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. 2022 May 7;13(1):187.
doi: 10.1186/s13287-022-02873-5.

The role of serum amyloid A1 in the adipogenic differentiation of human adipose-derived stem cells basing on single-cell RNA sequencing analysis

Affiliations

The role of serum amyloid A1 in the adipogenic differentiation of human adipose-derived stem cells basing on single-cell RNA sequencing analysis

Rongmei Qu et al. Stem Cell Res Ther. .

Abstract

Background: Adipose-derived stem cells (ASCs) are obtained from a variety of sources in vivo where they present in large quantities. These cells are suitable for use in autologous transplantation and the construction of tissue-engineered adipose tissue. Studies have shown that ASCs differentiation is in a high degree of heterogeneity, yet the molecular basis including key regulators of differentiation remains to clarify.

Methods: We performed single-cell RNA sequencing and bioinformatics analysis on both undifferentiated (ASC-GM group) and adipogenically differentiated human ASCs (ASC-AD group, ASCs were cultured in adipogenic inducing medium for 1 week). And then, we verified the results of serum amyloid A1 (SAA1) with western blotting, immunofluorescence staining, oil red O staining. After these experiments, we down-regulated the expression of serum amyloid A1 (SAA1) gene to verify the adipogenic differentiation ability of ASCs.

Results: In single-cell RNA sequence analyzing, we obtained 4415 cells in the ASC-GM group and 4634 cells in the ASC-AD group. The integrated sample cells could be divided into 11 subgroups (0-10 cluster). The cells in cluster 0, 2, 5 were came from ASC-GM group and the cells in cluster 1, 3, 7 came from ASC-AD group. The cells of cluster 4 and 6 came from both ASC-GM and ASC-AD groups. Fatty acid binding protein 4, fatty acid binding protein 5, complement factor D, fatty acid desaturase 1, and insulin like growth factor binding protein 5 were high expressed in category 1 and 7. Regulation of inflammatory response is the rank 1 biological processes. And cellular responses to external stimuli, negative regulation of defense response and acute inflammatory response are included in top 20 biological processes. Based on the MCODE results, we found that SAA1, C-C Motif Chemokine Ligand 5 (CCL5), and Annexin A1 (ANXA1) significantly highly expressed during adipogenic differentiation. Western blot and immunofluorescent staining results showed that SAA1 increased during adipogenesis. And the area of ORO positive staining in siSAA1 cells was significantly lower than in the siControl (negative control) cells.

Conclusions: Our results also indicated that our adipogenic induction was successful, and there was great heterogeneity in the adipogenic differentiation of ASCs. SAA1 with the regulation of inflammatory response were involved in adipogenesis of ASCs based on single-cell RNA sequencing analysis. The data obtained will help to elucidate the intrinsic mechanism of heterogeneity in the differentiation process of stem cells, thus, guiding the regulation of self-renewal and differentiation of adult stem cells.

Keywords: Adipogenesis; Adipose-derived stem cells (ASCs); Regulation of inflammatory response; Serum amyloid A1 (SAA1); Single-cell transcriptomic sequencing (scRNA-seq).

