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Research Paper

Comparison of stromal vascular fraction cell composition between Coleman fat and extracellular matrix/stromal vascular fraction gel

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Article: 2360037 | Received 01 Feb 2024, Accepted 21 May 2024, Published online: 03 Jun 2024

Figures & data

Figure 1. Preparation process of Coleman fat and ECM/SVF gels. ECM/SVF-gels are highly condensed in volume compared with Coleman fat. The final volume of the ECM/SVF gel was about one-quarter that of the Coleman fat.

Three 10-ml syringes respectively containing sedimented fat, Coleman fat, and ECM/SVF-gel, showing 10 ml of sedimented fat being condensed into Coleman fat through centrifugation and elimination of the upper oil layer and lower liquid layer, and Coleman fat further being condensed into an ECM/SVF-gel through mechanical emulsification, centrifugation, and elimination of the upper oil layer and lower liquid layer. The ECM/SVF-gel was highly condensed in volume compared with Coleman fat. The final volume of the ECM/SVF gel was about one-quarter that of the Coleman fat.
Figure 1. Preparation process of Coleman fat and ECM/SVF gels. ECM/SVF-gels are highly condensed in volume compared with Coleman fat. The final volume of the ECM/SVF gel was about one-quarter that of the Coleman fat.

Figure 2. Volcano plot for DEGs, between Coleman fat and ECM/SVF-gels, revealing 9 upregulated and 73 downregulated DEGs in the ECM/SVF-gel. Each dot represents a detected gene; blue dots denote downregulated DEGs, and red dots represent upregulated DEGs. DEGs, differentially expressed genes.

Figure 2. Volcano plot for DEGs, between Coleman fat and ECM/SVF-gels, revealing 9 upregulated and 73 downregulated DEGs in the ECM/SVF-gel. Each dot represents a detected gene; blue dots denote downregulated DEGs, and red dots represent upregulated DEGs. DEGs, differentially expressed genes.

Figure 3. Gene Ontology (GO) functional enrichment analysis of 73 downregulated DEGs performed using the DAVID database (A) and Metascape platform (B), revealing enrichment of biological processes mainly associated with inflammatory response and immune response. DEGs, differentially expressed genes.

Two bar plots (a and b) representing Gene Ontology functional enrichment analysis of the 73 downregulated differentially expressed genes performed respectively using the DAVID database and Metascape platform, with the X-axis denoting –log10 (FDR) and Y-axis denoting the top 20 enriched biological processes, revealing enrichment of biological processes mainly associated with inflammatory response and immune response.
Figure 3. Gene Ontology (GO) functional enrichment analysis of 73 downregulated DEGs performed using the DAVID database (A) and Metascape platform (B), revealing enrichment of biological processes mainly associated with inflammatory response and immune response. DEGs, differentially expressed genes.

Figure 4. Web-based cell-type-specific enrichment analysis (WebCSEA) of 73 downregulated DEGs, revealing vasculature macrophages, muscle macrophages, and fat macrophages as the top 3 significantly enriched tissue-cell types. The X-axis represents 11 human organ systems. Y-axis indicates the – log10 (raw p-value) for each tissue-cell type from WebCSEA result. Each dot represents one tissue-cell type in the group on the X-axis differentiated by colour. The most significant dots are highlighted and annotated with their corresponding tissue-cell types. The red dashed line indicates the Bonferroni-corrected significance (p = 3.69 × 10−5) by 1355 tissue-cell types. The grey solid line indicates the nominal significance (p = 1 × 10−3). DEGs, differentially expressed genes.

A jitter plot reflecting web-based cell-type-specific enrichment analysis (WebCSEA) of 73 downregulated differentially expressed genes, with X-axis representing 11 human organ systems, Y-axis indicating the–log10 (raw p-value) for each tissue-cell type from WebCSEA, and each dot representing one tissue-cell type in the group differentiated by color on the X-axis. The most significant dots are highlighted and annotated with their corresponding tissue-cell types, revealing vasculature macrophages, muscle macrophages, and fat macrophages as the top 3 enriched tissue-cell types.
Figure 4. Web-based cell-type-specific enrichment analysis (WebCSEA) of 73 downregulated DEGs, revealing vasculature macrophages, muscle macrophages, and fat macrophages as the top 3 significantly enriched tissue-cell types. The X-axis represents 11 human organ systems. Y-axis indicates the – log10 (raw p-value) for each tissue-cell type from WebCSEA result. Each dot represents one tissue-cell type in the group on the X-axis differentiated by colour. The most significant dots are highlighted and annotated with their corresponding tissue-cell types. The red dashed line indicates the Bonferroni-corrected significance (p = 3.69 × 10−5) by 1355 tissue-cell types. The grey solid line indicates the nominal significance (p = 1 × 10−3). DEGs, differentially expressed genes.

Figure 5. Gene set enrichment analysis (GSEA) based on whole gene expression profiles. (A and B) Gene sets involved in responses to interferon (IFN)-α and IFN-γ were enriched in the ECM/SVF-gel (FDR <0.05). (C and D) Gene sets involved in inflammatory response and adipogenesis were the top 2 gene sets enriched in Coleman fat (FDR <0.05). NES, normalized enrichment score.

