Int J Stem Cells.  2022 May;15(2):173-182. 10.15283/ijsc21042.

Single-Cell RNA Sequencing of Bone Marrow Mesenchymal Stem Cells from the Elderly People

• Zhu D
• Gao J
• Tang C
• Xu Z
• Sun T

• KMID: 2529789
• DOI: http://doi.org/10.15283/ijsc21042

Abstract

Background and Objectives
Bone marrow mesenchymal stem cells (BMSCs) show considerable promise in regenerative medicine. Many studies demonstrated that BMSCs cultured in vitro were highly heterogeneous and composed of diverse cell subpopulations, which may be the basis of their multiple biological characteristics. However, the exact cell subpopulations that make up BMSCs are still unknown.
Methods and Results
In this study, we used single-cell RNA sequencing (scRNA-Seq) to divide 6,514 BMSCs into three clusters. The number and corresponding proportion of cells in clusters 1 to 3 were 3,766 (57.81%), 1,720 (26.40%), and 1,028 (15.78%). The gene expression profile and function of the cells in the same cluster were similar. The vast majority of cells expressed the markers defining BMSCs by flow cytometry and gene expression analysis. Each cluster had at least 20 differentially expressed genes (DEGs). We conducted Gene Ontology enrichment analysis on the top 20 DEGs of each cluster and found that the three clusters had different functions, which were related to self-renewal, multilineage differentiation and cytokine secretion, respectively. In addition, the function of the top 20 DEGs of each cluster was checked by the National Center for Biotechnology Information gene database to further verify our hypothesis.
Conclusions
This study indicated that scRNA-Seq can be used to divide BMSCs into different subpopulations, demon-strating the heterogeneity of BMSCs.

Keyword

Bone marrow mesenchymal stem cells; Single-cell RNA sequencing; Subpopulation; Heterogeneity

Figure

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  Fig. 1 Expression of BMSCs markers by flow cytometry analysis and scRNA-seq. (a) Expression of surface marker antigens of the BMSCs. (b) Expression patterns of characteristic marker genes were projected on the t-SNE plot. (c) Expression patterns of marker gene for early passage BMSCs, FGFR2, and late passage BMSCs, PLAT, were projected on the t-SNE plot. Each cell is coloured based on the expression level of the indicated marker gene.

• 

  Fig. 2 The barcode on the left of the green marker line is the valid cell, and the Barcode on the right is the background. The figure on the right of the marker line has a steep downward trend, indicating that the effective cells are well differentiated from the background. The intersection point between the marker line and the abscissa is the effective cell number.

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  Fig. 3 T-SNE projection of cells colored by clustering. Each dot in the figure represents a cell. The legend on the right is the name of the cluster. Different colors represent different clusters.

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  Fig. 4 Clustering heat map of top 20 DEGs corresponding to the three clusters. Each column in the figure represents a gene and each row represents a cluster. Each small area color in the heat map represents the average expression level of the corresponding gene in the cluster. As shown in the right legend, the color from red to blue represents the gene expression from high to low. Different clusters are distinguished by different colors in the first line.

Reference

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