Int J Stem Cells.  2023 Aug;16(3):342-355. 10.15283/ijsc22101.

Dissection of Cellular Communication between Human Primary Osteoblasts and Bone Marrow Mesenchymal Stem Cells in Osteoarthritis at Single-Cell Resolution

• Liu Y
• Chen Y
• Li XH
• Cao C
• Zhang HX
• Zhou C
• Chen Y
• Gong Y
• Yang JX
• Cheng L
• Chen XD
• Shen H
• Xiao HM
• Tan LJ
• Deng HW

• KMID: 2545233
• DOI: http://doi.org/10.15283/ijsc22101

Abstract

Background and Objectives
Osteoblasts are derived from bone marrow mesenchymal stem cells (BMMSCs) and play important role in bone remodeling. While our previous studies have investigated the cell subtypes and heterogeneity in osteoblasts and BMMSCs separately, cell-to-cell communications between osteoblasts and BMMSCs in vivo in humans have not been characterized. The aim of this study was to investigate the cellular communication between human primary osteoblasts and bone marrow mesenchymal stem cells.
Methods and Results
To investigate the cell-to-cell communications between osteoblasts and BMMSCs and identify new cell subtypes, we performed a systematic integration analysis with our single-cell RNA sequencing (scRNA-seq) transcriptomes data from BMMSCs and osteoblasts. We successfully identified a novel preosteoblasts subtype which highly expressed ATF3, CCL2, CXCL2 and IRF1. Biological functional annotations of the transcriptomes suggested that the novel preosteoblasts subtype may inhibit osteoblasts differentiation, maintain cells to a less differentiated status and recruit osteoclasts. Ligand-receptor interaction analysis showed strong interaction between mature osteoblasts and BMMSCs. Meanwhile, we found FZD1 was highly expressed in BMMSCs of osteogenic differentiation direction. WIF1 and SFRP4, which were highly expressed in mature osteoblasts were reported to inhibit osteogenic differentiation. We speculated that WIF1 and sFRP4 expressed in mature osteoblasts inhibited the binding of FZD1 to Wnt ligand in BMMSCs, thereby further inhibiting osteogenic differentiation of BMMSCs.
Conclusions
Our study provided a more systematic and comprehensive understanding of the heterogeneity of osteogenic cells. At the single cell level, this study provided insights into the cell-to-cell communications between BMMSCs and osteoblasts and mature osteoblasts may mediate negative feedback regulation of osteogenesis process.

Keyword

Single-cell RNA sequencing (scRNA-seq); Bone marrow mesenchymal stem cells (BMMSCs); Osteoblasts; Cellular heterogeneity

Figure

• 

  Fig. 1 Integration of transcriptome data of BMMSCs and osteoblasts. (A) UMAP visualization of the osteogenesis cells (n=8,841 cells) in distinct clusters. Each point was one cell, and colors indicated graph-based cluster assignments. BMMSCs1, BMMSCs2 and Osteoblast on the top right corner represented three different subjects. (B) Correlation of gene expression between two BMMSCs subjects. Each dot represented an individual gene. Axis measure the average gene expression level in the indicated subject (axis is log-scaled). Correlation was tested by Pearson correlation coefficient (R2=0.96, p<0.01). (C) Violin plots showed the log-transformed normalized expression levels of the most significant marker genes in each cluster. (D) Dot plot showed selected biological processes (BPs) in the GO analysis of clusters. X-axis, gene ratio; Y-axis, enriched BP terms in clusters; color (red, high; blue, low), -log10(p-adjusted) of each term.

• 

  Fig. 2 Reconstruction of the developmental trajectory of BMMSCs and osteoblasts. (A) Cell differentiation pseudotime trajectory of osteogenesis clusters reconstructed with diffusion mapping. The trajectory graph on the upper right showed the direction of pseudotime from deep to shallow. (B) Distribution of each cell subpopulation along the pseudotime. (C) The expression levels (log-normalized) of key specific genes fluctuated with osteogenesis development. The x-axis indicated the pseudotime, while the y-axis represented the log-normalized gene expression levels. The colors corresponded to the six different osteogenesis cell subsets. (D) UMAP plots of osteogenesis cells, colored by expression of the indicated genes with roles in osteogenic differentiation.

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  Fig. 3 GO terms and the expression of marker genes in six clusters. (A) Osteogenic differentiation and bone formation related GO terms enriched in six clusters. The size of dot indicated the gene ratio. The colors indicated the adjusted p-value for enrichment analysis. (B) The expression of several significant genes in each osteogenesis cell cluster.

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  Fig. 4 Construction of cellular communication network. (A) Network plot showed the number of ligand-receptor interactions detected between each two cell clusters and/or within the same cell cluster. (B) The Circos diagram showed the top 30 highly expressed ligand-receptor pairs interactions in the 6 clusters. (C) The violin chart showed the expression of ligand and receptor genes in each cell cluster.

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  Fig. 5 Protein-protein network interaction between mature osteoblasts and BMMSCs. (A) Mature osteoblasts cluster and BMMSC1 cluster were marked in oval and hexagon, respectively. (B) Subnets of FZD1, WIF1 and SFRP4. (C) Violin plots demonstrated the expression of FZD1, WIF1, and sFRP4 in each osteogenesis cluster. ns: not significant, *p-adjusted ≤0.05, ****p-adjusted ≤0.001. (D) Schematic representation of SFRP4 and WIF1 involved in the WNT signaling pathway.

Reference

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