Four line graphs reflecting gene set enrichment analysis results based on whole gene expression profiles, with each graph having a peak representing normalized enrichment score, which reflects the degree to which a query gene set is overrepresented at the top or bottom of the ranked gene list, ordered according to their differential expression between Coleman fat and ECM/SVF-gels. Graph A and B respectively show gene sets involved in responses to interferon (IFN)-α and IFN-γ were enriched in the ECM/SVF-gel. Graph C and D respectively show gene sets involved in inflammatory response and adipogenesis were enriched in Coleman fat.
Figure 5. Gene set enrichment analysis (GSEA) based on whole gene expression profiles. (A and B) Gene sets involved in responses to interferon (IFN)-α and IFN-γ were enriched in the ECM/SVF-gel (FDR <0.05). (C and D) Gene sets involved in inflammatory response and adipogenesis were the top 2 gene sets enriched in Coleman fat (FDR <0.05). NES, normalized enrichment score.

Figure 6. Composition of 22 immune cells in Coleman fat and the ECM/SVF-gel estimated by the CIBERSORT algorithm (only naïve CD4+ T cells were not detected in any of the samples). A. Relative proportion of 22 immune cells in each sample; B. Overall distribution of 22 immune cells in Coleman fat and the ECM/SVF-gel, indicating that M2 macrophages (28.8% vs. 23.2%), resting CD4+ memory T cells (17.9% vs. 21.5%), M1 macrophages (7.3% vs. 9.8%), resting mast cells (13.8% vs. 9.4%), and M0 macrophages (6.6% vs. 8.8%) represented the top five infiltrating cell types both in Coleman fat and the ECM/SVF-gel. In particular, M2 macrophages were the most prevalent. Each bar plot shows the cell type and relative percentage. Different colours represent different cell types, which are shown in the right side.

Two stacked histograms (A and B) presenting the composition of 22 immune cells in Coleman fat and the ECM/SVF-gel estimated by the CIBERSORT algorithm. A. Relative proportion of 22 immune cells in each sample; B. Overall distribution of 22 immune cells in Coleman fat and the ECM/SVF-gel. Different colours represent different cell types.
Figure 6. Composition of 22 immune cells in Coleman fat and the ECM/SVF-gel estimated by the CIBERSORT algorithm (only naïve CD4+ T cells were not detected in any of the samples). A. Relative proportion of 22 immune cells in each sample; B. Overall distribution of 22 immune cells in Coleman fat and the ECM/SVF-gel, indicating that M2 macrophages (28.8% vs. 23.2%), resting CD4+ memory T cells (17.9% vs. 21.5%), M1 macrophages (7.3% vs. 9.8%), resting mast cells (13.8% vs. 9.4%), and M0 macrophages (6.6% vs. 8.8%) represented the top five infiltrating cell types both in Coleman fat and the ECM/SVF-gel. In particular, M2 macrophages were the most prevalent. Each bar plot shows the cell type and relative percentage. Different colours represent different cell types, which are shown in the right side.

Figure 7. The xCell-inferred enrichment scores (xCell scores) of non-immune cell types in Coleman fat (blue) and the ECM/SVF-gel (red), indicating no statistical differences in xCell scores between the two groups. The xCell scores predict relative enrichment for cell types, resembling the fractions of the cell types, but not the exact cellular proportions. The error bar denotes standard error for the sample mean. Mesenchymal stem cells detected by xCell in adipose tissue actually were ADSCs. mv Endothelial cells, microvascular Endothelial cells.

An interleaved bar graph comparing the xCell-inferred enrichment scores (xCell scores) of non-immune cell types between Coleman fat and the ECM/SVF-gel, with X-axis denoting non-immune cell types and Y-axis denoting xCell score, indicating no statistical differences in xCell scores between the two groups. Blue bars represent Coleman fat, red bars represent the ECM/SVF-gel.
Figure 7. The xCell-inferred enrichment scores (xCell scores) of non-immune cell types in Coleman fat (blue) and the ECM/SVF-gel (red), indicating no statistical differences in xCell scores between the two groups. The xCell scores predict relative enrichment for cell types, resembling the fractions of the cell types, but not the exact cellular proportions. The error bar denotes standard error for the sample mean. Mesenchymal stem cells detected by xCell in adipose tissue actually were ADSCs. mv Endothelial cells, microvascular Endothelial cells.
Supplemental material

Supplemental Material

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Data availability statement

The detailed information of our raw data link: The raw sequence data reported in this manuscript have been deposited in the Genome Sequence Archive (Genomics, Proteomics & Bioinformatics 2021) in National Genomics Data Center (Nucleic Acids Res 2022), China National Center for Bioinformation/Beijing Institute of Genomics, Chinese Academy of Sciences (GSA-Human: HRA007009) that are publicly accessible at https://ngdc.cncb.ac.cn/gsa-human.