mRNA profiling of mesenchymal stem cell-derived exosomes reveals their function in accelerating wound healing

mRNA profiling of mesenchymal stem cell-derived exosomes reveals their function in accelerating wound healing | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article mRNA profiling of mesenchymal stem cell-derived exosomes reveals their function in accelerating wound healing Uyen Thi Trang Than, Hoai Thi Thanh Nguyen, Quang Minh Dang, Thu-Huyen Nguyen, and 9 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8130672/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 21 Mar, 2026 Read the published version in Scientific Reports → Version 1 posted 13 You are reading this latest preprint version Abstract Extracellular vesicles (EVs) are emerging as innovative tools for regenerative and therapeutic applications, including wound healing, owing to their ability to encapsulate bioactive agents from their parent cells. In this study, we profiled the transcriptome of umbilical cord mesenchymal stem cell (UCMSC)-derived exosomes (EXs) using RNA-seq and explored the functional roles of their transcriptome, particularly in cutaneous wound repair. We detected 4,578 protein-coding genes in UCMSC-derived EXs, of which 2,004 were upregulated, and 2,574 were downregulated relative to their secreting cells. Notably, many EX-enriched genes were associated with wound-healing biology, and pathway analysis revealed that upregulated exosomal genes were involved in GO terms and KEGG pathways related to DNA replication, ribosome function, cell cycle regulation, and pyrimidine metabolism. To validate UCMSC-EX's capability for wound healing predicted through in silico analyses, we further assessed EX penetration into the dermis, cellular uptake, and therapeutic efficacy in a burned mouse model. UCMSC-derived EXs efficiently penetrated human dermal tissue, were internalized by fibroblasts, and promoted fibroblast and keratinocyte proliferation and migration in 2D culture. In vivo , EX treatment accelerated wound closure, particularly during the early stages of healing. Overall, our findings demonstrate selective mRNA enrichment in UCMSC-derived EXs and highlight their promising therapeutic potential in cutaneous wound healing. Biological sciences/Cell biology Biological sciences/Molecular biology Biological sciences/Stem cells Umbilical mesenchymal stem cell-derived exosomes RNA-seq exosome penetration cutaneous wound healing Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Introduction Exosomes (EXs) or small vesicles, a specific subtype of extracellular vesicles (EVs), are nanosized particles with diameters ranging from 30 to 150 nm 1 . They are secreted by virtually all cell types and could be obtained from conditioned media during cell culture in vitro and different biological fluids such as blood, urine, saliva, amniotic fluid, and breast milk 2 , 3 . The intravesicular contents of EVs display considerable diversity, which depends on their cellular origin, physiological state, and sorting mechanisms 4 , 5 ; thus, EXs are packed with bioactive molecules, including proteins (tetraspanins, heat-shock proteins), nucleic acids (RNAs, microRNAs), and lipids (ceramides, cholesterol, sphingolipids) 4 , 6 , 7 . According to the latest update of ExoCarta, 13476 proteins, 3408 mRNAs, 10755 miRNAs, and 3946 lipid entries have been detected in exosomes ( http://www.exocarta.org/ , accessed 29/06/2025). Given the remarkable diversity in EX compositions linked to diverse cellular provenance, comprehensive omic-level profiling of these particles is of significant value. Such investigations hold the potential to unveil mechanisms and therapeutic targets worthy of further exploration and development. In recent years, investigations have confirmed that mesenchymal stem cells (MSCs)-derived EXs possess a wide range of therapeutic capabilities across diverse conditions, including cardiovascular and renal protection, stroke, perinatal hypoxic-ischemic brain injury, hind-limb ischemia, immune-related diseases, cancer, wound healing, and even COVID-19 8,9 . EXs derived from MSCs of varying origins or exposed to distinct external stimuli exhibit markedly different compositions of functional molecules and heterogeneous characteristics, consequently manifesting divergent therapeutic properties 9 – 11 . For example, bone marrow MSC-derived EXs have pronounced regeneration capacity through the induction of angiogenesis, adipose tissue MSC-derived exosomes show the most influential secretory activity and immunomodulation compared with MSCs derived from other sources, and UCMSC-derived EXs primarily participate in tissue repair 12 . Additionally, EXs have a significant impact on skin regeneration through modulating cell behaviors and functions of immune cells, fibroblasts, and endothelial cells, regulating inflammation and immune microenvironment, and promoting collagen deposition and angiogenesis by enabling intercellular crosstalk 13 – 16 . However, the mechanistic understanding of how EXs elicit their biological effects remains incomplete. While much of the focus has been on either EXs' broad interaction with cellular targets or protein-level characterisation of EXs' cargo, little emphasis has been placed on EXs' transcriptome. Various groups have reported the presence of mRNA in EXs, as reviewed elsewhere 17 . However, the properties and functions of coding RNAs remain largely unexplored 18 , 19 , which may strengthen the mechanistic understanding behind EXs' properties, such as wound healing. In this study, we investigated mRNA transcripts in UCMSC-derived EXs and simultaneously examined the wound healing capability of these EXs in both in vitro and in vivo models. Results Exosome characterization We used differential centrifugation to isolate exosomes (EXs) from conditioned media of UCMSCs at P5. This population was examined for size distribution using the NTA technique and showed that the size distribution of EXs ranged from 40 nm to 350 nm, with the highest peak at 100 nm (Fig. 1 a). Results from TEM imaging showed that a quite homologous cup-shaped morphology and smooth surface of EXs have been observed under TEM (Fig. 1 b). Additionally, immunohistological analysis showed that exosomal markers of CD9, CD63, HSP70, and AGO2 have been detected in exosome fraction (Fig. 1 c). The size of EXs analyzed using the NTA is consistent with the size observed under TEM, around 100 nm. Protein-coding RNAs are differentially enriched in exosomes, and many are associated with wound-healing In order to characterize the RNAs contained within EVs released from UCMSCs and secreting cells, an RNA sequencing approach was performed using the Nextseq 500/550 system (Illumina, USA). Statistics for alignment to the human HG38 genome and the proportion of uniquely mapped reads are shown in Table 1 . More than 4 million uniquely mapped reads were obtained for all samples. The alignment rate was around 90% − 91% (Table 1 ). Table 1 Read mapping, alignment, and feature-counting statistics Category Statistic Exosome 1 Exosome 2 Exosome 3 UCMSC1 UCMSC2 UCMSC3 Sequence counts Average number of uniquely mapped reads 4,173,608 5,111,878 4,518,578 5,167,534 8,615,614 8,097,777 Average number of duplicated reads 5,250,685 7,443,151 4,478,099 5,610,149 11,512,273 12,144,406 Alignment Total pair of reads 9,424,293 12,555,029 8,996,677 10,777,683 20,127,887 20,242,183 Alignment rate 89.90% 89.85% 90.23% 90.25% 90.70% 91.38% Mapping reads to features Total alignments 12,783,855 15,408,981 11,788,975 13,432,806 23,036,659 22,990,238 Successful assignment rate of reads to features 66.0% 74.4% 67.8% 70.8% 78.1% 81.2% We first investigated the different biotypes of RNAs present in EXs. Results showed that the MGcound toolkit annotated relevant RNA features such as long RNA introns, long RNA exons, snoRNAs, and snaRNAs in the dataset (Fig. 2 a-b). Regarding small non-coding RNAs, it was highlighted that SNORA49, RMRP-202, and SCARNA7 are downregulated in EXs, but RN7SL471P is upregulated in EXs. We observed a notable enrichment of various endogenous non-coding RNAs belonging to the RN7SL family, which encodes the signal recognition particle complex. Additionally, we found that our approach mainly captured protein-coding mRNAs in EXs (Fig. 2 b). To assess which coding transcripts were preferentially exported to EXs or retained in mother cells, using the R package DESeq2 20 , a differential analysis was performed to evaluate coding RNA abundances across UCMSCs and the EXs they secrete. Using a threshold of adjusted p-value = 0.05 and |Log2(Fold Change)| greater than 1, about 4578 genes were differentially expressed in UCMSC-derived EXs (Fig. 2 c, Additional file 1 – Fig. 1 ). Among them, 2574 genes were downregulated, and 2004 genes were upregulated in UCMSC-derived EXs (padj < 0.05) (Fig. 2 b-c). Genes in clusters identified through hierarchical clustering of top-upregulated genes in UCMSC-EXs could be found in the Additional file 2 – Table 1 . Notably, the most enriched transcripts in EXs included Net 1 (Log 2 FC = 7.03, padj = 1.50 × 10 –31 ), Track2 (Log 2 FC = 6.70, padj = 1.59 × 10 –50 ), Rab13 (Log 2 FC = 6.44, padj = 9.7 × 10 –14 ), and Kif1c (Log 2 FC = 6.26, padj = 4.53 × 10 –34 ). Interestingly, Anp32b (Log 2 FC = 5.38, padj = 2.69 × 10 –21 ), which harbors immune functions, and Dgf11 (Log 2 FC = 5.45, padj = 3.02 × 10 –33 ), which has multiple effects on cell development and physiology, were also one of the most enriched genes in EXs in our dataset. Interestingly, these genes are reported to be highly enriched in human umbilical cord vein endothelial cell-derived EXs. Therefore, our result strongly reproduced previous findings in EXs derived from