Roles of Sp7 in osteoblasts for the proliferation, differentiation, and osteocyte process formation

Intake of eggshell membrane enhances bone mass and suppresses bone marrow adiposity in normal growing rats

Eggshell membrane intake is considered to have beneficial effects on bone health; however, relevant evidence remains scant. Therefore, we aimed to explore the direct effects of eggshell membrane intake on osteogenic function in normal growing rats. Six-week-old male Wistar rats were divided into control (CO) and eggshell membrane (EM) groups. The experiment was conducted over 8 weeks. Visual observation and micro-computed tomography analysis revealed a significant increase in bone mass in the EM group compared with that in the CO group. Histological analysis showed thick and long trabeculae in the EM group, accompanied by an increase in the number of osteoblasts and suppression of adipocyte accumulation. Furthermore, Col1a1 expression was significantly higher in the EM group than in the CO group, although no significant differences were found in the number of TRAP-positive osteoclasts or Ctsk expression. Immunohistochemical analysis demonstrated a notable increase in the number of Col1-positive osteoblasts but a significant decrease in the number of Dlk1-positive adipocytes in the EM group. Gene expression analysis revealed no difference in the expression of Runx2 (the master regulator of osteoblast differentiation) between the groups. However, the expression of Sp7, which functions downstream of Runx2, was significantly upregulated, whereas that of Pparg, the master regulator of adipocyte differentiation, was significantly downregulated in the EM group compared with those in the CO group. Overall, the intake of eggshell membranes may enhance osteogenic function and suppress bone marrow adiposity. These findings support the beneficial effects of eggshell membrane intake on bone health.

A novel optimized silver nitrate staining method for visualizing the osteocyte lacuno-canalicular system

A 50% (w/v, equivalent to 2.943 mol/L) silver nitrate solution is commonly used to stain and characterize the osteocyte lacuno-canalicular system (LCS) in bone biology research. However, variability in reagent concentrations and types, along with inconsistent staining procedures, have limited the broader application of this method in osteocyte research. In this study, we present a novel optimized silver nitrate staining technique aimed at addressing these limitations. This new method utilizes a 1 mol/L (equivalent to 16.987%, w/v) silver nitrate solution in combination with a type-B gelatin-formic acid solution at various concentrations (0.05%-0.5% gelatin and 0.05%-5% formic acid, or 1%-2% gelatin and 0.1%-2% formic acid) in volume ratios of 4:1, 2:1, or 1:1, or a 0.5 mol/L silver nitrate solution at a 4:1 ratio. The staining process is carried out for 1 hour under ultraviolet light or 90 minutes under regular room light (or dark), followed by washing with Milli-Q water to terminate the reaction. We applied this new method to stain the osteocyte LCS in bone samples from different species and pathological bone models. The technique consistently produced clear, distinct staining patterns across all samples. Moreover, our novel method revealed a greater number of LCS compared to the traditional 50% silver nitrate solution. This suggests that the commonly used 50% silver nitrate method may disrupt or inadequately reveal the LCS in bones, potentially leading to an underestimation of LCS density and number. In conclusion, our novel silver nitrate staining method provides a simpler and more cost-effective alternative to the traditional technique. By offering a more accurate and comprehensive analysis of the LCS across species, this approach has the potential to advance research on osteocyte morphogenesis, as well as the functional and evolutionary adaptations of the osteocyte LCS across different taxa.

Deep Neural Networks Based on Sp7 Protein Sequence Prediction in Peri-Implant Bone Formation

Objective: Peri-implant bone regeneration is crucial for dental implant success, particularly in managing peri-implantitis, which causes inflammation and bone loss. SP7 (Osterix) is vital for osteoblast differentiation and bone matrix formation. Advances in deep neural networks (DNNs) offer new ways to analyze protein sequences, potentially improving our understanding of SP7's role in bone formation. This study aims to develop and utilize DNNs to predict the SP7 protein sequence and understand its role in peri-implant bone formation. Materials: and Methods: Sequences were retrieved from UniProt IDs Q8TDD2 and Q9V3Z2 using the UniProt dataset. The sequences were Sp7 fasta sequences. These sequences were located, and their quality was assessed. We built an architecture that can handle a wide range of input sequences using a DNN technique, with computing needs based on the length of the input sequences. Results: Protein sequences were analyzed using a DNN architecture with ADAM optimizer over 50 epochs, achieving a sensitivity of 0.89 and a specificity of 0.82. The receiver operating characteristic (ROC) curve demonstrated high true-positive rates and low false-positive rates, indicating robust model performance. Precision-recall analysis underscored the model's effectiveness in handling imbalanced data, with significant area under the curve (AUC-PR). Epoch plots highlighted consistent model accuracy throughout training, confirming its reliability for protein sequence analysis. Conclusion: The DNN employed with ADAM optimizer demonstrated robust performance in analyzing protein sequences, achieving an accuracy of 0.85 and high sensitivity and specificity. The ROC curve highlighted the model's effectiveness in distinguishing true positives from false positives, which is essential for reliable protein classification. These findings suggest that the developed model is promising for enhancing predictive capabilities in computational biology and biomedical research, particularly in protein function prediction and therapeutic development applications.

