| Mechanical loading of bone results in various osteogenic stimuli, including new bone formation as well as repair. Osteocytes are thought to be critical for sending signals to other bone cells. However, few markers for osteocytes are recognized and the gene expression patterns and signaling pathways of osteocytes responding to mechanical loading are not well defined. To understand the characteristic genes of osteocytes and the mechanism of how cellular information is transmitted by mechanical loading in bone to the genome, we investigated load responsive gene expression patterns using Mouse 5k oligonucleotide microarrays and the 2T3 osteoblast-osteocyte differentiation cell model and MLO-Y4 osteocyte-like cell model. After hybridization experiments, gene expression intensities were quantified and statistically analyzed in triplicate experiments. Northern analysis was performed to validate key gene expression patterns. We then performed several clustering algorithms based on pattern similarity to organize clusters of expression patterns. Functional classification was used to evaluate the biological features of the data. From these diverse data sets, we built gene expression and pathway maps. With this study, we derived several biological hypotheses from the gene expression profiles regarding loading responsive signaling pathways in bone cells. |