endothelial cells 21 , indicating perhaps the existence of conserved exosome mRNA markers. In relation to wound healing, we found that many genes with the most significant magnitude of enrichment in EXs (evidenced by read counts and fold enrichment) are established potentiators of wound healing (Fig. 2 b). These genes play diverse but relevant roles in the physiological wound-healing response. Of those, Kif1c , Net1 , Map4k4 , and Coro1c are applicable due to their involvement in regulating cellular migration during wound healing. Other relevant genes included Discoidin domain receptor 2 ( Ddr2 ), Mmp2 , and zinc finger E-box binding homeobox 1 ( Zeb1 ). The data of many protein-coding mRNAs upregulated in EXs are associated with wound healing, indicating that UCMSC-derived EXs may play an essential role in the cutaneous healing process. Network analysis and hierarchical clustering description indicated RNAs enriched in exosomes involved in the wound healing process We performed a two-pronged approach to investigate the gene modules representing higher-level biological processes that are enriched within the community of coding RNAs in UCMSC-derived EXs. First, we constructed a protein interaction network for all genes contained within EXs and deconvolved network structures into clusters of highly interconnected nodes to define notable network structures that may underpin biological functions. In parallel, hierarchical clustering was performed to examine the pairwise correlations of genes strongly enriched in UCMSC-EXs. Pearson correlation coefficient was used to construct the distance matrix, with average as the agglomeration method. The goal was to identify clusters of highly correlated genes, suggesting a specific biological function enriched within EXs. The STRING protein interaction database was then used to map interactions between gene-encoded proteins contained within the cluster. Our rationale is that by combining two layers of evidence characterizing gene-gene association (by measuring the Pearson correlation coefficient), and protein interactions (by using the STRING database), we can comprehensively unveil emergent biological properties that may otherwise be missed. For the first approach, after mapping exhaustive protein interactions between exosome-enriched genes, we used MCODE to deconvolve the network into significant clusters 22 . Two major networks were identified using a threshold score of 25 (Fig. 3 a-b, Table 2 , Supplemental Additional file 3 – Table 2 ). Table 2 Network analysis statistics of clusters 1 and 2 - the two most significant clusters of protein interaction identified from exosome-enriched genes * . Cluster 1 Cluster 2 Number of nodes 200 55 Number of edges 9154 797 Network density 0.460 0.537 Network centralization 0.155 0.308 * Gene list contributed in clusters 1 and 2 could be found in Supplemental Additional file 3 – Table 2 . Regarding the first network, the gene Mcm3 is a central hub within this network, with connections to 200 nodes in the network (Fig. 3 a). Mcm3 promotes cellular proliferation and restricts apoptosis in many models and carcinoma cell types 23 – 25 , and thus might be a central regulator of wound healing. Mcm3 's ability to direct cell proliferation is related to its ability to regulate DNA replication. Mcm3 is indispensable for initiating eukaryotic genome replication and is required to ensure that DNA replication is initiated precisely once per cell cycle. The second clusters include genes associated with mitochondria, many of which are subtypes of mitochondrial complex 1: NADH: ubiquinone oxidoreductase supernumerary subunits ( Nduf ) such as Ndufs5 , Ndufs8 , Ndufb2 , Ndufb6 , and Ndufb10 . Many other members of this cluster are subunits of the mitochondrial ATP synthase ( Atp5j2 , Atp5o , Atp5e , Atp5g1 , and Atp5g3 ) that have a role in driving the synthesis of ATP with the presence of a proton gradient, allowing cells to efficiently utilize the energy generated during electron transport 26 . Also, parts of this cluster are eight genes encoding mitochondrial and cellular ribosomal proteins that are part of the MRP and RPL protein families. Altogether, this cluster likely underlies major structural constituents of the mitochondrial ribosome and ATPase, which are essential for energy and protein regulation. For the second approach, following hierarchical clustering, two significant clusters consisting of strongly correlated gene features were identified (Fig. 3 c-d). To understand the biological processes governed by genes contained within these clusters, using the STRING protein interaction databases, we further identified the interconnected network motif (cluster) of protein interactions using MCODE. In cluster 1, genes in the MCODE-identified network are extensively documented to be involved in processes related to wound healing, notably cell migration and growth: Ska3 , Cenpu , and Cks1b . Pathway analysis of clusters revealed the enrichment of GO processes related to organ development and inflammation, which are all key to wound healing (Additional file 4 – Fig. 2 a). Regarding cluster 2, this network underpins mitotic cell division and cell cycle control, including Cenpw , Brirc5 , Cdca5 , and Cenpm . GO pathway enrichment analysis of this network has revealed that they contributed into intracellular protein transport and localization (Additional file 4 – Fig. 2 b), which are critical for cellular functioning and division. KEGG pathway enrichment and GO term analysis KEGG pathway enrichment was employed to investigate the functional implication of genes enriched in EXs. Only protein-coding genes were considered. Data showed that genes upregulated in EXs were extensively involved in DNA replication (Fig. 4 a). Other differentially enriched pathways included were related to cell cycle, splicesome, and pyrimidine metabolism (Additional file 5 – Fig. 3 ). Interestingly, regarding DNA replication, exosomal genes are components of many complexes required for DNA replication in eukaryotes. For example, among exosome-upregulated genes are five minichromosome maintenance ( Mcm ) genes that contributed significantly to the MCM complex, a DNA helicase functioning hydrogen bond between two DNA single strands. Additionally, exosomal genes encoding for protein epsilon 2, 3, and 4 are also crucial factors evolved in the DNA polymerase ε complex. Regarding the cell cycle pathway, which is essential to cell development, genes upregulated in EXs contributed to all phases of the cell cycle, such as G1, S, G2, and M. These exosomal genes are primarily associated with assembling cyclin/CDKs to control phosphorylation of target genes (Additional file 4 – Fig. 2 ). We were also interested in exosomal differential genes associated with the ECM-receptor interaction due to the ECM's extensive modulation of many mammalian biological processes relevant to skin wound healing. Notably, data indicated that numerous exosomally downregulated genes contributed to ECM interactions, namely those encoding for collagen, laminin, fibronectin, and tenascin (Fig. 4 b). Other genes, including genes coding for Vitronectin, Thrombospondin, Arginin, and Perlecan, were also associated with ECM receptors herein. These genes directly activate various classes of cellular membrane receptors, such as Integrins, Proteoglycan, Glycoprotein, Ig-SF, and other combinations. Besides, some ECM genes, such as Col2a , Col23 , and Lamc3 , were still upregulated. Our data indicate that ECM genes are not selectively sorted into EXs; however, their expression in UCMSC-EX still reflects these particles' critical role in modulating ECM interactions. We further extended our analysis to identify genes comprising the top GO terms. The top five enriched MF GO terms for differential genes are related to binding activities, such as cytoskeletal protein binding, microtubule binding, RNA binding, tubulin binding, and structural constituent of ribosome (Fig. 4 c). Top five BP GO terms for differential genes are related to cellular proliferation, such as nuclear division, organelle fission, cell division, and mitotic cell cycle (Fig. 4 d). We found over 200 genes contributing to the three most significant BP GO terms: cytoskeleton organization, mitotic cell cycle, and mitotic cell cycle process. These data reinforce that exosomal RNAs regulate cellular proliferation, relevant to injury healing. UCMSC-EXs promote the wound-healing process in vitro To address a part of the hypothesis generated from the bioinformatics analysis, we examined the capacity of EXs on the proliferation and migration of human dermal fibroblasts and keratinocytes, as well as mouse fibroblast NIH3T3, in 2D cultures. Results showed that UCMSC-EXs stimulated the proliferation of all three cell types compared to the control (Fig. 5 a). Interestingly, the EXs induced the migration of two skin cell lines, NIH3T3 and HaCaT, but not the primary human dermal fibroblasts, compared to the control (Fig. 5 b-c). These may be correlated to the data of protein-coding genes in EXs associated with the cell growth and cycle processes described in the section above. UCMSC-EX penetration into the dermis and uptake by fibroblasts Following the examination of EXs to enhance cell migration and proliferation, we further investigated the mechanism that EXs use to trigger cell behaviors using human skin models and fibroblasts in 2D cultures. Data showed that UCMSC-EXs injected into the epidermis could penetrate the dermis and disperse evenly in the dermis (Fig. 6 a & b). Observation showed that EXs were also close to the nucleus, indicating the EXs internalized into the dermis cells (Fig. 6 c). Additionally, 2D cell cultures revealed that EXs were uptaken