Osteocytes and Primary Cilia

Estrogen and estrogen receptors mediate the mechanobiology of bone disease and repair

It is well understood that the balance of bone formation and resorption is dependent on both mechanical and biochemical factors. In addition to cell-secreted cytokines and growth factors, sex hormones like estrogen are critical to maintaining bone health. Although the direct osteoprotective function of estrogen and estrogen receptors (ERs) has been reported extensively, evidence that estrogen signaling also has a role in mediating the effects of mechanical loading on maintenance of bone mass and healing of bone injuries has more recently emerged. Recent studies have underscored the role of estrogen and ERs in many pathways of bone mechanosensation and mechanotransduction. Estrogen and ERs have been shown to augment integrin-based mechanotransduction as well as canonical Wnt/b-catenin, RhoA/ROCK, and YAP/TAZ pathways. Estrogen and ERs also influence the mechanosensitivity of not only osteocytes but also osteoblasts, osteoclasts, and marrow stromal cells. The current review will highlight these roles of estrogen and ERs in cellular mechanisms underlying bone mechanobiology and discuss their implications for management of osteoporosis and bone fractures. A greater understanding of the mechanisms behind interactions between estrogen and mechanical loading may be crucial to addressing the shortcomings of current hormonal and pharmaceutical therapies. A combined therapy approach including high-impact exercise therapy may mitigate adverse side effects and allow an effective long-term solution for the prevention, treatment, and management of bone fragility in at-risk populations. Furthermore, future implications to novel local delivery mechanisms of hormonal therapy for osteoporosis treatment, as well as the effects on bone health of applications of sex hormone therapy outside of bone disease, will be discussed.

Distraction force promotes the osteogenic differentiation of Gli1+ cells in facial sutures via primary cilia-mediated Hedgehog signaling pathway

BACKGROUND

Trans-sutural distraction osteogenesis (TSDO) involves the application of distraction force to facial sutures to stimulate osteogenesis. Gli1+ cells in the cranial sutures play an important role in bone growth. However, whether Gli1+ cells in facial sutures differentiate into bone under distraction force is unknown.

METHODS

4-week-old Gli1ER/Td and C57BL/6 mice were used to establish a TSDO model to explore osteogenesis of zygomaticomaxillary sutures. A Gli1+ cell lineage tracing model was used to observe the distribution of Gli1+ cells and explore the role of Gli1+ cells in facial bone remodeling.

RESULTS

Distraction force promoted bone remodeling during TSDO. Fluorescence and two-photon scanning images revealed the distribution of Gli1+ cells. Under distraction force, Gli1-lineage cells proliferated significantly and co-localized with Runx2+ cells. Hedgehog signaling was upregulated in Gli1+ cells. Inhibition of Hedgehog signaling suppresses the proliferation and osteogenesis of Gli1+ cells induced by distraction force. Subsequently, the stem cell characteristics of Gli1+ cells were identified. Cell-stretching experiments verified that mechanical force promoted the osteogenic differentiation of Gli1+ cells through Hh signaling. Furthermore, immunofluorescence staining and RT-qPCR experiments demonstrated that the primary cilia in Gli1+ cells exhibit Hedgehog-independent mechanosensitivity, which was required for the osteogenic differentiation induced by mechanical force.

CONCLUSIONS

Our study indicates that the primary cilia of Gli1+ cells sense mechanical stimuli, mediate Hedgehog signaling activation, and promote the osteogenic differentiation of Gli1+ cells in zygomaticomaxillary sutures.

β-glycerophosphate, not low magnitude fluid shear stress, increases osteocytogenesis in the osteoblast-to-osteocyte cell line IDG-SW3

AIM

As osteoblasts deposit a mineralized collagen network, a subpopulation of these cells differentiates into osteocytes. Biochemical and mechanical stimuli, particularly fluid shear stress (FSS), are thought to regulate this, but their relative influence remains unclear. Here, we assess both biochemical and mechanical stimuli on long-term bone formation and osteocytogenesis using the osteoblast-osteocyte cell line IDG-SW3.

