Therapeatic evaluation and single cell analysis of adipose stromal vascular fraction isolation from a commercial cell separation system

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However, the cellular composition and therapeutic effect of SVF products prepared via different methods are unclear. Methods: SVF cells were obtained via three approaches: (1) generation of the SVF via mechanical emulsification (M-SVF), (2) generation of the SVF via laboratory enzymatic digestion (L-SVF), and (3) generation of the SVF via commercial cell separation systems (C-SVF). We evaluated their healing effects on mouse wounds. Additionally, we utilized single-nucleus RNA sequencing (snRNA-seq) technology to explore the cellular composition of the C-SVF. Results: The cell yield of C-SVF was comparable to that of L-SVF. During in vitro culture, C-SVF exhibited enhanced proliferation and a reduced proportion of apoptotic cells. In a mouse wound model, the application of C-SVF facilitated the closure of mouse wounds and improved collagen remodeling and angiogenesis in the wound area. Additional snRNA-seq analysis revealed that APOE+ adipose-derived stem cells and immune cells, especially M2 anti-inflammatory macrophages, are enriched in C-SVF, which together promote wound repair, and that APOE+ adipose-derived stem cells (ADSCs) and immune cells, especially M2 anti-inflammatory macrophages, are enriched in C-SVF, which jointly regulate and promote wound repair. Conclusion: A commercial extraction system is an effective method for isolating viable SVF cells enriched with APOE+ ADSCs and M2 macrophages. stromal vascular fraction adipose-derived stem cells enzyme digestion method separation equipment mechanical method single-nucleus RNA sequencing Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 1 Introduction Stem cell therapy has recently gained widespread acceptance in regenerative medicine, covering a range of treatments for conditions such as stubborn wounds, ischemic conditions, and tissue deficiencies. Adipose-derived stem cells (ADSCs) have increased in prominence as preferred stem cells because of their facile procurement, high storage capacity, and rapid proliferation kinetics[ 1 ]. The stromal vascular fraction (SVF), a recently emerged derivative of adipose tissue, has sparked widespread research endeavors. Its abundant bioactive substances, including notably ADSCs and matrix components, have positioned it as a viable solution for treating stubborn wounds[ 2 – 4 ]. At present, there is no broad consensus on the standard separation procedure for SVFs. Typically, separation methods can be classified into two main categories on the basis of whether collagenase is used to assist in the breakdown of the extracellular matrix (ECM) of adipocytes: enzymatic methods and nonenzymatic methods. Nonenzymatic (mechanical) methods rely mainly on physical operations such as emulsification, centrifugation, oscillation, and vortexing to disrupt the ECM and concentrate cellular components[ 5 , 6 ]. The enzymatic method results in a high yield of SVF cells but is more expensive, has a longer preparation time, and has a greater risk of contamination. In contrast, nonenzymatic methods are less labor intensive, time saving, and easier to use in clinical practice; however, it is still uncertain whether they have regenerative effects comparable to those of enzymatic methods[ 7 – 10 ]. To obtain SVFs more conveniently and quickly during surgery, a range of semi or fully automatic separation and extraction devices have been introduced to the market[ 11 ]. Among these devives, Celution 800 was proven to be more effective with rapid processing time, greater viable cell yield, a lower residual enzyme level and a reduced cost[ 12 ]. Celution 800 has been widely used in different indications and has achieved significant results[ 13 – 15 ]. In this study, we compared the regenerative effects of SVF cells obtained via one nonenzymatic and two enzymatic methods. We evaluated their regenerative effects in a mouse wound model. Additionally, we utilized single-nucleus RNA sequencing (snRNA-seq) to explore the cellular composition of the SVF generated by commercial cell separation systems. 2 Materials and methods 2.1 Adipose tissue acquisition and processing With the informed consent and approval of the Medical Research Ethics Committee of Nanfang Hospital, affiliated with Southern Medical University, adipose aspirates were obtained from six young healthy female human donors (demographic details of the participants are presented in Additional file 1). Following collection, the samples were immediately cooled on ice and subjected to further processing. Preparation of the SVF generated via laboratory enzymatic digestion (L-SVF): The adipose aspirate was subjected to digestion with a 0.1% collagenase I solution (Solarbio, Beijing) in a 37°C shaker for 30 minutes. The mixture was subsequently centrifuged at 1000 rpm for 5 minutes to isolate the cell pellet at the bottom. Following filtration through a 100 µm mesh sieve, the cells were resuspended in phosphate-buffered saline (PBS) (Servicebio, Hubei). To remove red blood cells, the samples were treated with red blood cell lysis buffer (GenStar, Beijing) at room temperature for 5 minutes. After another centrifugation at 1000 rpm for 5 minutes, the pellet was resuspended to yield the L-SVF suspension. Preparation of the SVF generated by mechanical emulsification (M-SVF): The adipose aspirate was subjected to centrifugation at 3000 rpm for 3 minutes. The supernatant and top oil layer were discarded, and the intermediate layer was transferred to a threaded syringe with a 1.4mm Luer connector. It was then injected and expelled 50 times, followed by centrifugation (3000 rpm, 3 minutes) to obtain M-SVF. Preparation of SVFs generated by a commercial cell separation system (C-SVF): Approximately 250 ml of adipose aspirate was added to the Celulation 800 system, after which the Celase enzyme reagent was added. Following standardized washing and centrifugation steps, C-SVF was obtained. 2.2 Cell morphology The freshly obtained L-SVF and C-SVF were cultured in Dulbecco's modified Eagle’s medium (DMEM) (Gibco, Waltham, MA) supplemented with 10% fetal bovine serum and 100 U/ml penicillin‒streptomycin. The morphology of the cells was subsequently examined via an inverted microscope. 2.3 Cell proliferation rate The manufacturer's manual for assessing cell viability was followed with the Human Cholecystokinin/Octapeptide (CCK8) ELISA Kit from Guangzhou Orida Biotechnology Co., Ltd. The optical density (OD) at 450 nm is indicative of the cell proliferation potential. 2.4 Collagenase residue detection The manufacturer's manual was followed to employ a Collagenase Type I Residue Detection ELISA Kit (Shanghai Ruifan Biological Technology Co., Ltd.) to identify collagenase residues. The OD reading at 450/630 nm was used to determine the concentration of the collagenase residue. 2.5 Flow cytometry The SVF cell suspension was prepared at a concentration of 1×10^6/ml, 100 µl of the suspension was removed, and the mixture was incubated with the following antibodies according to the manufacturer's protocol: anti-CD90-APC, anti-CD105-PerCP-Cy5.5, anti-CD31-FITC, anti-CD133-PE, anti-CD146-FITC, and anti-CD34-PE-Cy7, and anti-PDGFRα-PE, Annexin V, and PI (BD BIOSCIENCE, USA; 1:200). The samples were subsequently analyzed via a flow cytometer (BD FACS Cantoll flow cytometer, USA). 2.6 Animals All animal experiments were approved by the Experimental Animal Care and Use Committee of Nanfang Hospital and were conducted in strict accordance with the guidelines set by the National Health and Medical Research Council (China). Female nude mice (BALB/c-nu), aged 6–8 weeks and weighing 20–23 g, were purchased from the Experimental Animal Center of Southern Medical University (Guangzhou, China). The mice were bred through a regular breeding program at the Experimental Animal Center of Southern Medical University. The animals were maintained on a standard food diet with free access to food under a 12-h light‒dark cycle. 2.7 Establishment of a full-thickness skin defect wound model After the mice were anesthetized with an isoflurane anesthesia machine (Yuyan Corporation, China) at a flow rate of 1 L/min, a circular full-thickness wound (diameter of 6 mm) was created through the skin on the on both sides of the dorsum of each mouse. The mice were randomly divided into four groups, namely the L-SVF, M-SVF, C-SVF, and PBS groups, with six mice in each group (n = 6). The experimental groups were subcutaneously injected with 0.1 ml of the corresponding SVF cell suspension (2×10^5 cells/ml), whereas the control group received 0.1 ml of PBS. The wound was then wrapped with sterile Tegaderm dressings (3M Healthcare, St Paul, MN, USA), which were changed every other day until day 14. Digital photos were taken on days 0, 2, 4, 7, 10, and 14, and skin tissue around the wound was collected on days 7 and 14. The wound area was quantified via ImageJ. For the anesthetized mice from which samples have already been taken, trained and skilled personnel euthanized them via the method of cervical dislocation. Death was confirmed by absence of corneal reflex and cessation of heartbeat for 5 minutes. All procedures were approved by the Experimental Animal Care and Use Committee of Nanfang Hospital and complied with the ARRIVE Guidelines 2.0. 2.8 Histological staining The harvested tissue samples were fixed in 10% formalin for 36–48 hours, and paraffin-embedded tissue sections with a thickness of 4 micrometres were prepared. Following deparaffinization, the sections were stained with hematoxylin and eosin (H&E) and Masson's trichrome (BASMEDTSCI, Hubei) in accordance with the standard protocol and the manufacturer's instructions. For immunohistochemical staining, antigen retrieval was conducted using an EDTA solution (pH = 9.0), followed by washing with PBS and blocking with goat serum for 1 hour at room temperature to prevent nonspecific binding. The sections were subsequently incubated overnight at 4°C with a primary antibody against CD31 (EPR17259; 1:1000; Abcam, Cambridge, MA). The next day, the sections were incubated with a secondary antibody conjugated with HRP, counterstained with hematoxylin, and developed with diaminobenzidine. Collagen content and vessel density were quantified via ImageJ software. 2.9 snRNA-seq The improved nuclear separation method was utilized to isolate nuclei from frozen human white adipose tissue (WAT) and C-SVF. Sequencing was conducted by SequMed Biotech, Inc. The single-cell nuclear suspension was assessed with a Countess II instrument prior to loading onto the machine, with an anticipated capture of 10,000 nuclei. Single-cell 3' v2 chemistry was employed to produce single-cell barcoded droplets (GEMs), and upon capturing the nuclei, the GEM solution appeared as a uniform milky white liquid. The GEM solution was subsequently withdrawn and transferred to PCR tubes for reverse transcription and library construction for sequencing. The "gene expression library" was quantified via a Qubit instrument, and the fragment size of the "gene expression library" was analyzed via Qpcr. Subsequently, Illumina NovaSeq was utilized with a PE150 sequencing strategy for paired-end sequencing, with both reads being 150 bp in length. The raw image files obtained from high-throughput sequencing were converted into sequencing reads (sequenced reads) via base calling with CASAVA and stored in FASTQ format for further analysis. 2.9.1 snRNA-seq Data Analysis The default parameters of Cell Ranger single-cell software (10x Genomics) were used for data alignment, unique molecular identifier (UMI) counting, cell counting and clustering analysis. The quality of the sample-specific FASTQ files was assessed via Cell Ranger's counts. The expression level of each transcript is determined by the quantity of UMI assigned to it. The filtered gene expression matrix was then employed for downstream analysis. RStudio (v.4.4.1) was used to visualize clustering and gene expression with the Seurat software package (v.5.1.0). The uniform manifold approximation and projection (UMAP) method in Seurat software was used for dimensionality reduction. The differential gene expression among clusters was analyzed via the Seurat function FindMarkers and the Wilcoxon test. Violin plots, heatmaps and individual UMAP maps of the given genes were generated via the VlnPlot, DoHeatmap and FeaturePlot functions of the Seurat toolkit, respectively. 