by fibroblasts (Fig. 6 d). These data indicate that UCMSC-EXs can internalize into cells and distribute to other layers of skin. UCMSC-EXs promote the wound-healing process in vivo We further tested the capacity of UCMSC-EXs in stimulating wound healing using burned skin mouse models. The healing process was followed up to 14 days. Results showed that the animal groups treated with EXs expressed a greater healing rate than the control and PBS-treated animals after being wounded until 10 days after treatment. However, the healing rate was similar for all treated groups from day 10. Interestingly, on the 14th, wounded areas associated with EX treatment healed faster than PBS treatment, but there was no difference among the other groups (Fig. 7 b-c). These data indicate that EXs stimulate the healing process in the early period of the wound in this circumstance. Discussion Evidence has been increasing for the importance of mesenchymal stem cell-derived EXs for therapeutic purposes. Especially, EXs from UCMSCs have been shown to be involved in wound healing processes due to their potential to protect cells from oxidative stress-induced cell apoptosis in vitro 27 and promote cutaneous wound healing 28 and human skin rejuvenation 29 . Therefore, UCMSC-derived EXs are promising candidates for developing effective cutaneous wound-healing therapeutic products. Hence, in this study, we evaluated the mRNA profile in EXs released by primary human UCMSCs and the association of these molecules with wound healing processes in vitro and animal models. We first isolated UCMSC-derived EXs and demonstrated that these particles expressed typical cup-shaped morphology with a size between 40–150 nm and biomarkers of CD9, CD63, and AGO2. These were typical characteristics of EXs as described in previous reports 30 , 31 . Different molecules in EXs were reported to affect target cell functions. Focusing on skin wound healing and regeneration, several crucial growth factors essential for skin biology and healing have been reported previously 10 , 32 – 34 . Genetic materials, such as exosomal microRNAs, have also been reported to have a role in healing 35 . In this study, using RNA-seq as a proxy for transcriptome profiling, we discovered the identity of protein-encoding genes in EXs; more than 2000 genes are upregulated, indicating that these genes may be selectively sorted into EXs. Pathway enrichment reveals these genes' involvement in GO terms and KEGG pathways associated with cell growth and the cell cycle. This leads to our hypothesis that UCMSC-derived EXs play a role in wound healing. Interestingly, we detect genes that are selectively enriched in exosomes, which are conserved across cell types and biological tissues. For instance, we found Track2 to be one of the most enriched transcripts in EXs (Log 2 FC = 6.70, padj = 1.59x10 -50 ), which is similar to O'Grady et al. (2022), but the difference in the cell type of human umbilical vein endothelial cells 21 . Various mRNAs found to be enriched EXs reported by O'Grady were also reproduced in our dataset, notably Rab13 , Anp32b , and ribosomal genes such as Rpl14 and Rpl26 . Of these genes, Anp32b was also one of the most enriched genes in EXs in our dataset (Log 2 FC = 5.38, padj = 2.69x10 -21 ); this gene modulates T lymphocyte phenotype and associated immunomodulatory pathways, leading to an autoreactive state 36 . Notably, many EX-enriched genes have functions relevant to wound healing. This function is relevant to wound healing, which requires fine-tuned control of inflammation as the initial step. Genes, including Kif1c , Net1 , Map4k4 , Coro1c , Ddr2 , Mmp2 , and Zeb1 , enriched with the largest fold changes in UCMSC-derived EXs, could be potentiators of wound healing. Kif1c modulates directional cell migration - a process that is of vital importance to wound healing by stabilization of an extended and tense cell tail, facilitating persistent cell migration 37 . Kif1c is also involved in the turnover of podosome - actin-rich adhesions that enable cells to migrate 38 . Moreover, Net1 knockdown reduced the wound-healing capacity of AGS gastric cancer cells by lowering their cell migration properties 39 . Similarly, Map4k4 inhibition ameliorated the wound-healing and migratory properties of MDA-MB-231 breast cancer cells. Coro1c perturbation dampened persistent forward migration of mesenchymal cells in 1D and 3D cell culture systems by causing a loss in cell polarity 40 . Notably, the gene Ddr2 is a tyrosine kinase receptor whose phosphorylation directly drives skin fibroblasts' capacity for proliferation, migratory capacity in response to chemotactic stimuli, and secretion of key factors involved in skin wound healing, such as Mmp2 and fibrillar collagen 41 . In animal models, Ddr2 ablation directly delayed the healing of skin injuries, in conjunction with the attenuated secretion of Mmp2 , collagen type I, and crosslinking molecules that regulate the tensile strength of the skin 42 . The transcription factor Zeb1 was also upregulated in EXs. It is a well-established potentiator of wound healing across diverse tissues, including the skin and cornea, by accelerating cellular proliferation, migration, and angiogenesis 38 , 43 , 44 . All of these genes enriched in UCMSC-derived EXs confirm the above hypothesis that UCMSC-derived EXs have roles in the wound healing process. In this study, we did not observe the upregulation of ECM genes in exosomal components. The reason may be that the EXs were collected from basal conditions. If the MSCs were under stimulated conditions, such as the co-culture with the wounded fibroblast models, it could be induced by the signal molecules secreted from the target cells, as indicated in the impact of EV physiology on the characteristics of EV-producing cell transcriptomes 21 . To link the mRNA profile to the experimental cell behaviors, we examined the roles of UCMSC-derived EXs in cell proliferation and migration in vitro and in burned animal models. Similar to previous data, EXs could stimulate cell proliferation and migration in 2D cultures and heal the wound faster than the control group in burned mice 10 , 45 . The mechanism under this effectiveness may come from EXs internalized into cultured cells and penetrating into the skin and distributed around the area, as we have reported in Fig. 6 . This is important to the applicable approach regarding the real application of EXs. Furthermore, the efficacy of the healing rate may be due to the components equipped with EXs that induce regeneration at the wound site. However, the faster healing effect did not last until day 10. This may be due to the intradermal treatment of EXs only for the first three days, indicating a prolonged treatment requirement depending on the wound's severity. In conclusion, our study is the first reported mRNA profile in human UCMSC-derived EXs since the first report on exosomal mRNA profiles originated from mouse and human mast cell lines [5]. There have been several investigations on UCMSC-derived exosome miRNAs, but not yet on mRNAs. Despite this study being the pioneer study reported on the mRNAs packed into EXs and their effectiveness in promoting cell proliferation, migration, and wound closure, we have only investigated entire EXs in several wound healing processes. Further investigations are required for the association of exosomal genes with signaling pathways and their influence on other wound healing processes, such as angiogenesis, coagulation, scar formation, and the recovery level of skin structure. Materials and methods Ethical declarations Ethical approval for the use of human MSCs from the umbilical cord and dermal fibroblasts was issued by the Vinmec International General Hospital Joint Stock Company's ethics committee (Ethical approval number: 02/2022/CN-HĐĐĐ VMEC). The umbilical cord tissues were collected from three healthy donors aged 20 to 40, and skin tissues for fibroblasts were collected from women who had undergone plastic surgery. All donors signed written informed consent before donating their samples, and experimental protocols were performed in accordance with the relevant guidelines and regulations and approved by the ethics committee. For the use of animals and all experimental protocols involving animals, the study was approved by the Institutional Review Board at Dinh Tien Hoang Institute of Medicine. The Ethical approval number IRB-A 2203. We confirmed that all experiments and methods used in this study were performed in accordance with relevant regulations and the ARRIVE (Animal Research: Reporting of In Vivo Experiments) guideline. EX preparation The primary UCMSCs at passage 3 (P3) were supplied by the EV group (Vinmec Hi-Tech Center) and expanded to P5 in DMEM/F12 (Gibco, Massachusetts, USA) supplemented with 10% FBS (Gibco, Massachusetts, USA) (v/v) at 5% CO 2 and 37 o C. UCMSCs P5 were seeded with a density of 5000 cells/cm 2 in a T75 flask with EV-depleted culture media (90% DMEM/F12 and 10% EV-depleted FBS). To prepare EV-depleted FBS, FBS was centrifuged at 120,000 × g / 18 hours /4°C. After four or five days of incubation, when cells reached 80% confluency, the conditioned medium was collected and centrifuged at 300 × g / 10 minutes / 4°C to remove cell debris. Then, apoptotic bodies and microvesicles (MV) were removed using sequential centrifugations at 2,000 × g / 20 min / 4°C and 16,500 × g / 30 min / 4°C, respectively. The remaining supernatant was collected and centrifuged at 100,000 × g / 90 min / 4°C for EXs (Optima XPN-100 Ultracentrifuge, Beckman Coulter, California, USA) 10 . All EXs were resuspended in PBS and stored at − 80°C for further use. Western blot EXs were mixed with RIPA buffer (Thermo Scientific, USA) in an equivalent volume, incubated for 30 min at 4°C, and then centrifuged at 16,000 x g for 20 min at 4 o C for protein extraction. Protein concentration was determined using the Pierce ™ BCA Protein Assay Kit (Thermo Scientific, USA) and the optical densitometry method (Optical density - OD) at 560nm. A total 10–20 µg exosome proteins was loaded into each well and separated using a 4–12% NuPAGE gel (Invitrogen, USA) at 200 V for 60 min at 4°C prior to being transferred to a PVDF membrane (AmershamTM, GE Healthcare Life Science, Illinois, US) at 200 mA for 2 hours at 4°C. After that, membranes were incubated with primary antibodies diluted in TBST solution for anti-CD63 (dilution 1:200), anti-CD9 (dilution 1:100), anti-HSP70 (dilution 1:200), and anti-AGO2 (dilution 1:100) (Abcam, Cambridge, UK) overnight at 4°C. The primary antibodies were washed before incubating with secondary antibody Mouse IgG (Amersham ECL Mouse IgG, HRP-linked whole Ab, GE Healthcare Life Sciences, Pittsburgh, USA). Antibody binding was detected by ECL chemiluminescent substrate (Sigma-Aldrich, Singapore) and imaged on an ImageQuant LAS 500 (GE Healthcare Life Science, Illinois, US) 46 . Transmission electron microscopy (TEM) EXs were fixed with 4% paraformaldehyde and subsequently placed onto a carbon grid (Ted Pella Inc., California, USA). Samples were then washed before being stained and dried at room temperature. Finally, samples were examined and photographed by a Transmission Electron Microscopy JEOL 1100 (TEM, JEOL Ltd., Tokyo, Japan) at 80 kV at the National Institute of Hygiene and Epidemiology (NIHE) 46 . Exosome label, uptake, and penetration EXs were stained using the ExoGlow-Membrane EV Labeling Kit (System Biosciences, USA) according to the manufacturer's protocol. In brief, the labeling buffer and dye were mixed with 100 µg of EXs and incubated for 30 minutes at room temperature in the dark. The reaction mixture was then applied to a PD SpinTrap G-25 column (Cytiva Sweden, UK) to eliminate unbound dye and centrifuged at 800 × g for 2 minutes. The labeled EXs were collected in the first eluate 47 . EX uptake assays were conducted using human dermal fibroblasts provided by the EV group (Vinmec HiTech Center). Cells were seeded into a 96-well plate and incubated with labeled EXs. After four hours of incubation at 37°C, the medium containing excess labeled EXs was removed, and the cells were washed with PBS. Then, cells were fixed with PFA 4% for 20 minutes, followed by nuclear staining with DAPI (4′,6-diamidino-2-phenylindole) (Thermo Fisher Scientific). EX uptake was evaluated by using confocal microscopy 47 . EX penetration examinations were tested on ex vivo human skin models. The skin was cut into approximately 1 x 1 cm in length and placed on clean dishes. 100 µL of fluorescence-labeled EX solution (50 µg of exosomal protein) was injected into the epidermis (five injection sites) using a 1 mL syringe equipped with a 32G needle. Skin explants injected with fluorescence-labeled EXs were cultured for 12 hours before being fixed and stained to investigate the penetration of EXs into the dermis 48 . RNA library preparation and transcription sequencing Total RNAs from EXs and secreting UCMSCs were extracted using Trizol ™ method. Extracted RNA was quantified using Qubit RNA HS Assay Kit (Thermo Fisher, USA) to measure total RNA concentration. The optimal range for purified RNA is from 5 ng/µL to 10 ng/µL in RNase/DNase-free water. RNA integrity (RIN) was measured by the Agilent 4200 TapeStation system using High Sensi RNA ScreenTape (Agilent, USA). An amount of 50 ng total RNA was used for reverse transcription using random hexamer primers to synthesize the first cDNA strand. The second cDNA strand was synthesized by DNA polymerase using the first cDNA strand as a template. The cDNA fragments were then end-repaired and A-tailed to generate the 5' overhangs for indexing adapter ligation. The A-tailed cDNA fragments were ligated with an indexing adapter, followed by amplification with i5 and i7 indexing primers for sample multiplexing. The indexed libraries were pooled and hybridized with the Illumina exome sequencing panel (Illumina, USA). Targeted regions of interest were then captured using Streptavidin Magnetic Beads, followed by the final amplification step to achieve an enriched library. The quality of the enriched library was then assessed on Agilent 4200 TapeStation (Agilent, USA) using High-Sensitivity D1000 Tapes. The library concentration was measured by Qubit 4.0 Fluorimeter using Qubit dsDNA BR Assay Kit (Thermo Fisher, USA). The library was diluted to 4 nM using the resuspension buffer (RSB), followed by a denaturing step in the presence of NaOH 0.2 N by ratio 1:1 (v/v). The denatured library was diluted with denaturing buffer HT1 to achieve a 20 pM denatured library solution. The denatured library was then diluted to the final concentration of 1.3 pM in a total volume of 1.3 mL for sequencing. Sequencing was done on the Nextseq 500/550 system using Nextseq High Output v2.5 (300 cycles) (Illumina, USA). RNA-seq data analysis At least 9 million paired-end reads (2 x 75 base pairs or bp) were obtained for each replicate. Raw quality sequencing was assessed using FastQC v0.11.9 49 both before and after adapter trimming, and all samples passed scores on all FastQC criteria. Nextera adapter sequences, low-quality base calls (Phred score < 15), and short reads (read length < 20 base pairs) were trimmed using Trim Galore v0.6.2 50 . FASTQ paired-end reads were aligned using HISAT2 v2.2.1 51 to the human GRCh38 genome build from Ensembl 52 . The resulting BAM files were sorted by read name and chromosome position with Samtools v1.8 53 . Transcripts were quantified via the FeatureCounts function of the Bioconductor R package Rsubread v1.6.4 54 , counting non-strand-specific fragments instead of reads. MultiQC (v1.9) 55 was used to aggregate FastQC, HISAT2, and FeatureCounts results. RNA biotype classification and analysis To quantify the presence of different RNA biotypes, including long RNAs (both coding and non-coding) and short RNAs, the MGcount toolkit (v1.1.0) 56 was used using parameters suitable for unstranded paired-end reads. MGcount hierarchically assigns RNA-seq reads present to genomic annotated features in three pre-defined sequential rounds based on transcript body length: small RNA, long RNA exon, and long RNA introns, then quantifies these RNA features. An integrated GRCh38 .gtf file was used in this analysis to annotate relevant RNA features such as long RNA introns, long RNA exons, snoRNAs, and snaRNAs in the dataset if they are present. The RNA feature expression matrix from MGcount was used as input to DESeq2 for differential analysis of RNA biotype abundance between exosomes and cells, enabling the identification of features enriched in exosomes. RNA biotype distribution and differential abundance were visualized using a series of R packages, including Enhanced Volcano and ggplot2. Differential analysis Differential analysis was performed on the count matrix using R version 4.2 and the R package DESeq2 v3.15 to compare exosomes and cells from which they are excreted 20 . Data was normalized using DESeq2's built-in median-of-ratios method to account for library depth and RNA composition across samples. Genes with low counts (the sum of counts is less than 60 across all samples) were filtered, as they mostly reflect noise in the dataset.. Heatmaps were generated with the R package pheatmap (v1.0.12, available at: https://github.com/raivokolde/pheatmap ). P values were adjusted using the FDR method for multiple testing. Significantly differentially expressed genes (DEGs) were selected with an FDR < 0.05 and log 2 fold change ≥ 1 or <-1 for comparison between exosomes and cells. Volcano plots were built using the R package Enhanced Volcano (v1.16.0) 57 . Pairwise correlations and hierarchical clustering The top significant DEGs in upregulated and downregulated gene sets were filtered according to adjusted p values (adjusted p 2). Using the average agglomeration method, the distance matrix was constructed using the Pearson correlation coefficient of the logarithm of the normalized expression of DEGs in all samples. The gene-gene correlation heatmap was visualized using the heatmap.2 function of the R package gplots (version 3.1.3) 58 . Pathway enrichment analysis Significant DEGs (adjusted p-value 1) were used to identify over-represented Gene Ontology (GO) terms (GO Biological Process and Molecular Function databases) and enriched pathways annotated in the Kyoto Encyclopedia of genes and genomes (KEGG) database. Enriched pathways with p < 0.05 were considered statistically significant. Analysis and visualization of GO term overrepresentation were performed using the R package ClusterProfiler v4.4.4 59 . KEGG pathway enrichment and visualization were performed via the R package gage (v2.52.0) 60 and KEGG v1.42.0 61 . Network analysis Protein-protein interactions of the genes enriched in exosomes or part of the exosome-enriched cluster were constructed using the STRING protein database ( https://string-db.org/ ). Upregulated genes were filtered based on the following thresholds: adjusted p-value 1. Protein interactions with a confidence score of more than 0.4 were chosen, indicating moderate to strong evidence of protein interaction. The largest subnetwork was selected for further analysis to filter proteins or protein pairs with few interactions with other nodes in the network. Using default parameters, the Cytoscape plug-in Molecular Complex Detection (version 1.32) 22 was used to identify prominent subnetworks and clusters within the protein interaction network. Network