A biomimetic calcium phosphate nanowire coating on titanium surface enhances osteoimmunomodulation and osteointegration

The appropriate immune microenvironment plays crucial roles in bone regeneration. Surface structure and chemisty are key factors affecting immune cells behaivor and subsequently regulating the activity of bone-related cells. To achieve rapid osteointegration, this study prepared a biomimetic calcium phosphate (CaP) coating on Ti-based substrates (THCaP) with the help of oleic acid under hydrothermal condition. The coating was composed of hydroxyapatite nanowires and further self-assembled into macropores. Also, the effect of the biomimetic CaP coating on the immune response of macrophages and the impact on angiogenesis and osteogenesis were investigated. In vitro cell culture results showed that compared with pristine Ti and similar titanate nanowire structure (TH), THCaP not only stimulated the polarization of macrophages towards to pro-healing M2 phenotype, but also enhanced the angiogenic and osteogenic differentiation of endothelial cells and preosteoblastic cells, respectively. Especially, macrophages on THCaP induced a favorable immune microenvironment and further facilitated the osteogenic diffferention of preosteoblastic cells. In vivo tests confirmed the aforementioned results, which proved that the implanted THCaP could decrease the inflammatory response and facilitate new bone formation when compared with pristine Ti and TH implants. These findings indicate that preparation of biomimetic CaP network structure is a promising strategy to surface design of Ti-based substrates, which is beneficial to generate a favorable osteoimmunomodulatory microenvironment for enhancing osteointegration. To investigate the immunomodulatory effects of titanium surface bionic calcium phosphate nanowire coating (THCaP), we used the Raw 264.7 cells line with titanate nanowires (TH) obtained by alkaline heat treatment as control samples. The total RNAs from cells on the samples were extracted after culture of 1 d, then we performed gene expression profiling analysis using data obtained from RNA-seq.