Epigenetic Regulation of ZNF687 by miR-142a-3p and DNA Methylation During Osteoblast Differentiation and Mice Bone Development and Aging

Zinc finger protein 687 (ZNF687), a transcription factor implicated in osteoblast/osteoclast differentiation and linked to Paget's disease of bone, has unclear mechanisms in bone metabolism. Epigenetic disruptions can affect bone cell activity and contribute to bone-related diseases. This work aimed to elucidate the regulatory role of epigenetics in modulating Zfp687 expression throughout osteoblast differentiation and bone growth/aging in mice. Differentiation of the mouse-derived osteoblast precursor cell line (MC3T3-E1) showed increased expression of osteogenic markers and decreased Zfp687 expression. In the hindlimb bones of C57BL/6J mice, the expression of most bone-forming genes decreased from youth to adulthood, while Zfp687 and Runx2 expression was maintained, being only significantly reduced in old mice in comparison to young mice. Bisulfite sequencing revealed hypomethylation of the Zfp687 promoter during MC3T3-E1 differentiation and bone growth/aging. Bioinformatics predicted miR-142a-3p, miR-122b-5p, and miR-124-3p binding sites in Zfp687 3'UTR, and RT-qPCR analysis showed higher expression of these miRNAs in mature osteoblasts. Transfection of a miR-142-3p mimic reduced luciferase activity in the wildtype Zfp687 3'UTR but not the mutant 3'UTR and downregulated the Zfp687 gene and protein levels. In conclusion, miR-142a-3p directly targets the Zfp687 3'UTR, promoting its downregulation during osteoblastogenesis. Furthermore, DNA methylation does not appear to regulate Zfp687 during osteoblast differentiation or bone development in mice.

Regulation of Skeletal Development and Maintenance by Runx2 and Sp7

Runx2 (runt related transcription factor 2) and Sp7 (Sp7 transcription factor 7) are crucial transcription factors for bone development. The cotranscription factor Cbfb (core binding factor beta), which enhances the DNA-binding capacity of Runx2 and stabilizes the Runx2 protein, is necessary for bone development. Runx2 is essential for chondrocyte maturation, and Sp7 is partly involved. Runx2 induces the commitment of multipotent mesenchymal cells to osteoblast lineage cells and enhances the proliferation of osteoprogenitors. Reciprocal regulation between Runx2 and the Hedgehog, fibroblast growth factor (Fgf), Wnt, and parathyroid hormone-like hormone (Pthlh) signaling pathways and Dlx5 (distal-less homeobox 5) plays an important role in these processes. The induction of Fgfr2 (Fgf receptor 2) and Fgfr3 expression by Runx2 is important for the proliferation of osteoblast lineage cells. Runx2 induces Sp7 expression, and Runx2+ osteoprogenitors become Runx2+Sp7+ preosteoblasts. Sp7 induces the differentiation of preosteoblasts into osteoblasts without enhancing their proliferation. In osteoblasts, Runx2 is required for bone formation by inducing the expression of major bone matrix protein genes, including Col1a1 (collagen type I alpha 1), Col1a2, Spp1 (secreted phosphoprotein 1), Ibsp (integrin binding sialoprotein), and Bglap (bone gamma carboxyglutamate protein)/Bglap2. Bglap/Bglap2 (osteocalcin) regulates the alignment of apatite crystals parallel to collagen fibrils but does not function as a hormone that regulates glucose metabolism, testosterone synthesis, and muscle mass. Sp7 is also involved in Co1a1 expression and regulates osteoblast/osteocyte process formation, which is necessary for the survival of osteocytes and the prevention of cortical porosity. SP7 mutations cause osteogenesis imperfecta in rare cases. Runx2 is an important pathogenic factor, while Runx1, Runx3, and Cbfb are protective factors in osteoarthritis development.