clusters with an MCODE score greater than 25 were chosen to analyze upregulated genes. Proliferation Assay Human dermal fibroblasts were seeded at 2,500 cells/well of a 96-well plate and incubated in DMEM/F12 supplemented with 10% EV-depleted FBS and 10 µg EXs at 37°C and 5% CO 2 for 48 hours to proliferate. The control group consisted of cells incubated with DMEM/F12 supplemented with 10% EV-depleted FBS. The cell proliferation rate was assessed by performing a 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl tetrazolium bromide (MTT) assay (Abcam, Cambridge, UK) following the manufacturer's protocols. The proliferation rate was equivalent to the relative absorbance measured at 562 nm (SpectraMax M3, Molecular Devices, California, USA) at time points of 0 hours (as used for normalization) and 48 hours, with a higher OD value indicating a higher proliferation rate. Migration Assay Human dermal fibroblasts were seeded at 1.05 × 10 5 cells/ well of a 24-well plate at 37°C and 5% CO2 for attachment. After reaching 100% confluency, fibroblasts were incubated with Mitomycin C (10 µg/mL) for 2 hours to inhibit cell proliferation. A physical scratch was created on the cell attachment layer, and detached cells were removed by washing with media. The cells were then treated with DMEM/F12 supplemented with 10% EV-depleted FBS and 10 µg EXs, and the control cells were treated with DMEM/F12 supplemented with 10% EV-depleted FBS. Cell migration to close the wound area was captured by an inverted microscope at multiple time points. The wound area was measured using ImageJ software (version 1.48) and calculated for the closure percentage over time, representing the cell migration rate. Wound healing animal model Swiss male mice (50–60 g, 8–10 weeks old) were supplied by the Center of Experimental Animals - Vietnam Military Medical University. Mice were supplied with food and water daily in a 12-hour light/dark cycle condition. The mice were anesthetized with intraperitoneal ketamine (50 mg/mL), a 140 mg/kg body weight dosage. The dorsum of mice was shaved using an electric shaver, and the skin was disinfected with an alcohol swab. A metal plate (1.5 × 1.5 × 0.3 cm) was sterilized with 70% ethanol and then heated for 5 minutes in boiling water before being placed immediately on the skin for 10 seconds to create burned wounds. A wound would be made on the right side of the dorsum. The mice were randomly divided into three groups (n = 3 each), including group 1: non-treated, group 2: injected intradermally with 100 µL PBS, and group 3: injected intradermally with 100 µL EX solution (1 µg/1 µL). Wounded animals were immediately treated with substances as designed after creating the wounds, PBS, and exosome injections for the first three days, and all were followed up for 14 days. Mice were humanely euthanized at the end of the experiment at the Animal Center of the Military Medical Academy by the Center's technicians. The animals were euthanized using CO₂ in a specialized glass chamber. Each mouse was placed into the chamber, which was then filled with 100% compressed CO₂ at a flow rate of 30–70% of the chamber volume per minute to ensure rapid loss of consciousness and to minimize pain or distress. Each mouse was observed individually to detect cessation of breathing and corneal opacity (gradual clouding or paling of the eyes), which typically occurs after 2–3 minutes of gas exposure. CO₂ flow was maintained for at least one additional minute after respiratory arrest was confirmed. Statistical analysis N represents the number of independent replicates per group, as detailed in each figure legend. The false discovery rate (FDR) was calculated for each statistical test to correct for errors of multiple testing. The Benjamini and Hochberg (BH) method was used to compute the false discovery rate (FDR) for each statistical test. The thresholds for DEG detection were specified in the Methods section. Statistical testing was performed using built-in packages in R (version 4.2) (R Core Team, 2022) and Python (version 3.10). Data from the wet lab were presented in Mean ± SD. The student's t-test and ANOVA were used for comparisons between groups. The p-value < 0.05 was used to determine the significant difference. Abbreviations EVs Extracellular vesicles EXs Exosomes MSCs Mesenchymal stem cells UCMSCs Umbilical cord-derived mesenchymal stem cells GO Gene Ontology KEGG Kyoto encyclopedia of genes and genomes DEGs Differentially expressed genes GAGE Generally Applicable Gene-set Enrichment DMEM/F12 Dulbecco's Modified Eagle medium/Ham's F-12 FBS Fetal bovine serum MVs Microvesicles PBS Phosphate buffer saline BCA Bicinchoninic acid PVDF Polyvinylidene fluoride TBST Tris-buffered saline with Tween® 20 NTA Nanoparticle tracking analysis TEM Transmission electron microscopy FDR False discovery rate BH Benjamini and Hochbergw Declarations Acknowledgment We sincerely thank Dr. Nguyen Thi Nhan for their valuable bioinformatics analysis and review advice. Funding This project was funded by the VinIF project code VINIF.2021.DA00193. Data availability All data generated in this study are provided in the articles and available in online supplementary files. All RNA sequencing data reported in this publication have been deposited in NCBI's Gene Expression Omnibus and are accessible through the GEO accession number: GSE252017. Ethics approval and consent to participate Ethical approval for the use of human MSCs from the umbilical cord and dermal fibroblasts was issued by the Vinmec International General Hospital Joint Stock Company's ethics committee (Ethical approval number: 02/2022/CN-HĐĐĐ VMEC). The umbilical cord tissues were collected from three healthy donors aged 20 to 40, and all donors signed the written informed consent before the samples were collected. The use of animals in this present study followed guidelines for animal treatment and complied with the relevant legislation from the Institutional Review Board at Dinh Tien Hoang Institute of Medicine (Ethical approval number: IRB-A 2203). Consent for publication Not applicable. Competing interests The authors declare that they have no competing interests. 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Supplementary Files Westernblotfullgel.pdf Supplementaryfile1Fig.1.docx Supplementaryfile2Table1.docx Supplementaryfile3Table2.docx Supplementaryfile4Fig.2.docx Supplementaryfile5Fig.3.docx Cite Share Download PDF Status: Published Journal Publication published 21 Mar, 2026 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 04 Feb, 2026 Reviewers agreed at journal 30 Jan, 2026 Reviews received at journal 28 Jan, 2026 Reviewers agreed at journal 25 Jan, 2026 Reviewers agreed at journal 25 Jan, 2026 Reviewers agreed at journal 24 Jan, 2026 Reviews received at journal 21 Jan, 2026 Reviewers agreed at journal 14 Jan, 2026 Reviewers invited by journal 14 Jan, 2026 Editor invited by journal 30 Dec, 2025 Editor assigned by journal 29 Dec, 2025 Submission checks completed at journal 26 Dec, 2025 First submitted to journal 26 Dec, 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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18:03:47","extension":"xml","order_by":23,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":151075,"visible":true,"origin":"","legend":"","description":"","filename":"f4587e74020b45df860e07721c80d3f51structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-8130672/v1/d88d53c55220a320a2cb9343.xml"},{"id":100618391,"identity":"d05a8a55-1135-4162-a342-ff573b2fc901","added_by":"auto","created_at":"2026-01-19 18:01:51","extension":"html","order_by":24,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":168859,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8130672/v1/9a9d291eb329663a17497a55.html"},{"id":100618914,"identity":"e1487101-ea0c-493e-99e3-d5759a7dec0e","added_by":"auto","created_at":"2026-01-19 18:04:21","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":350366,"visible":true,"origin":"","legend":"\u003cp\u003eCharacteristics of exosomes derived from UCMSCs. \u003cstrong\u003ea\u003c/strong\u003e Size distribution of exosomes that the majority of exosomes are around 100 nm. \u003cstrong\u003eb\u003c/strong\u003e Exosomes expressed a cup-shaped morphology and smooth surface; \u003cstrong\u003ec\u003c/strong\u003eExosomal marker expression, that exosomes were detected with CD9, CD63, HSP70, and AGO2. Three separate exosome samples were analyzed: EX1, EX2, and EX3, respectively.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8130672/v1/a681fb48863689e664bbb8cf.png"},{"id":100796165,"identity":"b3f74e53-9505-488d-9df3-cfe4c7678066","added_by":"auto","created_at":"2026-01-21 13:41:10","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":364032,"visible":true,"origin":"","legend":"\u003cp\u003emRNA biotype distribution and volcano plot indicated the notable genes detected in all samples. \u003cstrong\u003ea-b\u003c/strong\u003e The number of assigned reads belonging to each RNA subtype detected in UCMSC-derived exosomes. These include essential genes upregulated in UCMSC-derived exosomes associated with wound healing. Volcano plot shows the log2FC versus -log10(P-value) of all RNA biotypes. \u003cstrong\u003ec\u003c/strong\u003e Heatmap showcased top differential genes, a diagram depicting the overall approach.