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Updated: May 1, 2026

Analysis and Imaging of Osteocytes
Published on: November 29, 2024
Integrative transcriptomic and proteomic analysis of osteocytic cells exposed to fluid flow reveals novel
Peter M Govey1, Jon M Jacobs2, Susan C Tilton2
1Division of Musculoskeletal Sciences, Department of Orthopaedics and Rehabilitation, Penn State College of Medicine, Hershey, PA 17033, USA.
Abstract:
Osteocytes, positioned within bone׳s porous structure, are subject to interstitial fluid flow upon whole bone loading. Such fluid flow is widely theorized to be a mechanical signal transduced by osteocytes, initiating a poorly understood cascade of signaling events mediating bone adaptation to mechanical load. The objective of this study was to examine the time course of flow-induced changes in osteocyte gene transcript and protein levels using high-throughput approaches. Osteocyte-like MLO-Y4 cells were subjected to 2h of oscillating fluid flow (1Pa peak shear stress) and analyzed following 0, 2, 8, and 24h post-flow incubation. Transcriptomic microarray analysis, followed by gene ontology pathway analysis, demonstrated fluid flow regulation of genes consistent with both known and unknown metabolic and inflammatory responses in bone. Additionally, two of the more highly up-regulated gene products - chemokines Cxcl1 and Cxcl2, supported by qPCR - have not previously been reported as responsive to fluid flow. Proteomic analysis demonstrated greatest up-regulation of the ATP-producing enzyme NDK, calcium-binding Calcyclin, and G protein-coupled receptor kinase 6. Finally, an integrative pathway analysis merging fold changes in transcript and protein levels predicted signaling nodes not directly detected at the sampled time points, including transcription factors c-Myc, c-Jun, and RelA/NF-κB. These results extend our knowledge of the osteocytic response to fluid flow, most notably up-regulation of Cxcl1 and Cxcl2 as possible paracrine agents for osteoblastic and osteoclastic recruitment. Moreover, these results demonstrate the utility of integrative, high-throughput approaches in place of a traditional candidate approach for identifying novel mechano-sensitive signaling molecules.
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