Bone is a “smart” living tissue that adapts to its mechanical environment. Yet, the mechanisms by which bone senses and responds to the external mechanical stimuli remain inconclusive. The work presented in this thesis aimed at understanding the mechanotransduction process in osteocytes, the most abundant and major mechanical sensing cells in bone, with a special focus on pericellular matrix (PCM).

Three independent studies are included in this thesis. In my first study, a multiscale computational model was built based on micro-computed tomography (μCT) of a murine tibia subjected to mechanical loading in order to predict how the mechanical signals at the whole bone level results in tissue level signals (matrix strain, pore pressure) and cellular level stimuli (interstitial fluid flow, shear stress and drag force). The model coupled the elastic whole bone, the biphasic poroelastic bone segment, and the ultrastructural Brinkman canalicular fluid flow. The results expanded our previous experimental measurements at limited locations near periosteum and provided spatialtemporal profiles of mechanical stimuli in a larger bone segment relevant to bone adaptation in vivo. In the second study, I focused on how these mechanical stimuli activate osteocyte’s intracellular calcium signaling and downstream pathways in vivo and how these responses are altered when the osteocytic PCM loses the normal expression of perlecan. Our group previously demonstrated diminished anabolic effects from loading in perlecan deficient mouse (termed Hypo) compared to wildtype controls and proposed that the linear perlecan acts as a flow sensor for transducing mechanical signals to osteocytes. In this study, I utilized the next generation RNA sequencing and bioinformatics analysis and found that perlecan deficiency significantly suppressed bone’s mechanotransduction pathways (ECM-receptor interaction, focal adhesion and intracellular calcium signaling) following repetitive loading. By in situ intracellular calcium imaging I found decreased response rate, reduced number of calcium peaks and slower recovery speed in the Hypo osteocytes. In the third study, I explored the stability of the osteocytic PCM flow sensors. Although the turnover of bone’s territorial extracellular matrix is well understood, the synthesis and degradation (turnover) of the PCM around osteocytes have not been studied due to its small dimension and encasement in the mineralized matrix. To overcome the challenge, I developed a novel method based on metabolic labeling and “click” chemistry, which allowed labeling and tracking the de novo PCM of osteocytes for the first time. I demonstrated the capability of the technique and the shifting of PCM synthesis in osteocytes from aged vs. young mice. Most importantly, I confirmed that the osteocyte PCM is indeed stable with a halflife time of 8-10 weeks under normal locomotion, but tibial loading or hindlimb suspension greatly accelerates the turnover of PCM as its half-life time shortened to 2- 3 weeks via upregulation of the membrane-bound matrix metallopeptidase MMP14.

Taken together, this thesis contributes to our understanding of bone mechanotransduction and, in particular, the role of osteocytic PCM in the process. The osteocytic PCM regulates not only how osteocytes perceive the mechanical signals imparted by physiological loading, but also their downstream responses to mechanical stimuli. The accelerated turnover of the osteocytic PCM under loading and disuse suggests, for the first time, a mechanical-driven feedback loop in the osteocyte between its sensing complex and mechanical inputs. The osteocytic PCM could be a potential treatment target for bone related diseases such as osteoporosis.