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8130672/v1/b33b9f26a0e312b775874971.png"},{"id":100618671,"identity":"9bec870a-6c88-4b93-ae9c-4751eb457db8","added_by":"auto","created_at":"2026-01-19 18:03:32","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":249689,"visible":true,"origin":"","legend":"\u003cp\u003eString analysis showed the interaction network of proteins encoded by genes upregulated in exosomes. \u003cstrong\u003ea-b\u003c/strong\u003e Two major networks were generated by String, where the gene \u003cem\u003eMCM3\u003c/em\u003e is a central hub within network A, and network B comprises connections to proteins associated with mitochondria and ATP synthase complex. \u003cstrong\u003ec-d\u003c/strong\u003eclusters of protein interactions deconvolved using MCODE from networks A and B.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-8130672/v1/c58799dc1456dd7256240029.png"},{"id":100618476,"identity":"1702f6ec-d576-46e3-b03b-6d9d7333efa5","added_by":"auto","created_at":"2026-01-19 18:02:04","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":389850,"visible":true,"origin":"","legend":"\u003cp\u003eKEGG pathway and GO term analysis genes detected in exosomes, with \u003cstrong\u003ea\u003c/strong\u003e the involvement of upregulated exosomal genes in DNA replication pathway; \u003cstrong\u003eb\u003c/strong\u003e the involvement of downregulated exosomal genes in ECM-receptor interaction pathway; \u003cstrong\u003ec\u003c/strong\u003etop five MF GO terms and \u003cstrong\u003ed\u003c/strong\u003e top five BP GO terms were revealed using the Cytoscape plug-in Molecular Complex Detection.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-8130672/v1/fae11edac3687aebb33a1b52.png"},{"id":100618696,"identity":"dabe0c31-440c-466e-9b0b-a72199428403","added_by":"auto","created_at":"2026-01-19 18:03:38","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":322321,"visible":true,"origin":"","legend":"\u003cp\u003eEffect of EXs in wound healing \u003cem\u003ein vitro\u003c/em\u003e. \u003cstrong\u003ea\u003c/strong\u003e Capacity of EXs to stimulate dermal human fibroblast, NIH3T3, and HaCaT proliferation. \u003cstrong\u003eb\u003c/strong\u003e The image of cell migration followed the time of observation. \u003cstrong\u003ec\u003c/strong\u003e The quantification of wound closure rate (%). Scale bar: 50 µm.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-8130672/v1/999d9833147dd90b8c3219ff.png"},{"id":100618687,"identity":"cb929f50-9672-449b-a3ec-ed1f55160319","added_by":"auto","created_at":"2026-01-19 18:03:35","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":187480,"visible":true,"origin":"","legend":"\u003cp\u003eThe capacity of UCMSC-derived EXs penetrated into the dermis and were up-taken by cells. \u003cstrong\u003ea, b, \u003c/strong\u003e\u0026amp;\u003cstrong\u003e c \u003c/strong\u003eThe penetration of UCMSC-derived EXs into the dermis in the human skin model ex vivo after 12 hours. \u003cstrong\u003ed\u003c/strong\u003e UCMSC-derived EXs were up-taken by fibroblasts in 2D cell cultures after 0.5 hours.\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-8130672/v1/584faed971979eebec1fb137.png"},{"id":100618140,"identity":"9cef026d-079d-4919-88d0-9d28cf048fdd","added_by":"auto","created_at":"2026-01-19 18:00:24","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":261663,"visible":true,"origin":"","legend":"\u003cp\u003eEffect of EXs in wound healing \u003cem\u003ein vivo\u003c/em\u003e. \u003cstrong\u003ea\u003c/strong\u003eImages of the burned site on mice in different groups: control, PBS, and EX treatment. \u003cstrong\u003eb\u003c/strong\u003e Burned animal models indicate that EXs have effects on stimulating the wound closing faster in the early days after wounded skin. This efficacy decreased from day ten onward. Control: no treatment; PBS: burned animal models treated with PBS; EX: burned animal models treated with exosomes. Results were averages of 3 biological samples (n = 3). Statistical significance was determined by Two-Way ANOVA and indicated by *** where \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001. Error bars indicate ± SD.\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-8130672/v1/29f8047706897f33b2488719.png"},{"id":105223694,"identity":"72717d56-8b55-4639-944a-b144099bd3b5","added_by":"auto","created_at":"2026-03-23 16:09:09","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3392062,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8130672/v1/a08180f9-14cd-48f0-a57e-a25f3d1f0cf7.pdf"},{"id":100618928,"identity":"0343daf1-7954-4e64-9d18-69d529394a3f","added_by":"auto","created_at":"2026-01-19 18:04:29","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":166748,"visible":true,"origin":"","legend":"","description":"","filename":"Westernblotfullgel.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8130672/v1/8bda9c87c26295c07bc10eec.pdf"},{"id":100618663,"identity":"4b866b68-8b86-4692-93d2-fa70004f2838","added_by":"auto","created_at":"2026-01-19 18:03:28","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":754286,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementaryfile1Fig.1.docx","url":"https://assets-eu.researchsquare.com/files/rs-8130672/v1/0d4727f612236be744cbff31.docx"},{"id":100618603,"identity":"a35e6294-6663-4342-a396-4cabb371704c","added_by":"auto","created_at":"2026-01-19 18:02:49","extension":"docx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":14370,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementaryfile2Table1.docx","url":"https://assets-eu.researchsquare.com/files/rs-8130672/v1/a04b20008984f88592b71daa.docx"},{"id":100618582,"identity":"2cc048fa-053b-4e1d-a695-576edfa7a871","added_by":"auto","created_at":"2026-01-19 18:02:41","extension":"docx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":14060,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementaryfile3Table2.docx","url":"https://assets-eu.researchsquare.com/files/rs-8130672/v1/d3657c18aafb7ea010dca758.docx"},{"id":100618699,"identity":"fc98426c-9976-4c6d-96bd-55460ef952ee","added_by":"auto","created_at":"2026-01-19 18:03:41","extension":"docx","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":307016,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementaryfile4Fig.2.docx","url":"https://assets-eu.researchsquare.com/files/rs-8130672/v1/7f6a80394cc7ee88d8a2a806.docx"},{"id":100618700,"identity":"b21c5d1c-09de-4182-b101-313472cb4637","added_by":"auto","created_at":"2026-01-19 18:03:42","extension":"docx","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":743199,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementaryfile5Fig.3.docx","url":"https://assets-eu.researchsquare.com/files/rs-8130672/v1/0864f575fe2c65e8279ad10f.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"mRNA profiling of mesenchymal stem cell-derived exosomes reveals their function in accelerating wound healing","fulltext":[{"header":"Introduction","content":"\u003cp\u003eExosomes (EXs) or small vesicles, a specific subtype of extracellular vesicles (EVs), are nanosized particles with diameters ranging from 30 to 150 nm \u003csup\u003e1\u003c/sup\u003e. They are secreted by virtually all cell types and could be obtained from conditioned media during cell culture \u003cem\u003ein vitro\u003c/em\u003e and different biological fluids such as blood, urine, saliva, amniotic fluid, and breast milk \u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e,\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. The intravesicular contents of EVs display considerable diversity, which depends on their cellular origin, physiological state, and sorting mechanisms \u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e; thus, EXs are packed with bioactive molecules, including proteins (tetraspanins, heat-shock proteins), nucleic acids (RNAs, microRNAs), and lipids (ceramides, cholesterol, sphingolipids) \u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. According to the latest update of ExoCarta, 13476 proteins, 3408 mRNAs, 10755 miRNAs, and 3946 lipid entries have been detected in exosomes (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.exocarta.org/\u003c/span\u003e\u003cspan address=\"http://www.exocarta.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e, accessed 29/06/2025). Given the remarkable diversity in EX compositions linked to diverse cellular provenance, comprehensive omic-level profiling of these particles is of significant value. Such investigations hold the potential to unveil mechanisms and therapeutic targets worthy of further exploration and development.\u003c/p\u003e \u003cp\u003eIn recent years, investigations have confirmed that mesenchymal stem cells (MSCs)-derived EXs possess a wide range of therapeutic capabilities across diverse conditions, including cardiovascular and renal protection, stroke, perinatal hypoxic-ischemic brain injury, hind-limb ischemia, immune-related diseases, cancer, wound healing, and even COVID-19 \u003csup\u003e8,9\u003c/sup\u003e. EXs derived from MSCs of varying origins or exposed to distinct external stimuli exhibit markedly different compositions of functional molecules and heterogeneous characteristics, consequently manifesting divergent therapeutic properties \u003csup\u003e\u003cspan additionalcitationids=\"CR10\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. For example, bone marrow MSC-derived EXs have pronounced regeneration capacity through the induction of angiogenesis, adipose tissue MSC-derived exosomes show the most influential secretory activity and immunomodulation compared with MSCs derived from other sources, and UCMSC-derived EXs primarily participate in tissue repair \u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. Additionally, EXs have a significant impact on skin regeneration through modulating cell behaviors and functions of immune cells, fibroblasts, and endothelial cells, regulating inflammation and immune microenvironment, and promoting collagen deposition and angiogenesis by enabling intercellular crosstalk \u003csup\u003e\u003cspan additionalcitationids=\"CR14 CR15\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. However, the mechanistic understanding of how EXs elicit their biological effects remains incomplete. While much of the focus has been on either EXs' broad interaction with cellular targets or protein-level characterisation of EXs' cargo, little emphasis has been placed on EXs' transcriptome.