2.9.2 Cell type identification Using the Seurat R package, after the initial Cell Ranger metric check, cells with 20% mitochondrial genes and single-sample data with nCount_RNA < 1,000 were excluded. After quality control, 7,691 C-SVF and 5,657 adipose tissue cells remained; 24,982 of the integrated data were retained for bioinformatics. PCA of the top 2,000 var. gene-aligned samples. In adipose tissue, C-SVF, and the integrated data, total-cell clustering was conducted at resolutions of 0.5, 0.5, and 0.2, respectively, via the "FindClusters" function. Dimensionality reduction was achieved via the RunUMAP function, and visualization was performed via UMAP. For subpopulation cell clustering, different cell types were extracted separately and clustered on the basis of their respective top 10 principal components. For adipose stem cells, the resolution was 0.5. Lymphocytes and macrophages were clustered according to their top 5 and top 6 principal components, respectively, with resolutions of 0.2 and 0.5. The marker genes for each cluster were identified via the "FindAllMarkers" function with the Wilcoxon rank-sum test. Only genes with |avg_log2FC| > 0.25 and p_val < 0.05 were regarded as marker genes. Additional file 2 displays the marker genes for each cluster. 2.9.3 Differentially expressed gene (DEG) identification and gene ontology(GO) analysis The "FindMarkers" function in Seurat was used to identify DEGs among different cell types or between C-SVF and adipose tissue for each cell type. The log fold change (log2FC) and adjusted p value of each DEG were calculated via the nonparametric two-sided Wilcoxon rank-sum test. DEGs are defined as those with |avg_log2FC| > 0.5 and p_val_adj < 0.05 and are listed in Additional file 3. GO analysis of the DEGs was performed with clusterProfiler (v.4.14.4), and the results were visualized via the ggplot2 R package (v.3.5.1). Representative terms (p < 0.01) were selected from the top 20 GO terms or pathways. 2.10 Statistical analyses All the data are expressed as the means ± standard errors of the means. Statistical significance was determined via an unpaired t test for comparisons between two groups and two-way ANOVA for comparisons among three or more means, followed by Dunnett’s test for pairwise comparisons (Graph Pad Prism version 10). P values < 0.05 denoted statistical significance. 3 Results 3.1 C-SVF maintained the viability of ADSCs The primary cell types in the SVF cell suspension encompass a variety of cell populations, such as ADSCs, endothelial cells (ECs), endothelial progenitor cells (EPCs), and pericytes [ 16 ]. No significant difference was found in the proportion of cellular components between L-SVF and C-SVF, suggesting that device processing does not affect the composition of different cell populations. Among each group, ADSCs constituted the major cellular population in the SVF, with the proportions of ADSCs in the L-SVF and C-SVF being 11.93 ± 1.20% and 13.16 ± 0.42%, respectively (Fig. 1 A). No notable difference in the morphology of ADSCs extracted via the two methods was detected (Fig. 1 B). Furthermore, the data indicate that the labotort enzymatic method yields approximately 175,000 ± 51,068 nucleated cells per gram of adipose tissue in approximately 2.5 hours, whereas the Celution 800 method produces approximately 112,000 ± 35,452 nucleated cells in approximately 1.5 hours. There was no statistically significant difference in extraction efficiency between the two methods (L-SVF and C-SVF produced approximately 70,000 ± 16,679 and 78,024 ± 16,342 nucleated cells per gram of adipose tissue per hour, respectively, P > 0.05) (Fig. 1 C). Notably, the proliferative capacity of C-SVF was marginally greater than that of L-SVF (P < 0.05) (Fig. 1 D). The L-SVF group presented a greater incidence of apoptosis and cellular debris (P < 0.05) (Fig. 1 E, F). Moreover, increased levels of collagenase residue were detected in the L-SVF extraction process (P < 0.05) (Fig. 1 G). 3.2 C-SVFeffectively improved skin wound closure. To compare the regenerative capacity of SVF cells obtained via different methods, we used a full-thickness wound model in nude mice (Fig. 2 A). Faster wound healing was observed in both the C-SVF and L-SVF groups (Fig. 2 B). By the 7th day, the wound healing rate for C-SVF had reached 87.86 ± 7.54%, and that for L-SVF had reached 83.96 ± 11.80% (P > 0.05). Concurrently, the wound closure rates for the PBS group and M-SVF group were 60.01 ± 13.49% (P 0.05), respectively (Fig. 2 C). The morphological characteristics of the wounds in each group were observed via H&E and Masson's trichrome staining. H&E staining on day 7 in each treatment group revealed a significant increase in granulation tissue thickness in the groups treated with C-SVF and L-SVF (compared with the PBS group, the C-SVF and L-SVF groups presented increases of 1.71 ± 0.26-fold and 1.51 ± 0.37-fold, respectively, P 0.05), indicating more effective re-epithelialization and a well-structured epidermis compared with the other groups. No significant differences were observed between these two groups. In stark contrast, the wound tissue of the M-SVF group contained many mature adipocytes ectopically deposited between the epidermis and dermis (Fig. 2 D, E). Furthermore, Masson's trichrome staining demonstrated increased collagen deposition in the C-SVF-treated group. Compared with the PBS group (8.22 ± 1.40%), the C-SVF, L-SVF and M-SVF groups presented increased collagen deposition (23.38 ± 1.71%, 13.14 ± 1.96% and 15.55 ± 1.32%, respectively, P < 0.001)(Fig. 2 F,G). Next, we used CD31 for immunohistochemical staining to assess angiogenesis in each group. The results revealed that the C-SVF group had the highest vascular density (4.17 ± 0.68%), which surpassed those of the M-SVF group and L-SVF group (3.65 ± 0.69% and 3.76 ± 0.74%, respectively, P > 0.05) (Fig. 2 H,I). 3.3 Enrichment of functional cells within the C-SVF To elucidate the cell subpopulations involved in C-SVF and their potential mechanisms, we conducted single-cell nuclear RNA sequencing analysis on subcutaneous adipose tissue and extracted C-SVF from a healthy 23-year-old female. The adipose tissue samples and C-SVF samples were each classified into 13 and 12 clusters, respectively (Fig. 3 A, B). The results indicate that the identified cell clusters can be categorized into four major groups: adipocytes, ADSCs, vascular cells, and immune cells, which aligns with the findings of Lucas et al. [ 18 ]. The large size and relatively fragile nature of mature adipocytes are considered to be the cause of adverse consequences such as oil swelling and inflammation after fat transplantation [ 19 ]. Compared with adipose tissue samples, C-SVF samples contain significantly fewer adipocytes. These findings suggest that C-SVF extraction can effectively disrupt and eliminate mature adipocytes, thereby enriching stem cells. Moreover, immune cells and vascular cells were more abundant in the C-SVF. 3.3.1 Characterization of ADSCs in C-SVF To enhance the comparability of these two datasets, we integrated them and conducted quality filtering prior to analysis. Unsupervised clustering of the gene expression profiles revealed 15 distinct cell types (Fig. 4 A). The cell clusters were annotated on the basis of the DEGs and established marker genes (Fig. 4 B and Additional file 2). By statistically comparing the proportions of the nuclei of major cell types, we found that C-SVF contains two main subpopulations of ADSCs, with a greater percentage of Type 2 ADSCs (Fig. 4 C). GO analysis revealed that pathways related to collagen and growth factor synthesis were upregulated in type 2 adipose-derived stem cells compared with type 1 adipose-derived stem cells (Fig. 4 D). These findings indicate that the remarkable therapeutic effects of C-SVF on ECM deposition may be associated with the abundant content of type 2 ADSCs. To classify different subpopulations of ADSCs more precisely, we reclustered the cells at a higher resolution, dividing the ADSCs into 6 subtypes (Fig. 5 A, Additional file 2), all of which significantly expressed the identified ADSC markers Pdgfrα, CD34, Itgb1 (CD29), and Thy1 (Cd90) [ 20 – 23 ] (Fig. 5 B). Among them, clusters 0 and 4 expressed marker genes for adipogenesis-regulating cells (Aregs) as defined by Schwalie et al.[ 24 ]. The tendency of Aregs to form adipocytes is significantly decreased and can negatively regulate the adipogenic capacity of other ADSCs through paracrine signaling mechanisms, such as Rtp3, Spink2, Fgf12, and Vit [ 24 , 25 ]. Cluster 1 exhibited relatively high expression of KDM4B, a gene known to be linked with the transcriptional activation of various metabolic genes, including PGC-1. Mice lacking KDM4B display compromised adrenergic responses and albinism in their brown adipose tissue[ 26 ]. Consequently, Cluster 1 may indicate potential beige adipocyte precursors within white adipose tissue. In Cluster 2, the APOE gene is significantly overexpressed, and its functions encompass multidimensional regulatory mechanisms. On the one hand, it facilitates adipocyte differentiation by activating the PPARγ pathway[ 27 ]. On the other hand, it neutralizes proinflammatory factors (such as TNF-α and IL-6) to inhibit the activation of the NF-κB pathway while also promoting the polarization of M2 macrophages, thus forming an immunosuppressive microenvironment[ 28 , 29 ]. These functions suggest that Cluster 2 genes may be involved in maintaining metabolic homeostasis and tissue repair by regulating lipid metabolism and the immune microenvironment. Cluster 3 cells display high expression of Dpp4 and CD55. Research indicates that the expression levels of general stem cell markers (such as CD34 and CD73), genes linked to cancer stem cells (CD99 and ITGB3), and an embryonic stem cell marker (GGT1) are elevated within this subset [ 30 , 31 ]. These findings suggest that this cell subset may have enhanced self-renewal and proliferation capabilities. Further studies have demonstrated that this subset has superior therapeutic effects in promoting wound healing and regeneration [ 32 ]. Additionally, Cluster 3 shows a certain level of CD24 expression, and CD24 + cells have been previously confirmed to be adipogenic progenitor cells capable of fat formation in vivo [ 23 ]. Therefore, this subset may also play a significant role in the process of adipocyte differentiation. In cluster 5, transcriptomic analysis revealed significantly elevated expression levels of RUNX3 and CCL5. Functional validation studies have demonstrated that ADSCs exert proangiogenic effects on human umbilical vein endothelial cells (HUVECs) through RUNX3-mediated signaling pathways, promoting endothelial cell proliferation, migration, and tube formation[ 33 ]. Subsequent in vivo investigations further identified CCL5 as a critical effector molecule in ADSC-driven angiogenesis during cutaneous wound healing[ 34 ]. Additionallly, cluster 5 cells expressed high levels of inflammatory markers (such as Ccl5, IL7R, Ptptc , and IL32 ), indicating that cluster 5 cells might orchestrate wound healing through bidirectional crosstalk with infiltrating immune cells [ 35 ]. Collectively, these results suggest that cluster 5 may have potential application value in modulating inflammation resolution and angiogenesis (Fig. 5 C, D). On the basis of the above analysis, we determined that specific ADSC subsets dynamically interact with macrophages during wound repair. Notably, T lymphocytes were significantly enriched in the C-SVF fraction, constituting the dominant cell population (Fig. 4 C). To characterize these interactions in detail, we performed a comprehensive analysis of immune cell subsets within the C-SVF, categorizing them into two major lineages: (i) lymphoid cells dominated by T cells and (ii) myeloid cells comprising mainly M2-like macrophages[ 36 ]. Sngle-cell profiling of these populations enabled the construction of a high-resolution atlas defining the transcriptional diversity and functional heterogeneity of distinct immune cell subsets. In the major lymphocyte group, four distinct clusters (clusters 0–3 in descending