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Fig. 1
Fig. 1
Single-cell RNA-seq data quality assessment and comparison between the AD and GM group of ASCs. A The proportion of specific RNA, RNA expression, and mitochondrial gene expression in the samples of the GM and AD groups. B The relationships among specific RNA, RNA expression, and mitochondrial gene expression in the samples of the GM and AD groups. C The expression distribution of the top 20 principal components in 100 different cell types in the samples of the GM and AD groups
Fig. 2
Fig. 2
A UMAP clustering results of the top 30 principal components and sample distribution. B The distribution of subpopulations of two samples in the integrated data UMAP clustering results. C The UMAP clustering of each subgroup of the integrated data in the two samples. D The number of cells distributed in each subgroup in the integrated data UMAP cluster
Fig. 3
Fig. 3
Distribution map of the top 2 tag genes expressed in different subgroups. The color depth represents the intensity of expression in the samples
Fig. 4
Fig. 4
Expression distribution map and violin diagram of the top 2 differentially expressed genes in each subgroup. A An expression distribution map. B Violin diagram
Fig. 5
Fig. 5
Heatmap of the top 5 tag genes expressed in different subgroups. Each row represents a gene, and each column represents a single cell, and the color depth represents the intensity of expression in the samples of the GM and AD groups
Fig. 6
Fig. 6
Pathway and process enrichment analysis. A Bar graph of enriched terms across input gene lists, colored by p values. The network of enriched terms: B colored by cluster ID, where nodes that share the same cluster ID are typically close to each other. Each term is represented by a circle node, where its size is proportional to the number of input genes fall into that term, and its color represents its cluster identity (i.e., nodes of the same color belong to the same cluster). Terms with a similarity score > 0.3 are linked by an edge (the thickness of the edge represents the similarity score). The network is visualized with Cytoscape with “force-directed” layout and with edge bundled for clarity. One term from each cluster is selected to have its term description shown as label. C The same enrichment network has its nodes colored by p value, as shown in the legend. The dark the color, the more statistically significant the node is (see legend for p value ranges). D protein–protein interaction network and MCODE components identified in the gene lists. MCODE algorithm was then applied to this network to identify neighborhoods where proteins are densely connected. Each MCODE network is assigned a unique color. GO enrichment analysis was applied to each MCODE network to assign “meanings” to the network component
Fig. 7
Fig. 7
SAA1 changed during the adipogenic differentiation of human ASCs. A Protein expression analysis of SAA1 and adipogenic differentiation protein markers after adipogenic-induced one week. GAPDH was used as the internal reference gene. Mean ± SD, *p < 0.05, n = 3. GM: human ASCs were cultured in growth medium; AD1W: human ASCs were cultured in adipogenic inducing medium 1 week. B Morphological changes of SAA1 during the adipogenic differentiation of ASCs. SAA1 is marked in red, microfilaments are marked with phalloidin in green, and the nucleus is marked with DAPI in blue. Scale bar = 50 µm. Mean ± SD, ** P < 0.01, n = 3. C Oil red O staining for triglyceride content and quantitative analysis in SAA1-silenced ASCs (siSAA1) after 4 days of adipogenic differentiation. Negative control group was siControl group. Scale bar = 100 μm. Mean ± SD, ****p < 0.0001, n = 3

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References

    1. Buehrer BM, Cheatham B. Isolation and characterization of human adipose-derived stem cells for use in tissue engineering. Methods Mol Biol. 2013;1001:1–11. doi: 10.1007/978-1-62703-363-3_1. - DOI - PubMed
    1. Zuk P. Adipose-derived stem cells in tissue regeneration: a review. ISRN Stem Cells. 2013;2013:1–35. doi: 10.1155/2013/713959. - DOI
    1. Tambuyzer E, Vandendriessche B, Austin CP, Brooks PJ, Larsson K, Needleman KIM, et al. Therapies for rare diseases therapeutic modalities, progress and challenges ahead. Nat Rev Drug Discov. 2020;19:93–111. doi: 10.1038/s41573-019-0049-9. - DOI - PubMed
    1. Bacakova L, Zarubova J, Travnickova M, Musilkova J, Pajorova J, Slepicka P, et al. Stem cells: their source, potency and use in regenerative therapies with focus on adipose-derived stem cells—a review. Biotechnol Adv. 2018;36:1111–1126. doi: 10.1016/j.biotechadv.2018.03.011. - DOI - PubMed
    1. Zhou Y, Liu Z, Welch JD, Gao X, Wang L, Garbutt T, et al. Single-cell transcriptomic analyses of cell fate transitions during human cardiac reprogramming. Cell Stem Cell. 2019;25:149–164. doi: 10.1016/j.stem.2019.05.020. - DOI - PMC - PubMed

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