\u003c/p\u003e \u003cp\u003eVarious groups have reported the presence of mRNA in EXs, as reviewed elsewhere \u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. However, the properties and functions of coding RNAs remain largely unexplored \u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e,\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e, which may strengthen the mechanistic understanding behind EXs' properties, such as wound healing. In this study, we investigated mRNA transcripts in UCMSC-derived EXs and simultaneously examined the wound healing capability of these EXs in both \u003cem\u003ein vitro\u003c/em\u003e and \u003cem\u003ein vivo\u003c/em\u003e models.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eExosome characterization\u003c/h2\u003e \u003cp\u003eWe used differential centrifugation to isolate exosomes (EXs) from conditioned media of UCMSCs at P5. This population was examined for size distribution using the NTA technique and showed that the size distribution of EXs ranged from 40 nm to 350 nm, with the highest peak at 100 nm (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea). Results from TEM imaging showed that a quite homologous cup-shaped morphology and smooth surface of EXs have been observed under TEM (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb). Additionally, immunohistological analysis showed that exosomal markers of CD9, CD63, HSP70, and AGO2 have been detected in exosome fraction (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ec). The size of EXs analyzed using the NTA is consistent with the size observed under TEM, around 100 nm.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eProtein-coding RNAs are differentially enriched in exosomes, and many are associated with wound-healing\u003c/h3\u003e\n\u003cp\u003eIn order to characterize the RNAs contained within EVs released from UCMSCs and secreting cells, an RNA sequencing approach was performed using the Nextseq 500/550 system (Illumina, USA). Statistics for alignment to the human HG38 genome and the proportion of uniquely mapped reads are shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. More than 4\u0026nbsp;million uniquely mapped reads were obtained for all samples. The alignment rate was around 90% \u0026minus;\u0026thinsp;91% (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eRead mapping, alignment, and feature-counting statistics\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCategory\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStatistic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eExosome 1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eExosome 2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eExosome 3\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eUCMSC1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eUCMSC2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eUCMSC3\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSequence counts\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAverage number of uniquely mapped reads\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4,173,608\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5,111,878\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4,518,578\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5,167,534\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e8,615,614\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e8,097,777\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAverage number of duplicated reads\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5,250,685\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7,443,151\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4,478,099\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5,610,149\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e11,512,273\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e12,144,406\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAlignment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal pair of reads\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9,424,293\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12,555,029\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8,996,677\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10,777,683\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e20,127,887\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e20,242,183\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAlignment rate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e89.90%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e89.85%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e90.23%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e90.25%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e90.70%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e91.38%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eMapping reads to features\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal alignments\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12,783,855\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15,408,981\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11,788,975\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e13,432,806\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e23,036,659\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e22,990,238\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSuccessful assignment rate of reads to features\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e66.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e74.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e67.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e70.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e78.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e81.2%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eWe first investigated the different biotypes of RNAs present in EXs. Results showed that the MGcound toolkit annotated relevant RNA features such as long RNA introns, long RNA exons, snoRNAs, and snaRNAs in the dataset (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea-b). Regarding small non-coding RNAs, it was highlighted that SNORA49, RMRP-202, and SCARNA7 are downregulated in EXs, but RN7SL471P is upregulated in EXs. We observed a notable enrichment of various endogenous non-coding RNAs belonging to the RN7SL family, which encodes the signal recognition particle complex. Additionally, we found that our approach mainly captured protein-coding mRNAs in EXs (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTo assess which coding transcripts were preferentially exported to EXs or retained in mother cells, using the R package DESeq2 \u003csup\u003e20\u003c/sup\u003e, a differential analysis was performed to evaluate coding RNA abundances across UCMSCs and the EXs they secrete. Using a threshold of adjusted p-value\u0026thinsp;=\u0026thinsp;0.05 and |Log2(Fold Change)| greater than 1, about 4578 genes were differentially expressed in UCMSC-derived EXs (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec, Additional file 1 \u0026ndash; Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Among them, 2574 genes were downregulated, and 2004 genes were upregulated in UCMSC-derived EXs (padj\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb-c). Genes in clusters identified through hierarchical clustering of top-upregulated genes in UCMSC-EXs could be found in the Additional file 2 \u0026ndash; Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eNotably, the most enriched transcripts in EXs included \u003cem\u003eNet 1\u003c/em\u003e (Log\u003csub\u003e2\u003c/sub\u003eFC\u0026thinsp;=\u0026thinsp;7.03, padj\u0026thinsp;=\u0026thinsp;1.50 \u0026times; 10\u003csup\u003e\u0026ndash;31\u003c/sup\u003e), \u003cem\u003eTrack2\u003c/em\u003e (Log\u003csub\u003e2\u003c/sub\u003eFC\u0026thinsp;=\u0026thinsp;6.70, padj\u0026thinsp;=\u0026thinsp;1.59 \u0026times; 10\u003csup\u003e\u0026ndash;50\u003c/sup\u003e), \u003cem\u003eRab13\u003c/em\u003e (Log\u003csub\u003e2\u003c/sub\u003eFC\u0026thinsp;=\u0026thinsp;6.44, padj\u0026thinsp;=\u0026thinsp;9.7 \u0026times; 10\u003csup\u003e\u0026ndash;14\u003c/sup\u003e), and \u003cem\u003eKif1c\u003c/em\u003e (Log\u003csub\u003e2\u003c/sub\u003eFC\u0026thinsp;=\u0026thinsp;6.26, padj\u0026thinsp;=\u0026thinsp;4.53 \u0026times; 10\u003csup\u003e\u0026ndash;34\u003c/sup\u003e). Interestingly, \u003cem\u003eAnp32b\u003c/em\u003e (Log\u003csub\u003e2\u003c/sub\u003eFC\u0026thinsp;=\u0026thinsp;5.38, padj\u0026thinsp;=\u0026thinsp;2.69 \u0026times; 10\u003csup\u003e\u0026ndash;21\u003c/sup\u003e), which harbors immune functions, and \u003cem\u003eDgf11\u003c/em\u003e (Log\u003csub\u003e2\u003c/sub\u003eFC\u0026thinsp;=\u0026thinsp;5.45, padj\u0026thinsp;=\u0026thinsp;3.02 \u0026times; 10\u003csup\u003e\u0026ndash;33\u003c/sup\u003e), which has multiple effects on cell development and physiology, were also one of the most enriched genes in EXs in our dataset. Interestingly, these genes are reported to be highly enriched in human umbilical cord vein endothelial cell-derived EXs. Therefore, our result strongly reproduced previous findings in EXs derived from endothelial cells \u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e, indicating perhaps the existence of conserved exosome mRNA markers.