abundance, Fig. 6A, Additional file 2) were identified. Cluster 0 presented relatively high expression of CD8A. Research suggests that the CD8α protein encoded by CD8A may participate in ADSC–immune cell crosstalk and regulate local immune responses[ 37 ]. Cluster 1 highly expresses CD28 and PCAT-1 and contains genes related to regulatory T-cell (Treg) subtypes [ 38 ]. In vitro, ADSCs can promote paracrine-mediated anti-inflammatory events by decreasing CD28-T cells and increasing FoxP3 + Tregs [ 39 ]. Elevated PCAT-1 levels are associated with reduced immune cell infiltration [ 40 ]. Cluster 2 had relatively high CTBP2 expression. Notably, LW et al. reported that miR-342-3p from human ADSCs can inhibit CtBP2 to activate adipogenic factor and marker expression [ 41 ]. Cluster 3 expressed TRM and B-cell marker genes[ 38 ] and highly expressed EGFR. A previous study[ 42 ] indicated that human ADSCs can activate skin stem cells via the EGFR/MEK/ERK pathway to promote wound healing (Fig. 6B). The myeloid group was classified into six clusters (clusters 0–5, Fig. 6C, Additional file 2). Clusters 0 and 1 highly expressed LYVE1, which is potentially involved in tissue support and angiogenesis[ 43 , 44 ]. Notably, Cluster 0 exhibited marked upregulation of CD163L1, an endocytic receptor whose expression is induced during monocyte-to-macrophage differentiation under M-CSF stimulation but suppressed by proinflammatory mediators such as TNF-α[ 45 ]. Cluster 2 expressed the marker genes of metabolically regulated macrophages[ 18 ], which are important for regulating inflammatory mediator and lipid metabolism balance[ 46 , 47 ]. Additionally, cluster 2 and 3 relatively highly expressed genes related to cell‒matrix interactions and ECM remodeling, such as C3 and S100A10 [ 48 , 49 ]. Cluster 5 also expressed genes related to lipid-associated macrophages (LAMs) (such as CD9, ABP4, CD68 , and N1 ) [ 50 – 52 ]. LAMs express many genes related to immunosuppression (e.g., Lgals1 and Lgals3), suggesting that they might be involved in regulating inflammatory responses related to cell death and lipid accumulation[ 53 ]. Burl et al.[ 54 , 55 ] identified a macrophage cluster (cluster 5 highly expressed relevant genes) and suggested that these cells might provide growth factors for adipose stem cells (Fig. 6D). On the basis of the above analysis, we posit that within the C-SVF fraction, ADSC subsets and diverse immune cell populations likely form a bidirectional regulatory network via paracrine signaling. ADSCs suppress excessive inflammation and remodel the immune microenvironment through the secretion of bioactive substances, whereas immune cells reciprocally promote ADSC proliferation, differentiation, and angiogenic gene expression via cytokine release. This dynamic interplay results in a multidimensional regulatory network for wound healing. 4 Discussions SVF cells are abundant in ADSCs and other therapeutically potent cell types such as vascular endothelial cells and tissue macrophages, which are crucial for wound healing and tissue regeneration. Currently, the enzymatic digestion method is predominant in SVF extraction. It is well-established, yielding relatively high cell numbers and survival rates, and is advancing toward closed, automated processes[ 56 ]. Various semiautomatic and fully automatic SVF extraction devices have been successively introduced to the market in recent years. Preclinical and clinical studies have indicated that SVF cells obtained through the decellularization system can facilitate angiogenesis[ 15 , 57 ], reduce inflammation[ 14 ], and improve other parameters related to the healing mechanism[ 58 , 59 ]. Our studies revealed that the production efficiency of C-SVF is comparable to that of the manual enzymatic digestion method, the prevalent technique for clinically isolating SVF cells. However, the Celution system offers several benefits, including shorter operation times, a simpler procedure, a reduced risk of external contamination, less reliance on operator skill, and improved reproducibility. Moreover, commercial extraction kits tend to have lower residual collagenase levels. Currently, various countries have different views on the use of enzymes, but there is a common consensus to limit the addition of foreign substances. Animal studies indicate that C-SVF is as effective as L-SVF in accelerating wound healing and slightly outperforms mechanically extracted M-SVF. These findings imply that the C-SVF is a novel and superior source of stem cells. Although M-SVF might not excel in facilitating tissue regeneration, its role in regenerative therapy for volumetric defects is nonsubstitutable. Hence, it is conceivable that C-SVF could be merged with conventional M-SVF in the future, increasing the functional cell content within M-SVF while sustaining its effective volumetric capacity, thereby resulting in enhanced therapeutic results. Moreover, for the first time, we performed snRNA-seq on SVFs extracted from commercial machines. By integrating and comparing these results with sequencing data from intact adipose tissue, we discovered that adipose-derived stem cells constitute one of the primary cellular populations in C-SVF, making them probable candidates for potential functional roles. Through a more in-depth analysis of cell subtypes, we further classified ADSCs into six functionally heterogeneous subsets, each of which exhibited unique molecular characteristics and potential for clinical application. For example, high expression of KDM4B in Cluster 1 was significantly associated with the activation of metabolic genes mediated by PGC-1α. This epigenetic regulatory mechanism can drive the browning process of white adipose tissue by promoting mitochondrial biogenesis. Our previous research revealed that the appearance of beige adipocytes in wound tissue contributes to wound repair[ 60 ]. The secretion of brown adipokines (e.g., FGF21) further accelerates metabolic reprogramming, collagen deposition, and angiogenesis in the wound microenvironment [ 61 ]. Cluster 2 conversely regulated both the immune microenvironment and lipid metabolism through a dual APOE-dependent axis. Functional validation confirmed that APOE-overexpressing ADSCs significantly improved healing in diabetic ulcers, positioning APOE as a metabolic‒immunomodulatory hub[ 62 , 63 ]. Collectively, these data highlight that ADSC subpopulations promote wound repair through multidimensional regulatory networks integrating metabolic reprogramming, immune modulation, and angiogenic differentiation. This study reveals the pivotal role of the dynamic interplay between ADSC subsets and the immune microenvironment in wound repair. Single-cell analysis revealed that ADSCs establish a multidimensional regulatory framework with immune cells (T cells and macrophages) via paracrine signaling. T cells in wound tissues display high heterogeneity (Clusters 0–3). ADSCs may promote Treg (Cluster 1) proliferation and suppress CD8 + T-cell activity, suggesting a potential strategy to counter the T-cell immune imbalance in diabetic wounds induced by the high-glucose milieu[ 64 ]. Macrophage subset analysis indicated that C-SVF is abundant in M2 anti-inflammatory macrophages. These cells curb excessive inflammation by secreting anti-inflammatory cytokines (e.g., IL-10 and TGF-β) [ 65 ], promote angiogenesis by releasing vascular endothelial growth factor, and expedite tissue remodeling through collagen matrix synthesis[ 66 , 67 ]. Cluster 5 combines with ADSCs for proliferation by highly expressing immunosuppressive factors such as Lgals3, creating an immunosuppressive-stem cell activation symbiotic system. These findings offer a novel perspective on the immunometabolic regulation of wound repair. Future research could integrate spatial transcriptomics and single-cell epigenomics to dissect the dynamic intersubset network and validate its translational potential as a therapeutic target in clinical cohorts. Importantly, our study has certain limitations. On the one hand, in the meta-analysis by Massier et al. [ 18 ], the correlation between snRNA-seq data and the transcriptional traits of isolated adipocytes was tenuous. For example, only feeble adipocyte subtype marker genes (e.g., Lep, Saa1, and Rbp4) [ 68 ] were detected in our snRNA-seq data. Thus, ascertaining adipocyte subtypes mandates combined analysis via diverse technical platforms (such as spatial transcriptomics). On the other hand, our sequencing results are based on a single sample, which significantly limits the universality of the observed outcomes. Additionally, we anticipate future studies that can further investigate the long-term effects of these technologies and cell populations. By delving deeper into its mechanism of action, targeted improvements to the corresponding cell extraction process can help enhance its therapeutic effects and broaden its applications in regenerative medicine. 5 Conclusions In our study, the C-SVF extraction technique was proven to have extraction efficiency comparable to that of the traditional L-SVF. Furthermore, it can effectively promote wound regeneration, and its efficacy is superior to that of the SVF components obtained through other methods. Abbreviations ADSCs: adipose-derived stem cells SVF: stromal vascular fraction ECM: extracellular matrix ADRCs: adipose-derived regenerative cells snRNA-seq: single-nucleus RNA sequencing L-SVF: SVF prepared by laboratory enzymatic digestion rpm: revolutions per minute PBS: phosphate buffered saline M-SVF: SVF generated by mechanical emulsification C-SVF: SVF generated by commercial cell separation systems DMEM: dulbecco's modified eagle medium OD: optical density H&E: hematoxylin and eosin EDTA: ethylenediaminetetraacetic acid HRP: horseradish peroxidase WAT: white adipose tissue GEMs: gel bead in emulsion microdroplets UMI: unique molecular identifiers UMAP: uniform manifold approximation and projection PCA: principal component analysis DEG: differentially expressed gene GO: gene ontology ECs: endothelial cells EPCs: endothelial precursor cells Aregs: adipogenesis-regulating cells HUVECs: human umbilical vein endothelial cells Tregs: regulatory T cells LAM: lipid associated macrophage CE: onformité européenne Declarations Ethics approval and consent to participate All experimental protocols were approved by the Medical Ethics Committee of Nanfang Hospital, Southern Medical University (approval No. NFEC-2024-296; June 19, 2024) under the ethics review protocol titled "Comparative Study on the Composition and Function of Adipose-Derived Regenerative Cells (ADRCs) Extracted by Celution® 800 and Stromal Vascular Fraction (SVF) Cells Obtained Through Different Methodological Approaches". This approval is applicable to the use of human specimens and animal research. Consent for publication Not applicable. Competing interests The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article. Funding This research was funded by Cytori Therapeutics LLC, under the project named "Comparative Study on the Composition and Function of Adipose-Derived Regenerative Cells (ADRCs) Extracted by Celution 800 and Stromal Vascular Fraction (SVF) Cells Obtained by Different Methods " with the grant number K61010028. The funders had no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. Authors’ Contributions JR and SX conceived and designed the experiment. LF supervised this project. SX performed the experiments and conducted the bioinformatics analyses. SX and ZQ composed the manuscript. All authors read and approved the final manuscript. Acknowledgments The authors would like to thank the many surgeons and patients who have donated adipose tissue for this research. We also thank Cytori Therapeutics for providing the Celution system and accessories for this study. The authors declare that they have not use AI-generated work in this manuscript" in this section. Availability of data and materials The single-nucleus RNA sequencing datasets generated and analyzed during this study contain unpublished findings that are currently being utilized in ongoing investigations. To protect the integrity of related follow-up studies, raw sequencing data and processed matrices will be made available upon reasonable request through direct communication with the corresponding author (email: [email protected] ). Full public deposition in recognized repositories (e.g., GEO, ENA, or SRA) will occur upon completion of the research program, with accession codes provided in future publications. 