Chondrocyte-like cells in nucleus pulposus and articular chondrocytes have similar transcriptomic profiles and are paracrine-regulated by hedgehog from notochordal cells and subchondral bone
Objective: The nucleus pulposus (NP) comprises notochordal NP cells (NCs) and chondrocyte-like NP cells (CLCs). Although morphological similarities between CLCs and chondrocytes have been reported, interactions between CLCs and NCs remain unclear. In this study, we aimed to clarify regulatory mechanisms of cells in the NP and chondrocytes. Design: We performed single-cell RNA sequencing (scRNA-seq) analysis of the articular cartilage (AC) and NP of three-year-old cynomolgus monkeys in which NCs were present. We then performed immunohistochemical analysis of NP and distal femur. We added sonic hedgehog (SHH) to primary chondrocyte culture. Results: The scRNA-seq analysis revealed that CLCs and some articular chondrocytes had similar gene expression profiles, particularly related to GLI1, the nuclear mediator of the hedgehog pathway. In the NP, cell-cell interaction analysis revealed SHH expression in NCs, resulting in hedgehog signaling to CLCs. In contrast, no hedgehog ligands were expressed by chondrocytes in AC samples. Immunohistochemical analysis of the distal end of femur indicated that SHH and Indian hedgehog (IHH) were expressed around the subchondral bone that was excluded from our scRNA-seq sample. scRNA-seq data analysis and treatment of primary chondrocytes with SHH revealed that hedgehog proteins mediated an increase in hypoxia-inducible factor 1-alpha (HIF-1α) levels. Conclusion: CLCs and some articular chondrocytes have similar transcriptional profiles, regulated by paracrine hedgehog proteins secreted from NCs in the NP and from the subchondral bone in the AC to promote the HIF-1α pathway. Keywords: HIF-1α; chondrocytes; hedgehog; nucleus pulposus cells; single-cell RNA sequencing.
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组织水平:空间多组学、多重荧光免疫组化、免疫组化、免疫荧光
数据分析:流式数据分析、组化数据分析、多因子数据分析
基因水平:PCR Array、RT-PCR、PCR、单细胞测序
蛋白水平:MSD、Luminex、CBA、Elispot、Antibody Array、ELISA、Sengenics
细胞水平:细胞染色、细胞分选、细胞培养、细胞功能
组织水平:空间多组学、多重荧光免疫组化、免疫组化、免疫荧光
数据分析:流式数据分析、组化数据分析、多因子数据分析
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