10.5 µm), creating models unprecedented in terms of scale and physiological detail. We plan to incorporate the physiological loading measurements to create individualized simulations of healing and bone remodeling.