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Kim SY, Nair MG. Macrophages in wound healing: activation and plasticity. Immunol Cell Biol. 2019;97(3):258–67. Bäckdahl J, et al. Spatial mapping reveals human adipocyte subpopulations with distinct sensitivities to insulin. Cell Metab. 2021;33(9):1869–e18826. Supplementary Files TheARRIVEEssential10.docx Cite Share Download PDF Status: Published Journal Publication published 07 Nov, 2025 Read the published version in Stem Cell Research & Therapy → Version 1 posted Reviewers agreed at journal 14 May, 2025 Reviewers invited by journal 14 May, 2025 Editor assigned by journal 29 Apr, 2025 First submitted to journal 28 Apr, 2025 Editorial decision: Major Revision 22 Apr, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6399413","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":456450075,"identity":"4a2de079-e6d7-4e35-aa5b-129841ef1002","order_by":0,"name":"Shunxin Han","email":"","orcid":"","institution":"Southern Medical University","correspondingAuthor":false,"prefix":"","firstName":"Shunxin","middleName":"","lastName":"Han","suffix":""},{"id":456450076,"identity":"a094aca1-92d2-4259-986e-a2bb08439079","order_by":1,"name":"Qian Zhang","email":"","orcid":"","institution":"Southern Medical University","correspondingAuthor":false,"prefix":"","firstName":"Qian","middleName":"","lastName":"Zhang","suffix":""},{"id":456450077,"identity":"fdc98124-4ce8-493b-b235-9d337533f4b0","order_by":2,"name":"Feng Lu","email":"","orcid":"","institution":"Southern Medical University","correspondingAuthor":false,"prefix":"","firstName":"Feng","middleName":"","lastName":"Lu","suffix":""},{"id":456450078,"identity":"c320aae1-1e02-4320-ae3c-b0d7532e7d08","order_by":3,"name":"Junrong cai","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA7ElEQVRIiWNgGAWjYDCCAwwJCPYHIMHHwMBMvJaDMxgYJNiI0IIAzDzEaOG7feCZdOEemzx598MPD9tUHK5jY28+bMBQYxONS4vkuYQ06RnP0ooNz6QZHM45c1iCjedYcgLDsbTcBhxaDM4wpEnzHDicuHEGg8Hh3DagFokc4wOMDYeJ0cL+4bAlSVrmS/AYHGaEaknAp0XyDEOyNc+BtMQNPDkFB3vOpEu2Af1ikIDHL3xneBJv8xywSZzffnzzhx8V1vz8wBCT+FBjg1MLAwNPAsSFB5AFE3AqBwF2iFp53IaOglEwCkbBSAcA3jBa3AhqEEkAAAAASUVORK5CYII=","orcid":"https://orcid.org/0000-0002-5314-0264","institution":"Southern Medical University Nanfang Hospital","correspondingAuthor":true,"prefix":"","firstName":"Junrong","middleName":"","lastName":"cai","suffix":""}],"badges":[],"createdAt":"2025-04-08 05:24:22","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6399413/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6399413/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s13287-025-04732-5","type":"published","date":"2025-11-07T15:57:36+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":82876165,"identity":"58a818c6-72e2-48c8-807f-90ac0b1ebed5","added_by":"auto","created_at":"2025-05-16 09:43:32","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":483210,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCytological comparison between the L-SVF and C-SVF.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA)Flow cytometric analysis of the principal constituents of freshly isolated cells in the L-SVF and C-SVF groups (n = 3).\u003c/p\u003e\n\u003cp\u003eB)Morphological characteristics of P0 ADSCs generated from L-SVFs and C-SVFs. Scale bar = 100 μm.\u003c/p\u003e\n\u003cp\u003eC)Viable nucleated cell yield per milliliter of processed tissue.\u003c/p\u003e\n\u003cp\u003eD)Comparative analysis of cell proliferation rates between the L-SVF and C-SVF groups (n = 6).\u003c/p\u003e\n\u003cp\u003eE)Comparative evaluation of the cell debris rates between the L-SVF and C-SVF groups (n = 6).\u003c/p\u003e\n\u003cp\u003eF)Comparative assessment of cell apoptosis rates between the L-SVF and C-SVF groups (n = 6).\u003c/p\u003e\n\u003cp\u003eG)Residual levels of human type I collagenase in the L-SVF and C-SVF groups (n = 6).\u003c/p\u003e\n\u003cp\u003e(ns p\u0026gt;0.05, *p\u0026lt;0.05, **p\u0026lt;0.01, ***p\u0026lt;0.001)\u003c/p\u003e","description":"","filename":"image1.png","url":"https://assets-eu.researchsquare.com/files/rs-6399413/v1/63cb638af23ff74797720b3f.png"},{"id":82877763,"identity":"007c9e49-d5d6-4e5f-9333-45e1254136d2","added_by":"auto","created_at":"2025-05-16 10:07:32","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1427159,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eEffects of different SVFs on wound healing in nude mice.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA) Schematic overview of the experimental flowchart for animal studies involving SVFs procured via diverse methods.\u003c/p\u003e\n\u003cp\u003eB) Representative images of full skin wounds in different treatment groups. Scale bar = 3 mm.\u003c/p\u003e\n\u003cp\u003eC) Quantitative analysis of the wound healing rate(n=6).\u003c/p\u003e\n\u003cp\u003eD) Representative images of H\u0026amp;E-stained wound tissue sections on day 7 following surgery from the PBS, C-SVF, L-SVF and M-SVF groups; scale bar = 250 μm\u003c/p\u003e\n\u003cp\u003eE) Quantification of granulation tissue thickness in the wounds on day 7 following surgery (n=6).\u003c/p\u003e\n\u003cp\u003eF) Masson’s trichrome staining of the wound tissue sections on day 7 following surgery from the PBS, C-SVF, L-SVF and M-SVF groups; scale bar = 100 μm.\u003c/p\u003e\n\u003cp\u003eG) Quantification of collagen volume fractions in the wounds on day 7 following surgery (n=6).\u003c/p\u003e\n\u003cp\u003eH) CD31 immunostaining results of the wound tissue sections on day 7 following surgery from the PBS, C-SVF, L-SVF and M-SVF groups; scale bar = 100 μm.\u003c/p\u003e\n\u003cp\u003eI) The percentage of CD31-positive cells in the wounds on day 7 following surgery was quantified(n=6).\u003c/p\u003e\n\u003cp\u003e(* represents statistical significance compared with C-SVF; # represents statistical significance compared with PBS. ∗ P \u0026lt; 0.05, ∗∗ P \u0026lt; 0.01, ∗∗∗P \u0026lt; 0.001).\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-6399413/v1/de761c0c9b648a37aabf71a2.png"},{"id":82876167,"identity":"d6f9fcc6-e89e-4d69-b6a3-501110d00b3f","added_by":"auto","created_at":"2025-05-16 09:43:32","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":374416,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eUnsupervised clustering in C-SVF and adipose tissue.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA) For 7,691 cells sampled from whole adipose tissue, unsupervised clustering was carried out, with 11 disparate cell clusters shown on the UMAP plot.\u003c/p\u003e\n\u003cp\u003eB) For 5,657 cells sampled from whole adipose tissue, unsupervised clustering was carried out, with 12 disparate cell clusters shown on the UMAP plot.\u003c/p\u003e\n\u003cp\u003eC) A schematic diagram illustrating the relative proportions of diverse cell types in both adipose tissue and C-SVF.\u003c/p\u003e","description":"","filename":"image3.png","url":"https://assets-eu.researchsquare.com/files/rs-6399413/v1/dcd2729a0da84ca1e62c58b3.png"},{"id":82876166,"identity":"f9eb37cd-04c3-4a37-a37e-3a02a11d0e32","added_by":"auto","created_at":"2025-05-16 09:43:32","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":662699,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCell clustering and gene profiling in C-SVF and adipose tissue.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA) The sample of 24,982 cells underwent unsupervised clustering, and 15 heterogeneous cell clusters were depicted on the UMAP plot.\u003c/p\u003e\n\u003cp\u003eB) Dot plot presenting the recognized cell markers and the top 5 differentially expressed genes for each cell population under study.\u003c/p\u003e\n\u003cp\u003eC) A stacked bar chart delineating the percentages of assorted cell subtypes within subcutaneous white adipose tissue.\u003c/p\u003e\n\u003cp\u003eD) Lollipop plot showing the GO enrichment analysis of upregulated genes in ADSC_2 versus ADSC_1 within the C-SVF sample.\u003c/p\u003e","description":"","filename":"image4.png","url":"https://assets-eu.researchsquare.com/files/rs-6399413/v1/568a0a92858a360a8bef08cd.png"},{"id":82877296,"identity":"be2b837d-dc59-410e-a699-101ba7601821","added_by":"auto","created_at":"2025-05-16 09:59:32","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":1285239,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCell clustering and gene pattern visualization in C-SVF-derived ADSCs.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA) Unsupervised clustering was conducted on 2,255 adipose-derived stem cells procured from sample C-SVF. A three-dimensional UMAP map was then generated, revealing six distinct cell clusters.\u003c/p\u003e\n\u003cp\u003eB) Investigation of the gene expression patterns of stem cell-specific marker genes derived from adipose tissue within the ADSCs of C-SVF.\u003c/p\u003e\n\u003cp\u003eC) Utilizing individual gene UMAP and violin plots to visualize both the expression levels and distributions of representative marker genes. Notably, the y-axis represents the normalized read count, presented on a logarithmic scale.\u003c/p\u003e\n\u003cp\u003eD) Violin plots were generated to depict the relative log2 expression levels of selected genes across the six groups.\u003c/p\u003e","description":"","filename":"image5.png","url":"https://assets-eu.researchsquare.com/files/rs-6399413/v1/51016c1643311f61075e75e3.png"},{"id":82876172,"identity":"6a2cfdd3-33ff-4b35-a4fe-cb3f0db522ff","added_by":"auto","created_at":"2025-05-16 09:43:32","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":501219,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eClustering and marker analysis of immune cells in the C-SVF.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA) Unsupervised clustering analysis was performed on 1,575 lymphocytes sampled from C-SVF, and a three-dimensional UMAP map was constructed, which revealed four discrete cell clusters.\u003c/p\u003e\n\u003cp\u003eB) A dot plot was generated to display selected cell markers corresponding to each lymphocyte subpopulation.\u003c/p\u003e\n\u003cp\u003eC) Similarly, unsupervised clustering was carried out on 1,191 macrophages obtained from sample C-SVF, yielding a three-dimensional UMAP map that revealed six distinct cell clusters.\u003c/p\u003e\n\u003cp\u003eD) A dot plot was subsequently devised to show selected cell markers specific to each macrophage subpopulation.\u003c/p\u003e","description":"","filename":"image6.png","url":"https://assets-eu.researchsquare.com/files/rs-6399413/v1/c9a743626f285b421d043639.png"},{"id":95564311,"identity":"f700ebb8-0b42-4252-bdd3-e155c46fc1bd","added_by":"auto","created_at":"2025-11-10 16:09:48","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":5339110,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6399413/v1/1da327b7-caec-4999-9858-042f2b5499df.pdf"},{"id":82876175,"identity":"c038ff4b-c9ba-4592-b184-f374a03d45fc","added_by":"auto","created_at":"2025-05-16 09:43:32","extension":"docx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":1450934,"visible":true,"origin":"","legend":"","description":"","filename":"TheARRIVEEssential10.docx","url":"https://assets-eu.researchsquare.com/files/rs-6399413/v1/1fc4b8691155de2437124814.docx"}],"financialInterests":"","formattedTitle":"Therapeatic evaluation and single cell analysis of adipose stromal vascular fraction isolation from a commercial cell separation system","fulltext":[{"header":"1 Introduction","content":"\u003cp\u003eStem cell therapy has recently gained widespread acceptance in regenerative medicine, covering a range of treatments for conditions such as stubborn wounds, ischemic conditions, and tissue deficiencies. Adipose-derived stem cells (ADSCs) have increased in prominence as preferred stem cells because of their facile procurement, high storage capacity, and rapid proliferation kinetics[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. The stromal vascular fraction (SVF), a recently emerged derivative of adipose tissue, has sparked widespread research endeavors. Its abundant bioactive substances, including notably ADSCs and matrix components, have positioned it as a viable solution for treating stubborn wounds[\u003cspan additionalcitationids=\"CR3\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAt present, there is no broad consensus on the standard separation procedure for SVFs. Typically, separation methods can be classified into two main categories on the basis of whether collagenase is used to assist in the breakdown of the extracellular matrix (ECM) of adipocytes: enzymatic methods and nonenzymatic methods. Nonenzymatic (mechanical) methods rely mainly on physical operations such as emulsification, centrifugation, oscillation, and vortexing to disrupt the ECM and concentrate cellular components[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. The enzymatic method results in a high yield of SVF cells but is more expensive, has a longer preparation time, and has a greater risk of contamination. In contrast, nonenzymatic methods are less labor intensive, time saving, and easier to use in clinical practice; however, it is still uncertain whether they have regenerative effects comparable to those of enzymatic methods[\u003cspan additionalcitationids=\"CR8 CR9\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eTo obtain SVFs more conveniently and quickly during surgery, a range of semi or fully automatic separation and extraction devices have been introduced to the market[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Among these devives, Celution 800 was proven to be more effective with rapid processing time, greater viable cell yield, a lower residual enzyme level and a reduced cost[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Celution 800 has been widely used in different indications and has achieved significant results[\u003cspan additionalcitationids=\"CR14\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn this study, we compared the regenerative effects of SVF cells obtained via one nonenzymatic and two enzymatic methods. We evaluated their regenerative effects in a mouse wound model. Additionally, we utilized single-nucleus RNA sequencing (snRNA-seq) to explore the cellular composition of the SVF generated by commercial cell separation systems.\u003c/p\u003e"},{"header":"2 Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Adipose tissue acquisition and processing\u003c/h2\u003e \u003cp\u003eWith the informed consent and approval of the Medical Research Ethics Committee of Nanfang Hospital, affiliated with Southern Medical University, adipose aspirates were obtained from six young healthy female human donors (demographic details of the participants are presented in Additional file 1). Following collection, the samples were immediately cooled on ice and subjected to further processing.\u003c/p\u003e \u003cp\u003ePreparation of the SVF generated via laboratory enzymatic digestion (L-SVF): The adipose aspirate was subjected to digestion with a 0.1% collagenase I solution (Solarbio, Beijing) in a 37\u0026deg;C shaker for 30 minutes. The mixture was subsequently centrifuged at 1000 rpm for 5 minutes to isolate the cell pellet at the bottom. Following filtration through a 100 \u0026micro;m mesh sieve, the cells were resuspended in phosphate-buffered saline (PBS) (Servicebio, Hubei). To remove red blood cells, the samples were treated with red blood cell lysis buffer (GenStar, Beijing) at room temperature for 5 minutes. After another centrifugation at 1000 rpm for 5 minutes, the pellet was resuspended to yield the L-SVF suspension.\u003c/p\u003e \u003cp\u003ePreparation of the SVF generated by mechanical emulsification (M-SVF): The adipose aspirate was subjected to centrifugation at 3000 rpm for 3 minutes. The supernatant and top oil layer were discarded, and the intermediate layer was transferred to a threaded syringe with a 1.4mm Luer connector. It was then injected and expelled 50 times, followed by centrifugation (3000 rpm, 3 minutes) to obtain M-SVF.\u003c/p\u003e \u003cp\u003ePreparation of SVFs generated by a commercial cell separation system (C-SVF): Approximately 250 ml of adipose aspirate was added to the Celulation 800 system, after which the Celase enzyme reagent was added. Following standardized washing and centrifugation steps, C-SVF was obtained.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Cell morphology\u003c/h2\u003e \u003cp\u003eThe freshly obtained L-SVF and C-SVF were cultured in Dulbecco's modified Eagle\u0026rsquo;s medium (DMEM) (Gibco, Waltham, MA) supplemented with 10% fetal bovine serum and 100 U/ml penicillin‒streptomycin. The morphology of the cells was subsequently examined via an inverted microscope.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Cell proliferation rate\u003c/h2\u003e \u003cp\u003eThe manufacturer's manual for assessing cell viability was followed with the Human Cholecystokinin/Octapeptide (CCK8) ELISA Kit from Guangzhou Orida Biotechnology Co., Ltd. The optical density (OD) at 450 nm is indicative of the cell proliferation potential.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Collagenase residue detection\u003c/h2\u003e \u003cp\u003eThe manufacturer's manual was followed to employ a Collagenase Type I Residue Detection ELISA Kit (Shanghai Ruifan Biological Technology Co., Ltd.) to identify collagenase residues. The OD reading at 450/630 nm was used to determine the concentration of the collagenase residue.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5 Flow cytometry\u003c/h2\u003e \u003cp\u003eThe SVF cell suspension was prepared at a concentration of 1\u0026times;10^6/ml, 100 \u0026micro;l of the suspension was removed, and the mixture was incubated with the following antibodies according to the manufacturer's protocol: anti-CD90-APC, anti-CD105-PerCP-Cy5.5, anti-CD31-FITC, anti-CD133-PE, anti-CD146-FITC, and anti-CD34-PE-Cy7, and anti-PDGFRα-PE, Annexin V, and PI (BD BIOSCIENCE, USA; 1:200). The samples were subsequently analyzed via a flow cytometer (BD FACS Cantoll flow cytometer, USA).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.6 Animals\u003c/h2\u003e \u003cp\u003e All animal experiments were approved by the Experimental Animal Care and Use Committee of Nanfang Hospital and were conducted in strict accordance with the guidelines set by the National Health and Medical Research Council (China). Female nude mice (BALB/c-nu), aged 6\u0026ndash;8 weeks and weighing 20\u0026ndash;23 g, were purchased from the Experimental Animal Center of Southern Medical University (Guangzhou, China). The mice were bred through a regular breeding program at the Experimental Animal Center of Southern Medical University. The animals were maintained on a standard food diet with free access to food under a 12-h light‒dark cycle.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e2.7 Establishment of a full-thickness skin defect wound model\u003c/h2\u003e \u003cp\u003eAfter the mice were anesthetized with an isoflurane anesthesia machine (Yuyan Corporation, China) at a flow rate of 1 L/min, a circular full-thickness wound (diameter of 6 mm) was created through the skin on the on both sides of the dorsum of each mouse. The mice were randomly divided into four groups, namely the L-SVF, M-SVF, C-SVF, and PBS groups, with six mice in each group (n\u0026thinsp;=\u0026thinsp;6). The experimental groups were subcutaneously injected with 0.1 ml of the corresponding SVF cell suspension (2\u0026times;10^5 cells/ml), whereas the control group received 0.1 ml of PBS. The wound was then wrapped with sterile Tegaderm dressings (3M Healthcare, St Paul, MN, USA), which were changed every other day until day 14. Digital photos were taken on days 0, 2, 4, 7, 10, and 14, and skin tissue around the wound was collected on days 7 and 14. The wound area was quantified via ImageJ. For the anesthetized mice from which samples have already been taken, trained and skilled personnel euthanized them via the method of cervical dislocation. Death was confirmed by absence of corneal reflex and cessation of heartbeat for 5 minutes. All procedures were approved by the Experimental Animal Care and Use Committee of Nanfang Hospital and complied with the ARRIVE Guidelines 2.0.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e2.8 Histological staining\u003c/h2\u003e \u003cp\u003eThe harvested tissue samples were fixed in 10% formalin for 36\u0026ndash;48 hours, and paraffin-embedded tissue sections with a thickness of 4 micrometres were prepared. Following deparaffinization, the sections were stained with hematoxylin and eosin (H\u0026amp;E) and Masson's trichrome (BASMEDTSCI, Hubei) in accordance with the standard protocol and the manufacturer's instructions. For immunohistochemical staining, antigen retrieval was conducted using an EDTA solution (pH\u0026thinsp;=\u0026thinsp;9.0), followed by washing with PBS and blocking with goat serum for 1 hour at room temperature to prevent nonspecific binding. The sections were subsequently incubated overnight at 4\u0026deg;C with a primary antibody against CD31 (EPR17259; 1:1000; Abcam, Cambridge, MA). The next day, the sections were incubated with a secondary antibody conjugated with HRP, counterstained with hematoxylin, and developed with diaminobenzidine. Collagen content and vessel density were quantified via ImageJ software.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e2.9 snRNA-seq\u003c/h2\u003e \u003cp\u003eThe improved nuclear separation method was utilized to isolate nuclei from frozen human white adipose tissue (WAT) and C-SVF. Sequencing was conducted by SequMed Biotech, Inc. The single-cell nuclear suspension was assessed with a Countess II instrument prior to loading onto the machine, with an anticipated capture of 10,000 nuclei. Single-cell 3' v2 chemistry was employed to produce single-cell barcoded droplets (GEMs), and upon capturing the nuclei, the GEM solution appeared as a uniform milky white liquid. The GEM solution was subsequently withdrawn and transferred to PCR tubes for reverse transcription and library construction for sequencing. The \"gene expression library\" was quantified via a Qubit instrument, and the fragment size of the \"gene expression library\" was analyzed via Qpcr. Subsequently, Illumina NovaSeq was utilized with a PE150 sequencing strategy for paired-end sequencing, with both reads being 150 bp in length. The raw image files obtained from high-throughput sequencing were converted into sequencing reads (sequenced reads) via base calling with CASAVA and stored in FASTQ format for further analysis.\u003c/p\u003e \u003cdiv id=\"Sec12\" class=\"Section3\"\u003e \u003ch2\u003e2.9.1 snRNA-seq Data Analysis\u003c/h2\u003e \u003cp\u003eThe default parameters of Cell Ranger single-cell software (10x Genomics) were used for data alignment, unique molecular identifier (UMI) counting, cell counting and clustering analysis. The quality of the sample-specific FASTQ files was assessed via Cell Ranger's counts. The expression level of each transcript is determined by the quantity of UMI assigned to it. The filtered gene expression matrix was then employed for downstream analysis. RStudio (v.4.4.1) was used to visualize clustering and gene expression with the Seurat software package (v.5.1.0). The uniform manifold approximation and projection (UMAP) method in Seurat software was used for dimensionality reduction. The differential gene expression among clusters was analyzed via the Seurat function FindMarkers and the Wilcoxon test. Violin plots, heatmaps and individual UMAP maps of the given genes were generated via the VlnPlot, DoHeatmap and FeaturePlot functions of the Seurat toolkit, respectively.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section3\"\u003e \u003ch2\u003e2.9.2 Cell type identification\u003c/h2\u003e \u003cp\u003eUsing the Seurat R package, after the initial Cell Ranger metric check, cells with \u0026lt;\u0026thinsp;200 genes or \u0026gt;\u0026thinsp;20% mitochondrial genes and single-sample data with nCount_RNA\u0026thinsp;\u0026lt;\u0026thinsp;1,000 were excluded. After quality control, 7,691 C-SVF and 5,657 adipose tissue cells remained; 24,982 of the integrated data were retained for bioinformatics. PCA of the top 2,000 var. gene-aligned samples. In adipose tissue, C-SVF, and the integrated data, total-cell clustering was conducted at resolutions of 0.5, 0.5, and 0.2, respectively, via the \"FindClusters\" function. Dimensionality reduction was achieved via the RunUMAP function, and visualization was performed via UMAP. For subpopulation cell clustering, different cell types were extracted separately and clustered on the basis of their respective top 10 principal components. For adipose stem cells, the resolution was 0.5. Lymphocytes and macrophages were clustered according to their top 5 and top 6 principal components, respectively, with resolutions of 0.2 and 0.5. The marker genes for each cluster were identified via the \"FindAllMarkers\" function with the Wilcoxon rank-sum test. Only genes with |avg_log2FC| \u0026gt; 0.25 and p_val\u0026thinsp;\u0026lt;\u0026thinsp;0.05 were regarded as marker genes. Additional file 2 displays the marker genes for each cluster.