METHODS

Due to the relative novelty and uncommon culture conditions of IDG-SW3 versus other osteoblast-lineage cell lines, effects of temperature and media formulation on matrix deposition and osteocytogenesis were initially characterized. Subsequently, the relative influence of biochemical (β-glycerophosphate (βGP) and ascorbic acid 2-phosphate (AA2P)) and mechanical stimulation on osteocytogenesis was compared, with intermittent application of low magnitude FSS generated by see-saw rocker.

RESULTS

βGP and AA2P supplementation were required for mineralization and osteocytogenesis, with 33°C cultures retaining a more osteoblastic phenotype and 37°C cultures undergoing significantly higher osteocytogenesis. βGP concentration positively correlated with calcium deposition, whilst AA2P stimulated alkaline phosphatase (ALP) activity and collagen deposition. We demonstrate that increasing βGP concentration also significantly enhances osteocytogenesis as quantified by the expression of green fluorescent protein linked to Dmp1. Intermittent FSS (~0.06 Pa) rocker had no effect on osteocytogenesis and matrix deposition.

CONCLUSIONS

This work demonstrates the suitability and ease with which IDG-SW3 can be utilized in osteocytogenesis studies. IDG-SW3 mineralization was only mediated through biochemical stimuli with no detectable effect of low magnitude FSS. Osteocytogenesis of IDG-SW3 primarily occurred in mineralized areas, further demonstrating the role mineralization of the bone extracellular matrix has in osteocyte differentiation.

A Novel Primary Cilium-Mediated Mechanism Through which Osteocytes Regulate Metastatic Behavior of Both Breast and Prostate Cancer Cells

Bone metastases are a common cause of suffering in breast and prostate cancer patients, however, the interaction between bone cells and cancer cells is poorly understood. Using a series of co-culture, conditioned media, human cancer spheroid, and organ-on-a-chip experiments, this study reveals that osteocytes suppress cancer cell proliferation and increase migration via tumor necrosis factor alpha (TNF-α) secretion. This action is regulated by osteocyte primary cilia and associated intraflagellar transport protein 88 (IFT88). Furthermore, it shows that cancer cells block this mechanism by secreting transforming growth factor beta (TGF-β), which disrupts osteocyte cilia and IFT88 gene expression. This bi-directional crosstalk signaling between osteocytes and cancer cells is common to both breast and prostate cancer. This study also proposes that osteocyte inhibition of cancer cell proliferation decreases as cancer cells increase, producing more TGF-β. Hence, a positive feedback loop develops accelerating metastatic tumor growth. These findings demonstrate the importance of cancer cell-osteocyte signaling in regulating breast and prostate bone metastases and support the development of therapies targeting this pathway.

Deep learning models to map osteocyte networks can successfully distinguish between young and aged bone

Osteocytes, the most abundant and mechanosensitive cells in bone tissue, play a pivotal role in bone homeostasis and mechano-responsiveness, orchestrating the intricate balance between bone formation and resorption under daily activity. Studying osteocyte connectivity and understanding their intricate arrangement within the lacunar canalicular network (LCN) is essential for unraveling bone physiology. This is particularly true as our bones age, which is associated with decreased integrity of the osteocyte network, disrupted mass transport, and lower sensitivity to the mechanical stimuli that allow the skeleton to adapt to changing demands. Much work has been carried out to investigate this relationship, often involving high resolution microscopy of discrete fragments of this network, alongside advanced computational modelling of individual cells. However, traditional methods of segmenting and measuring osteocyte connectomics are time-consuming and labour-intensive, often hindered by human subjectivity and limited throughput. In this study, we explore the application of deep learning and computer vision techniques to automate the segmentation and measurement of osteocyte connectomics, enabling more efficient and accurate analysis. We compare several state-of-the-art computer vision models (U-Nets and Vision Transformers) to successfully segment the LCN, finding that an Attention U-Net model can accurately segment and measure 81.8% of osteocytes and 42.1% of dendritic processes, when compared to manual labelling. While further development is required, we demonstrate that this degree of accuracy is already sufficient to distinguish between bones of young (2 month old) and aged (36 month old) mice, as well as capturing the degeneration induced by genetic modification of osteocytes. By harnessing the power of these advanced technologies, further developments can unravel the complexities of osteocyte networks in unprecedented detail, revolutionising our understanding of bone health and disease.