Mechanosensitive Ca2+ Signaling of Ex Vivo Osteocytes in Aging and Treatment
By: Andrea Elyse Campi
Publisher: [publisher not identified]
Published: 2019
Place of publication: [New York, N.Y.?]
Language: eng
Description: Of the three major cell types in bone, osteocytes are considered the major mechanosensors, capable of detecting whole-bone mechanical forces at a cellular level and coordinating tissue-level bone formation and resorption responses. The pathology of age-induced bone loss, a major factor in the development of osteoporosis, is attributed to impaired osteocyte mechanosensing. However, real-time evidence of immediate osteocyte responses to mechanical load to support the blunted tissue-level responses that have been demonstrated thus far is lacking. A ubiquitous cellular response upstream of many functions in all cell types, intracellular calcium (Ca2+) is an early mechanosensitive signal in osteocytes, wherein the response characteristics studied in systems of multiple scales are related to mechanical stimuli. Thus, this phenomenon can be characterized as a real-time measure of osteocyte mechanosensitivity. The objective of this thesis was to utilize an ex vivo model of osteocyte Ca2+ signaling to investigate potentially altered mechanosensitivity of the osteocyte network in two clinical contexts: aging, and a recently-approved therapy for treatment of osteoporosis.

Additionally, we aimed to enhance this ex vivo model to identify a functional consequence of this robust Ca2+ signaling response to mechanical load in the context of osteocyte mechanotransduction. We first sought to characterize and compare Ca2+ signaling responses to mechanical load in osteocytes from aged and young-adult mice using an ex vivo model to visualize cell networks in viable mouse tibiae. We found that fewer osteocytes responded to whole-bone cyclic mechanical loading in aged mice tibiae compared to those from young-adult mice and did so in a delayed manner, suggesting a diminished mechanosensitivity to load. Osteocytes from aged mice also lacked the well-correlated relationship between Ca2+ signaling synchrony and cell-cell distance exhibited by young-adult osteocyte networks. Taken together, we have demonstrated, for the first time, a real-time measure of the dampened mechanosensing and lack of signal coordination in aged osteocyte networks in situ, which may contribute to blunted long-term bone formation responses to load.

Next, we utilized the ex vivo Ca2+ signaling model to investigate the effect of bone formation in response to treatment with sclerostin antibody (Scl-Ab) on osteocyte mechanosensing. Previous studies have identified two phases of bone formation response to Scl-Ab treatment: an initial period of rapid bone formation with short-term dosing and a return to a steady phase of bone formation response with long-term dosing. Thus, we treated mice according to three groups: vehicle, short-term Scl-Ab, and long-term Scl-Ab. Serum P1NP assays and biweekly micro-CT scans throughout the treatment period confirmed the two phases of bone formation response to Scl-Ab. At the conclusion of treatment, under ex vivo whole-bone loading matched at 10 N, there were no significant differences in osteocyte Ca2+ signaling parameters between treatment groups. However, under strain-matched loading, fewer osteocytes from the short-term group exhibited Ca2+ responses and the initiation of Ca2+ signaling was delayed.

We interpreted this as reduced mechanosensing in osteocytes that have been newly-embedded in bone that has been rapidly formed in response to Scl-Ab, as confirmed by alizarin red intensity analysis in the osteocyte field of view ex vivo. This study provides real-time evidence of the cellular responses under the distinct phases of bone formation response to Scl-Ab and demonstrates that osteocyte mechanosensing is maintained with long-term treatment, suggesting that other mechanisms may be responsible for self-regulation of bone formation. Given the robust Ca2+ responses to load characterized in osteocytes by our group and others, we concluded this work by investigating a consequence of this mechanism that may contribute to osteocyte mechanotransduction. A common Ca2+-dependent mechanism that has been demonstrated in osteocytes in vitro with possible implications for cell-cell communication is contraction of the actin cytoskeleton. Therefore, we sought to confirm this mechanism in osteocytes maintained in their native 3D network and morphology using the ex vivo murine tibia model.

We successfully enhanced the model to simultaneously image intracellular Ca2+ and the F-actin network of individual osteocytes in situ at high magnification using transgenic Lifeact mice paired with either Ca2+ dye or bred with Ca2+ indicator mice. In both models, using biochemical stimuli, we quantified actin network dynamics over time and identified Ca2+-dependent contractile events. Under mechanical loading, phasic actin network contractions corresponded to individual Ca2+ peaks in single osteocytes. The mechanosensitive nature of these contractions was demonstrated by comparing cellular dynamics in single cells under two paired mechanical loading levels; interestingly, mechanosensitivity was dependent on the order of application of these load magnitudes. In identifying this novel mechanosensitive Ca2+-dependent mechanism, we enhance the understanding of the mechanotransduction pathway in osteocytes and have provided a potential point of intervention in cases where osteocyte mechanotransduction is inhibited, such as in osteoporosis.

Taken together, this body of work contributes to knowledge of how osteocytes are sensing mechanical forces in different contexts and transducing signals to effector cells. We provide novel, real-time, immediate measures of osteocyte mechanosensing in situ that may correspond to whole-bone responses, such as age-induced bone loss or the differential responses to Scl-Ab treatment. Future work will focus on ways to recover diminished osteocyte mechanosensing and further connect the cell responses we observe herein to long-term bone formation responses in clinical applications.
Notes: Department: Biomedical Engineering.

Thesis advisor: X. Edward Guo.

Thesis (Ph.D.)--Columbia University, 2019.