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section3\"\u003e \u003ch2\u003e2.9.3 Differentially expressed gene (DEG) identification and gene ontology(GO) analysis\u003c/h2\u003e \u003cp\u003eThe \"FindMarkers\" function in Seurat was used to identify DEGs among different cell types or between C-SVF and adipose tissue for each cell type. The log fold change (log2FC) and adjusted p value of each DEG were calculated via the nonparametric two-sided Wilcoxon rank-sum test. DEGs are defined as those with |avg_log2FC| \u0026gt; 0.5 and p_val_adj\u0026thinsp;\u0026lt;\u0026thinsp;0.05 and are listed in Additional file 3. GO analysis of the DEGs was performed with clusterProfiler (v.4.14.4), and the results were visualized via the ggplot2 R package (v.3.5.1). Representative terms (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) were selected from the top 20 GO terms or pathways.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e2.10 Statistical analyses\u003c/h2\u003e \u003cp\u003eAll the data are expressed as the means\u0026thinsp;\u0026plusmn;\u0026thinsp;standard errors of the means. Statistical significance was determined via an unpaired t test for comparisons between two groups and two-way ANOVA for comparisons among three or more means, followed by Dunnett\u0026rsquo;s test for pairwise comparisons (Graph Pad Prism version 10). P values\u0026thinsp;\u0026lt;\u0026thinsp;0.05 denoted statistical significance.\u003c/p\u003e \u003c/div\u003e"},{"header":"3 Results","content":"\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\n\u003ch2\u003e3.1 C-SVF maintained the viability of ADSCs\u003c/h2\u003e\n\u003cp\u003eThe primary cell types in the SVF cell suspension encompass a variety of cell populations, such as ADSCs, endothelial cells (ECs), endothelial progenitor cells (EPCs), and pericytes [\u003cspan class=\"CitationRef\"\u003e16\u003c/span\u003e]. No significant difference was found in the proportion of cellular components between L-SVF and C-SVF, suggesting that device processing does not affect the composition of different cell populations. Among each group, ADSCs constituted the major cellular population in the SVF, with the proportions of ADSCs in the L-SVF and C-SVF being 11.93\u0026thinsp;\u0026plusmn;\u0026thinsp;1.20% and 13.16\u0026thinsp;\u0026plusmn;\u0026thinsp;0.42%, respectively (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eA). No notable difference in the morphology of ADSCs extracted via the two methods was detected (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eB). Furthermore, the data indicate that the labotort enzymatic method yields approximately 175,000\u0026thinsp;\u0026plusmn;\u0026thinsp;51,068 nucleated cells per gram of adipose tissue in approximately 2.5 hours, whereas the Celution 800 method produces approximately 112,000\u0026thinsp;\u0026plusmn;\u0026thinsp;35,452 nucleated cells in approximately 1.5 hours. There was no statistically significant difference in extraction efficiency between the two methods (L-SVF and C-SVF produced approximately 70,000\u0026thinsp;\u0026plusmn;\u0026thinsp;16,679 and 78,024\u0026thinsp;\u0026plusmn;\u0026thinsp;16,342 nucleated cells per gram of adipose tissue per hour, respectively, P\u0026thinsp;\u0026gt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eC). Notably, the proliferative capacity of C-SVF was marginally greater than that of L-SVF (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eD). The L-SVF group presented a greater incidence of apoptosis and cellular debris (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eE, F). Moreover, increased levels of collagenase residue were detected in the L-SVF extraction process (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eG).\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\n\u003ch2\u003e3.2 C-SVFeffectively improved skin wound closure.\u003c/h2\u003e\n\u003cp\u003eTo compare the regenerative capacity of SVF cells obtained via different methods, we used a full-thickness wound model in nude mice (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eA). Faster wound healing was observed in both the C-SVF and L-SVF groups (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eB). By the 7th day, the wound healing rate for C-SVF had reached 87.86\u0026thinsp;\u0026plusmn;\u0026thinsp;7.54%, and that for L-SVF had reached 83.96\u0026thinsp;\u0026plusmn;\u0026thinsp;11.80% (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05). Concurrently, the wound closure rates for the PBS group and M-SVF group were 60.01\u0026thinsp;\u0026plusmn;\u0026thinsp;13.49% (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and 77.01\u0026thinsp;\u0026plusmn;\u0026thinsp;17.39% (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05), respectively (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eC). The morphological characteristics of the wounds in each group were observed via H\u0026amp;E and Masson's trichrome staining. H\u0026amp;E staining on day 7 in each treatment group revealed a significant increase in granulation tissue thickness in the groups treated with C-SVF and L-SVF (compared with the PBS group, the C-SVF and L-SVF groups presented increases of 1.71\u0026thinsp;\u0026plusmn;\u0026thinsp;0.26-fold and 1.51\u0026thinsp;\u0026plusmn;\u0026thinsp;0.37-fold, respectively, P\u0026thinsp;\u0026lt;\u0026thinsp;0.05; the M-SVF group presented an increase of 1.13\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3-fold, P\u0026thinsp;\u0026gt;\u0026thinsp;0.05), indicating more effective re-epithelialization and a well-structured epidermis compared with the other groups. No significant differences were observed between these two groups. In stark contrast, the wound tissue of the M-SVF group contained many mature adipocytes ectopically deposited between the epidermis and dermis (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eD, E). Furthermore, Masson's trichrome staining demonstrated increased collagen deposition in the C-SVF-treated group. Compared with the PBS group (8.22\u0026thinsp;\u0026plusmn;\u0026thinsp;1.40%), the C-SVF, L-SVF and M-SVF groups presented increased collagen deposition (23.38\u0026thinsp;\u0026plusmn;\u0026thinsp;1.71%, 13.14\u0026thinsp;\u0026plusmn;\u0026thinsp;1.96% and 15.55\u0026thinsp;\u0026plusmn;\u0026thinsp;1.32%, respectively, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001)(Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eF,G). Next, we used CD31 for immunohistochemical staining to assess angiogenesis in each group. The results revealed that the C-SVF group had the highest vascular density (4.17\u0026thinsp;\u0026plusmn;\u0026thinsp;0.68%), which surpassed those of the M-SVF group and L-SVF group (3.65\u0026thinsp;\u0026plusmn;\u0026thinsp;0.69% and 3.76\u0026thinsp;\u0026plusmn;\u0026thinsp;0.74%, respectively, P\u0026thinsp;\u0026gt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eH,I).\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e\n\u003ch2\u003e3.3 Enrichment of functional cells within the C-SVF\u003c/h2\u003e\n\u003cp\u003eTo elucidate the cell subpopulations involved in C-SVF and their potential mechanisms, we conducted single-cell nuclear RNA sequencing analysis on subcutaneous adipose tissue and extracted C-SVF from a healthy 23-year-old female. The adipose tissue samples and C-SVF samples were each classified into 13 and 12 clusters, respectively (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eA, B). The results indicate that the identified cell clusters can be categorized into four major groups: adipocytes, ADSCs, vascular cells, and immune cells, which aligns with the findings of Lucas et al. [\u003cspan class=\"CitationRef\"\u003e18\u003c/span\u003e]. The large size and relatively fragile nature of mature adipocytes are considered to be the cause of adverse consequences such as oil swelling and inflammation after fat transplantation [\u003cspan class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e\n\u003cp\u003eCompared with adipose tissue samples, C-SVF samples contain significantly fewer adipocytes. These findings suggest that C-SVF extraction can effectively disrupt and eliminate mature adipocytes, thereby enriching stem cells. Moreover, immune cells and vascular cells were more abundant in the C-SVF.\u003c/p\u003e\n\u003cdiv id=\"Sec20\" class=\"Section3\"\u003e\n\u003ch2\u003e3.3.1 Characterization of ADSCs in C-SVF\u003c/h2\u003e\n\u003cp\u003eTo enhance the comparability of these two datasets, we integrated them and conducted quality filtering prior to analysis. Unsupervised clustering of the gene expression profiles revealed 15 distinct cell types (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eA). The cell clusters were annotated on the basis of the DEGs and established marker genes (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eB and Additional file 2). By statistically comparing the proportions of the nuclei of major cell types, we found that C-SVF contains two main subpopulations of ADSCs, with a greater percentage of Type 2 ADSCs (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eC). GO analysis revealed that pathways related to collagen and growth factor synthesis were upregulated in type 2 adipose-derived stem cells compared with type 1 adipose-derived stem cells (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eD). These findings indicate that the remarkable therapeutic effects of C-SVF on ECM deposition may be associated with the abundant content of type 2 ADSCs.\u003c/p\u003e\n\u003cp\u003eTo classify different subpopulations of ADSCs more precisely, we reclustered the cells at a higher resolution, dividing the ADSCs into 6 subtypes (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003eA, Additional file 2), all of which significantly expressed the identified ADSC markers Pdgfr\u0026alpha;, CD34, Itgb1 (CD29), and Thy1 (Cd90) [\u003cspan class=\"CitationRef\"\u003e20\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e23\u003c/span\u003e] (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003eB). Among them, clusters 0 and 4 expressed marker genes for adipogenesis-regulating cells (Aregs) as defined by Schwalie et al.[\u003cspan class=\"CitationRef\"\u003e24\u003c/span\u003e]. The tendency of Aregs to form adipocytes is significantly decreased and can negatively regulate the adipogenic capacity of other ADSCs through paracrine signaling mechanisms, such as Rtp3, Spink2, Fgf12, and Vit [\u003cspan class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e25\u003c/span\u003e].\u003c/p\u003e\n\u003cp\u003eCluster 1 exhibited relatively high expression of KDM4B, a gene known to be linked with the transcriptional activation of various metabolic genes, including PGC-1. Mice lacking KDM4B display compromised adrenergic responses and albinism in their brown adipose tissue[\u003cspan class=\"CitationRef\"\u003e26\u003c/span\u003e]. Consequently, Cluster 1 may indicate potential beige adipocyte precursors within white adipose tissue. In Cluster 2, the APOE gene is significantly overexpressed, and its functions encompass multidimensional regulatory mechanisms. On the one hand, it facilitates adipocyte differentiation by activating the PPAR\u0026gamma; pathway[\u003cspan class=\"CitationRef\"\u003e27\u003c/span\u003e]. On the other hand, it neutralizes proinflammatory factors (such as TNF-\u0026alpha; and IL-6) to inhibit the activation of the NF-\u0026kappa;B pathway while also promoting the polarization of M2 macrophages, thus forming an immunosuppressive microenvironment[\u003cspan class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e29\u003c/span\u003e]. These functions suggest that Cluster 2 genes may be involved in maintaining metabolic homeostasis and tissue repair by regulating lipid metabolism and the immune microenvironment. Cluster 3 cells display high expression of Dpp4 and CD55. Research indicates that the expression levels of general stem cell markers (such as CD34 and CD73), genes linked to cancer stem cells (CD99 and ITGB3), and an embryonic stem cell marker (GGT1) are elevated within this subset [\u003cspan class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e31\u003c/span\u003e]. These findings suggest that this cell subset may have enhanced self-renewal and proliferation capabilities. Further studies have demonstrated that this subset has superior therapeutic effects in promoting wound healing and regeneration [\u003cspan class=\"CitationRef\"\u003e32\u003c/span\u003e]. Additionally, Cluster 3 shows a certain level of CD24 expression, and CD24\u0026thinsp;+\u0026thinsp;cells have been previously confirmed to be adipogenic progenitor cells capable of fat formation in vivo [\u003cspan class=\"CitationRef\"\u003e23\u003c/span\u003e]. Therefore, this subset may also play a significant role in the process of adipocyte differentiation.