\u003c/p\u003e \u003cp\u003eIn relation to wound healing, we found that many genes with the most significant magnitude of enrichment in EXs (evidenced by read counts and fold enrichment) are established potentiators of wound healing (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb). These genes play diverse but relevant roles in the physiological wound-healing response. Of those, \u003cem\u003eKif1c\u003c/em\u003e, \u003cem\u003eNet1\u003c/em\u003e, \u003cem\u003eMap4k4\u003c/em\u003e, and \u003cem\u003eCoro1c\u003c/em\u003e are applicable due to their involvement in regulating cellular migration during wound healing.\u003c/p\u003e \u003cp\u003eOther relevant genes included Discoidin domain receptor 2 (\u003cem\u003eDdr2\u003c/em\u003e), \u003cem\u003eMmp2\u003c/em\u003e, and zinc finger E-box binding homeobox 1 (\u003cem\u003eZeb1\u003c/em\u003e). The data of many protein-coding mRNAs upregulated in EXs are associated with wound healing, indicating that UCMSC-derived EXs may play an essential role in the cutaneous healing process.\u003c/p\u003e \u003cp\u003e \u003cb\u003eNetwork analysis and hierarchical clustering description indicated RNAs enriched in exosomes involved in the wound healing process\u003c/b\u003e \u003c/p\u003e \u003cp\u003eWe performed a two-pronged approach to investigate the gene modules representing higher-level biological processes that are enriched within the community of coding RNAs in UCMSC-derived EXs. First, we constructed a protein interaction network for all genes contained within EXs and deconvolved network structures into clusters of highly interconnected nodes to define notable network structures that may underpin biological functions. In parallel, hierarchical clustering was performed to examine the pairwise correlations of genes strongly enriched in UCMSC-EXs. Pearson correlation coefficient was used to construct the distance matrix, with average as the agglomeration method. The goal was to identify clusters of highly correlated genes, suggesting a specific biological function enriched within EXs. The STRING protein interaction database was then used to map interactions between gene-encoded proteins contained within the cluster. Our rationale is that by combining two layers of evidence characterizing gene-gene association (by measuring the Pearson correlation coefficient), and protein interactions (by using the STRING database), we can comprehensively unveil emergent biological properties that may otherwise be missed.\u003c/p\u003e \u003cp\u003eFor the first approach, after mapping exhaustive protein interactions between exosome-enriched genes, we used MCODE to deconvolve the network into significant clusters \u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. Two major networks were identified using a threshold score of 25 (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea-b, Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, Supplemental Additional file 3 \u0026ndash; Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eNetwork analysis statistics of clusters 1 and 2 - the two most significant clusters of protein interaction identified from exosome-enriched genes\u003csup\u003e*\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCluster 1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCluster 2\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of nodes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e55\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of edges\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9154\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e797\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNetwork density\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.460\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.537\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNetwork centralization\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.155\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.308\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003csup\u003e*\u003c/sup\u003e \u003cem\u003eGene list contributed in clusters 1 and 2 could be found in Supplemental Additional file 3 \u0026ndash;\u003c/em\u003e Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eRegarding the first network, the gene \u003cem\u003eMcm3\u003c/em\u003e is a central hub within this network, with connections to 200 nodes in the network (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea). \u003cem\u003eMcm3\u003c/em\u003e promotes cellular proliferation and restricts apoptosis in many models and carcinoma cell types \u003csup\u003e\u003cspan additionalcitationids=\"CR24\" citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e, and thus might be a central regulator of wound healing. \u003cem\u003eMcm3\u003c/em\u003e's ability to direct cell proliferation is related to its ability to regulate DNA replication. \u003cem\u003eMcm3\u003c/em\u003e is indispensable for initiating eukaryotic genome replication and is required to ensure that DNA replication is initiated precisely once per cell cycle. The second clusters include genes associated with mitochondria, many of which are subtypes of mitochondrial complex 1: NADH: ubiquinone oxidoreductase supernumerary subunits (\u003cem\u003eNduf\u003c/em\u003e) such as \u003cem\u003eNdufs5\u003c/em\u003e, \u003cem\u003eNdufs8\u003c/em\u003e, \u003cem\u003eNdufb2\u003c/em\u003e, \u003cem\u003eNdufb6\u003c/em\u003e, and \u003cem\u003eNdufb10\u003c/em\u003e. Many other members of this cluster are subunits of the mitochondrial ATP synthase (\u003cem\u003eAtp5j2\u003c/em\u003e, \u003cem\u003eAtp5o\u003c/em\u003e, \u003cem\u003eAtp5e\u003c/em\u003e, \u003cem\u003eAtp5g1\u003c/em\u003e, and \u003cem\u003eAtp5g3\u003c/em\u003e) that have a role in driving the synthesis of ATP with the presence of a proton gradient, allowing cells to efficiently utilize the energy generated during electron transport \u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. Also, parts of this cluster are eight genes encoding mitochondrial and cellular ribosomal proteins that are part of the MRP and RPL protein families. Altogether, this cluster likely underlies major structural constituents of the mitochondrial ribosome and ATPase, which are essential for energy and protein regulation.\u003c/p\u003e \u003cp\u003eFor the second approach, following hierarchical clustering, two significant clusters consisting of strongly correlated gene features were identified (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ec-d). To understand the biological processes governed by genes contained within these clusters, using the STRING protein interaction databases, we further identified the interconnected network motif (cluster) of protein interactions using MCODE. In cluster 1, genes in the MCODE-identified network are extensively documented to be involved in processes related to wound healing, notably cell migration and growth: \u003cem\u003eSka3\u003c/em\u003e, \u003cem\u003eCenpu\u003c/em\u003e, and \u003cem\u003eCks1b\u003c/em\u003e. Pathway analysis of clusters revealed the enrichment of GO processes related to organ development and inflammation, which are all key to wound healing (Additional file 4 \u0026ndash; Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea). Regarding cluster 2, this network underpins mitotic cell division and cell cycle control, including \u003cem\u003eCenpw\u003c/em\u003e, \u003cem\u003eBrirc5\u003c/em\u003e, \u003cem\u003eCdca5\u003c/em\u003e, and \u003cem\u003eCenpm\u003c/em\u003e. GO pathway enrichment analysis of this network has revealed that they contributed into intracellular protein transport and localization (Additional file 4 \u0026ndash; Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb), which are critical for cellular functioning and division.\u003c/p\u003e\n\u003ch3\u003eKEGG pathway enrichment and GO term analysis\u003c/h3\u003e\n\u003cp\u003eKEGG pathway enrichment was employed to investigate the functional implication of genes enriched in EXs. Only protein-coding genes were considered. Data showed that genes upregulated in EXs were extensively involved in DNA replication (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea). Other differentially enriched pathways included were related to cell cycle, splicesome, and pyrimidine metabolism (Additional file 5 \u0026ndash; Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Interestingly, regarding DNA replication, exosomal genes are components of many complexes required for DNA replication in eukaryotes. For example, among exosome-upregulated genes are five minichromosome maintenance (\u003cem\u003eMcm\u003c/em\u003e) genes that contributed significantly to the MCM complex, a DNA helicase functioning hydrogen bond between two DNA single strands. Additionally, exosomal genes encoding for protein epsilon 2, 3, and 4 are also crucial factors evolved in the DNA polymerase ε complex. Regarding the cell cycle pathway, which is essential to cell development, genes upregulated in EXs contributed to all phases of the cell cycle, such as G1, S, G2, and M. These exosomal genes are primarily associated with assembling cyclin/CDKs to control phosphorylation of target genes (Additional file 4 \u0026ndash; Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eWe were also interested in exosomal differential genes associated with the ECM-receptor interaction due to the ECM's extensive modulation of many mammalian biological processes relevant to skin wound healing. Notably, data indicated that numerous exosomally downregulated genes contributed to ECM interactions, namely those encoding for collagen, laminin, fibronectin, and tenascin (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eb). Other genes, including genes coding for Vitronectin, Thrombospondin, