Self-assembled peptide hydrogel loaded with functional peptide Dentonin accelerates vascularized bone tissue regeneration in critical-size bone defects

Regeneration of oral craniofacial bone defects is a complex process, and reconstruction of large bone defects without the use of exogenous cells or bioactive substances remains a major challenge. Hydrogels are highly hydrophilic polymer networks with the potential to promote bone tissue regeneration. In this study, functional peptide Dentonin was loaded onto self-assembled peptide hydrogels (RAD) to constitute functionally self-assembling peptide RAD/Dentonin hydrogel scaffolds with a view that RAD/Dentonin hydrogel could facilitate vascularized bone regeneration in critical-size calvarial defects. The functionalized peptide RAD/Dentonin forms highly ordered beta-sheet supramolecular structures via non-covalent interactions like hydrogen bonding, ultimately assembling into nano-fiber network. RAD/Dentonin hydrogels exhibited desirable porosity and swelling properties, and appropriate biodegradability. RAD/Dentonin hydrogel supported the adhesion, proliferation and three-dimensional migration of bone marrow mesenchymal stem cells (BMSCs) and has the potential to induce differentiation of BMSCs towards osteogenesis through activation of the Wnt/beta-catenin pathway. Moreover, RAD/Dentonin hydrogel modulated paracrine secretion of BMSCs and increased the migration, tube formation and angiogenic gene expression of human umbilical vein endothelial cells (HUVECs), which boosted the angiogenic capacity of HUVECs. In vivo, RAD/Dentonin hydrogel significantly strengthened vascularized bone formation in rat calvarial defect. Taken together, these results indicated that the functionalized self-assembling peptide RAD/Dentonin hydrogel effectively enhance osteogenic differentiation of BMSCs, indirectly induce angiogenic effects in HUVECs, and facilitate vascularized bone regeneration in vivo. Thus, it is a promising bioactive material for oral and maxillofacial regeneration. Graphical Abstract