\u003c/p\u003e\n\u003cp\u003eIn cluster 5, transcriptomic analysis revealed significantly elevated expression levels of RUNX3 and CCL5. Functional validation studies have demonstrated that ADSCs exert proangiogenic effects on human umbilical vein endothelial cells (HUVECs) through RUNX3-mediated signaling pathways, promoting endothelial cell proliferation, migration, and tube formation[\u003cspan class=\"CitationRef\"\u003e33\u003c/span\u003e]. Subsequent in vivo investigations further identified CCL5 as a critical effector molecule in ADSC-driven angiogenesis during cutaneous wound healing[\u003cspan class=\"CitationRef\"\u003e34\u003c/span\u003e]. Additionallly, cluster 5 cells expressed high levels of inflammatory markers (such as \u003cem\u003eCcl5, IL7R, Ptptc\u003c/em\u003e, and \u003cem\u003eIL32\u003c/em\u003e), indicating that cluster 5 cells might orchestrate wound healing through bidirectional crosstalk with infiltrating immune cells [\u003cspan class=\"CitationRef\"\u003e35\u003c/span\u003e]. Collectively, these results suggest that cluster 5 may have potential application value in modulating inflammation resolution and angiogenesis (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003eC, D).\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec21\" class=\"Section3\"\u003e\n\u003cp\u003eOn the basis of the above analysis, we determined that specific ADSC subsets dynamically interact with macrophages during wound repair. Notably, T lymphocytes were significantly enriched in the C-SVF fraction, constituting the dominant cell population (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eC). To characterize these interactions in detail, we performed a comprehensive analysis of immune cell subsets within the C-SVF, categorizing them into two major lineages: (i) lymphoid cells dominated by T cells and (ii) myeloid cells comprising mainly M2-like macrophages[\u003cspan class=\"CitationRef\"\u003e36\u003c/span\u003e]. Sngle-cell profiling of these populations enabled the construction of a high-resolution atlas defining the transcriptional diversity and functional heterogeneity of distinct immune cell subsets.\u003c/p\u003e\n\u003cp\u003eIn the major lymphocyte group, four distinct clusters (clusters 0\u0026ndash;3 in descending abundance, Fig.\u0026nbsp;6A, Additional file 2) were identified. Cluster 0 presented relatively high expression of CD8A. Research suggests that the CD8\u0026alpha; protein encoded by CD8A may participate in ADSC\u0026ndash;immune cell crosstalk and regulate local immune responses[\u003cspan class=\"CitationRef\"\u003e37\u003c/span\u003e]. Cluster 1 highly expresses CD28 and PCAT-1 and contains genes related to regulatory T-cell (Treg) subtypes [\u003cspan class=\"CitationRef\"\u003e38\u003c/span\u003e]. In vitro, ADSCs can promote paracrine-mediated anti-inflammatory events by decreasing CD28-T cells and increasing FoxP3\u0026thinsp;+\u0026thinsp;Tregs [\u003cspan class=\"CitationRef\"\u003e39\u003c/span\u003e]. Elevated PCAT-1 levels are associated with reduced immune cell infiltration [\u003cspan class=\"CitationRef\"\u003e40\u003c/span\u003e]. Cluster 2 had relatively high CTBP2 expression. Notably, LW et al. reported that miR-342-3p from human ADSCs can inhibit CtBP2 to activate adipogenic factor and marker expression [\u003cspan class=\"CitationRef\"\u003e41\u003c/span\u003e]. Cluster 3 expressed TRM and B-cell marker genes[\u003cspan class=\"CitationRef\"\u003e38\u003c/span\u003e] and highly expressed EGFR. A previous study[\u003cspan class=\"CitationRef\"\u003e42\u003c/span\u003e] indicated that human ADSCs can activate skin stem cells via the EGFR/MEK/ERK pathway to promote wound healing (Fig.\u0026nbsp;6B).\u003c/p\u003e\n\u003cp\u003eThe myeloid group was classified into six clusters (clusters 0\u0026ndash;5, Fig.\u0026nbsp;6C, Additional file 2). Clusters 0 and 1 highly expressed LYVE1, which is potentially involved in tissue support and angiogenesis[\u003cspan class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e44\u003c/span\u003e]. Notably, Cluster 0 exhibited marked upregulation of CD163L1, an endocytic receptor whose expression is induced during monocyte-to-macrophage differentiation under M-CSF stimulation but suppressed by proinflammatory mediators such as TNF-\u0026alpha;[\u003cspan class=\"CitationRef\"\u003e45\u003c/span\u003e]. Cluster 2 expressed the marker genes of metabolically regulated macrophages[\u003cspan class=\"CitationRef\"\u003e18\u003c/span\u003e], which are important for regulating inflammatory mediator and lipid metabolism balance[\u003cspan class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e47\u003c/span\u003e]. Additionally, cluster 2 and 3 relatively highly expressed genes related to cell‒matrix interactions and ECM remodeling, such as \u003cem\u003eC3\u003c/em\u003e and \u003cem\u003eS100A10\u003c/em\u003e[\u003cspan class=\"CitationRef\"\u003e48\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e49\u003c/span\u003e]. Cluster 5 also expressed genes related to lipid-associated macrophages (LAMs) (such as \u003cem\u003eCD9, ABP4, CD68\u003c/em\u003e, and \u003cem\u003eN1\u003c/em\u003e) [\u003cspan class=\"CitationRef\"\u003e50\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e52\u003c/span\u003e]. LAMs express many genes related to immunosuppression (e.g., Lgals1 and Lgals3), suggesting that they might be involved in regulating inflammatory responses related to cell death and lipid accumulation[\u003cspan class=\"CitationRef\"\u003e53\u003c/span\u003e]. Burl et al.[\u003cspan class=\"CitationRef\"\u003e54\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e55\u003c/span\u003e] identified a macrophage cluster (cluster 5 highly expressed relevant genes) and suggested that these cells might provide growth factors for adipose stem cells (Fig.\u0026nbsp;6D).\u003c/p\u003e\n\u003cp\u003eOn the basis of the above analysis, we posit that within the C-SVF fraction, ADSC subsets and diverse immune cell populations likely form a bidirectional regulatory network via paracrine signaling. ADSCs suppress excessive inflammation and remodel the immune microenvironment through the secretion of bioactive substances, whereas immune cells reciprocally promote ADSC proliferation, differentiation, and angiogenic gene expression via cytokine release. This dynamic interplay results in a multidimensional regulatory network for wound healing.\u003c/p\u003e\n\u003c/div\u003e\n\u003c/div\u003e"},{"header":"4 Discussions","content":"\u003cp\u003eSVF cells are abundant in ADSCs and other therapeutically potent cell types such as vascular endothelial cells and tissue macrophages, which are crucial for wound healing and tissue regeneration. Currently, the enzymatic digestion method is predominant in SVF extraction. It is well-established, yielding relatively high cell numbers and survival rates, and is advancing toward closed, automated processes[\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e]. Various semiautomatic and fully automatic SVF extraction devices have been successively introduced to the market in recent years. Preclinical and clinical studies have indicated that SVF cells obtained through the decellularization system can facilitate angiogenesis[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e], reduce inflammation[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e], and improve other parameters related to the healing mechanism[\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e, \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOur studies revealed that the production efficiency of C-SVF is comparable to that of the manual enzymatic digestion method, the prevalent technique for clinically isolating SVF cells. However, the Celution system offers several benefits, including shorter operation times, a simpler procedure, a reduced risk of external contamination, less reliance on operator skill, and improved reproducibility. Moreover, commercial extraction kits tend to have lower residual collagenase levels. Currently, various countries have different views on the use of enzymes, but there is a common consensus to limit the addition of foreign substances. Animal studies indicate that C-SVF is as effective as L-SVF in accelerating wound healing and slightly outperforms mechanically extracted M-SVF. These findings imply that the C-SVF is a novel and superior source of stem cells. Although M-SVF might not excel in facilitating tissue regeneration, its role in regenerative therapy for volumetric defects is nonsubstitutable. Hence, it is conceivable that C-SVF could be merged with conventional M-SVF in the future, increasing the functional cell content within M-SVF while sustaining its effective volumetric capacity, thereby resulting in enhanced therapeutic results.\u003c/p\u003e \u003cp\u003eMoreover, for the first time, we performed snRNA-seq on SVFs extracted from commercial machines. By integrating and comparing these results with sequencing data from intact adipose tissue, we discovered that adipose-derived stem cells constitute one of the primary cellular populations in C-SVF, making them probable candidates for potential functional roles.\u003c/p\u003e \u003cp\u003eThrough a more in-depth analysis of cell subtypes, we further classified ADSCs into six functionally heterogeneous subsets, each of which exhibited unique molecular characteristics and potential for clinical application. For example, high expression of KDM4B in Cluster 1 was significantly associated with the activation of metabolic genes mediated by PGC-1α. This epigenetic regulatory mechanism can drive the browning process of white adipose tissue by promoting mitochondrial biogenesis. Our previous research revealed that the appearance of beige adipocytes in wound tissue contributes to wound repair[\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e]. The secretion of brown adipokines (e.g., FGF21) further accelerates metabolic reprogramming, collagen deposition, and angiogenesis in the wound microenvironment [\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e]. Cluster 2 conversely regulated both the immune microenvironment and lipid metabolism through a dual APOE-dependent axis. Functional validation confirmed that APOE-overexpressing ADSCs significantly improved healing in diabetic ulcers, positioning APOE as a metabolic‒immunomodulatory hub[\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e, \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e]. Collectively, these data highlight that ADSC subpopulations promote wound repair through multidimensional regulatory networks integrating metabolic reprogramming, immune modulation, and angiogenic differentiation.\u003c/p\u003e \u003cp\u003eThis study reveals the pivotal role of the dynamic interplay between ADSC subsets and the immune microenvironment in wound repair. Single-cell analysis revealed that ADSCs establish a multidimensional regulatory framework with immune cells (T cells and macrophages) via paracrine signaling. T cells in wound tissues display high heterogeneity (Clusters 0\u0026ndash;3). ADSCs may promote Treg (Cluster 1) proliferation and suppress CD8\u0026thinsp;+\u0026thinsp;T-cell activity, suggesting a potential strategy to counter the T-cell immune imbalance in diabetic wounds induced by the high-glucose milieu[\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e]. Macrophage subset analysis indicated that C-SVF is abundant in M2 anti-inflammatory macrophages. These cells curb excessive inflammation by secreting anti-inflammatory cytokines (e.g., IL-10 and TGF-β) [\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e], promote angiogenesis by releasing vascular endothelial growth factor, and expedite tissue remodeling through collagen matrix synthesis[\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e, \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e]. Cluster 5 combines with ADSCs for proliferation by highly expressing immunosuppressive factors such as Lgals3, creating an immunosuppressive-stem cell activation symbiotic system. These findings offer a novel perspective on the immunometabolic regulation of wound repair. Future research could integrate spatial transcriptomics and single-cell epigenomics to dissect the dynamic intersubset network and validate its translational potential as a therapeutic target in clinical cohorts.\u003c/p\u003e \u003cp\u003eImportantly, our study has certain limitations. On the one hand, in the meta-analysis by Massier et al. [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e], the correlation between snRNA-seq data and the transcriptional traits of isolated adipocytes was tenuous. For example, only feeble adipocyte subtype marker genes (e.g., Lep, Saa1, and Rbp4) [\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e] were detected in our snRNA-seq data. Thus, ascertaining adipocyte subtypes mandates combined analysis via diverse technical platforms (such as spatial transcriptomics). On the other hand, our sequencing results are based on a single sample, which significantly limits the universality of the observed outcomes. Additionally, we anticipate future studies that can further investigate the long-term effects of these technologies and cell populations. By delving deeper into its mechanism of action, targeted improvements to the corresponding cell extraction process can help enhance its therapeutic effects and broaden its applications in regenerative medicine.\u003c/p\u003e"},{"header":"5 Conclusions","content":"\u003cp\u003eIn our study, the C-SVF extraction technique was proven to have extraction efficiency comparable to that of the traditional L-SVF. Furthermore, it can effectively promote wound regeneration, and its efficacy is superior to that of the SVF components obtained through other methods.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eADSCs: adipose-derived stem cells\u003c/p\u003e\n\u003cp\u003eSVF: stromal vascular fraction\u003c/p\u003e\n\u003cp\u003eECM: extracellular matrix\u003c/p\u003e\n\u003cp\u003eADRCs: adipose-derived regenerative cells\u003c/p\u003e\n\u003cp\u003esnRNA-seq: single-nucleus RNA sequencing\u003c/p\u003e\n\u003cp\u003eL-SVF: SVF prepared by laboratory enzymatic digestion\u003c/p\u003e\n\u003cp\u003erpm: revolutions per minute\u003c/p\u003e\n\u003cp\u003ePBS: phosphate buffered saline\u003c/p\u003e\n\u003cp\u003eM-SVF: SVF generated by mechanical emulsification\u003c/p\u003e\n\u003cp\u003eC-SVF: SVF generated by commercial cell separation systems\u003c/p\u003e\n\u003cp\u003eDMEM: dulbecco's modified eagle medium\u003c/p\u003e\n\u003cp\u003eOD: optical density\u003c/p\u003e\n\u003cp\u003eH\u0026amp;E: hematoxylin and eosin\u003c/p\u003e\n\u003cp\u003eEDTA: ethylenediaminetetraacetic acid\u003c/p\u003e\n\u003cp\u003eHRP: horseradish peroxidase\u003c/p\u003e\n\u003cp\u003eWAT: white adipose tissue\u003c/p\u003e\n\u003cp\u003eGEMs: gel bead in emulsion microdroplets\u003c/p\u003e\n\u003cp\u003eUMI: unique molecular identifiers\u003c/p\u003e\n\u003cp\u003eUMAP: uniform manifold approximation and projection\u003c/p\u003e\n\u003cp\u003ePCA: principal component analysis\u003c/p\u003e\n\u003cp\u003eDEG: differentially expressed gene\u003c/p\u003e\n\u003cp\u003eGO: gene ontology\u003c/p\u003e\n\u003cp\u003eECs: endothelial cells\u003c/p\u003e\n\u003cp\u003eEPCs: endothelial precursor cells\u003c/p\u003e\n\u003cp\u003eAregs: adipogenesis-regulating cells\u003c/p\u003e\n\u003cp\u003eHUVECs: human umbilical vein endothelial cells\u003c/p\u003e\n\u003cp\u003eTregs: regulatory T cells\u003c/p\u003e\n\u003cp\u003eLAM: lipid associated macrophage\u003c/p\u003e\n\u003cp\u003eCE: onformit\u0026eacute; europ\u0026eacute;enne\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e \u003cp\u003eAll experimental protocols were approved by the Medical Ethics Committee of Nanfang Hospital, Southern Medical University (approval No. NFEC-2024-296; June 19, 2024) under the ethics review protocol titled \"Comparative Study on the Composition and Function of Adipose-Derived Regenerative Cells (ADRCs) Extracted by Celution\u0026reg; 800 and Stromal Vascular Fraction (SVF) Cells Obtained Through Different Methodological Approaches\". This approval is applicable to the use of human specimens and animal research.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eConsent for publication\u003c/strong\u003e \u003cp\u003eNot applicable.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eCompeting interests\u003c/h2\u003e \u003cp\u003eThe authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThis research was funded by Cytori Therapeutics LLC, under the project named \"Comparative Study on the Composition and Function of Adipose-Derived Regenerative Cells (ADRCs) Extracted by Celution 800 and Stromal Vascular Fraction (SVF) Cells Obtained by Different Methods \" with the grant number K61010028. The funders had no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript.\u003c/p\u003e\u003ch2\u003eAuthors\u0026rsquo; Contributions\u003c/h2\u003e \u003cp\u003eJR and SX conceived and designed the experiment. LF supervised this project. SX performed the experiments and conducted the bioinformatics analyses. SX and ZQ composed the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgments\u003c/h2\u003e \u003cp\u003eThe authors would like to thank the many surgeons and patients who have donated adipose tissue for this research. We also thank Cytori Therapeutics for providing the Celution system and accessories for this study. The authors declare that they have not use AI-generated work in this manuscript\" in this section.\u003c/p\u003e\u003ch2\u003eAvailability of data and materials\u003c/h2\u003e \u003cp\u003eThe single-nucleus RNA sequencing datasets generated and analyzed during this study contain unpublished findings that are currently being utilized in ongoing investigations. To protect the integrity of related follow-up studies, raw sequencing data and processed matrices will be made available upon reasonable request through direct communication with the corresponding author (email: [email protected]). Full public deposition in recognized repositories (e.g., GEO, ENA, or SRA) will occur upon completion of the research program, with accession codes provided in future publications. All other experimental materials are available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eHsieh MW et al. 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Sci Rep. 2022;12(1):14929.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRX Z, HS B. Research progress in macrophages regulation on skin wound healing. Chin J Plast Surg. 2023;39(2):231\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMinutti CM, et al. Tissue-specific contribution of macrophages to wound healing. Semin Cell Dev Biol. 2017;61:3\u0026ndash;11.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKim SY, Nair MG. Macrophages in wound healing: activation and plasticity. Immunol Cell Biol. 2019;97(3):258\u0026ndash;67.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eB\u0026auml;ckdahl J, et al. Spatial mapping reveals human adipocyte subpopulations with distinct sensitivities to insulin. Cell Metab. 2021;33(9):1869\u0026ndash;e18826.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"stem-cell-research-and-therapy","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scrt","sideBox":"Learn more about [Stem Cell Research \u0026 Therapy](http://stemcellres.biomedcentral.com)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/scrt/default.aspx","title":"Stem Cell Research \u0026 Therapy","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"stromal vascular fraction, adipose-derived stem cells, enzyme digestion method, separation equipment, mechanical method, single-nucleus RNA sequencing","lastPublishedDoi":"10.21203/rs.3.rs-6399413/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6399413/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground: \u003c/strong\u003eIn the field of regenerative therapy, the stromal vascular fraction (SVF) extracted from adipose tissue has been widely recognized for its significant benefits. However, the cellular composition and therapeutic effect of SVF products prepared via different methods are unclear.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e SVF cells were obtained via three approaches: (1) generation of the SVF via mechanical emulsification (M-SVF), (2) generation of the SVF via laboratory enzymatic digestion (L-SVF), and (3) generation of the SVF via commercial cell separation systems (C-SVF). We evaluated their healing effects on mouse wounds. Additionally, we utilized single-nucleus RNA sequencing (snRNA-seq) technology to explore the cellular composition of the C-SVF.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eThe cell yield of C-SVF was comparable to that of L-SVF. During in vitro culture, C-SVF exhibited enhanced proliferation and a reduced proportion of apoptotic cells. In a mouse wound model, the application of C-SVF facilitated the closure of mouse wounds and improved collagen remodeling and angiogenesis in the wound area. Additional snRNA-seq analysis revealed that APOE+ adipose-derived stem cells and immune cells, especially M2 anti-inflammatory macrophages, are enriched in C-SVF, which together promote wound repair, and that APOE+ adipose-derived stem cells (ADSCs) and immune cells, especially M2 anti-inflammatory macrophages, are enriched in C-SVF, which jointly regulate and promote wound repair.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion: \u003c/strong\u003eA commercial extraction system is an effective method for isolating viable SVF cells enriched with APOE+ ADSCs and M2 macrophages.\u003c/p\u003e","manuscriptTitle":"Therapeatic evaluation and single cell analysis of adipose stromal vascular fraction isolation from a commercial cell separation system","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-16 09:43:27","doi":"10.21203/rs.3.rs-6399413/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"","date":"2025-05-14T11:18:07+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-05-14T09:54:14+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-04-30T03:11:55+00:00","index":"","fulltext":""},{"type":"submitted","content":"Stem Cell Research \u0026 Therapy","date":"2025-04-28T04:07:41+00:00","index":"","fulltext":""},{"type":"decision","content":"Major Revision","date":"2025-04-22T08:33:12+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"stem-cell-research-and-therapy","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scrt","sideBox":"Learn more about [Stem Cell Research \u0026 Therapy](http://stemcellres.biomedcentral.com)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/scrt/default.aspx","title":"Stem Cell Research \u0026 Therapy","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"1ccf970f-06de-4b2e-86f0-a74186350a81","owner":[],"postedDate":"May 16th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-11-10T16:06:49+00:00","versionOfRecord":{"articleIdentity":"rs-6399413","link":"https://doi.org/10.1186/s13287-025-04732-5","journal":{"identity":"stem-cell-research-and-therapy","isVorOnly":false,"title":"Stem Cell Research \u0026 Therapy"},"publishedOn":"2025-11-07 15:57:36","publishedOnDateReadable":"November 7th, 2025"},"versionCreatedAt":"2025-05-16 09:43:27","video":"","vorDoi":"10.1186/s13287-025-04732-5","vorDoiUrl":"https://doi.org/10.1186/s13287-025-04732-5","workflowStages":[]},"version":"v1","identity":"rs-6399413","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6399413","identity":"rs-6399413","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}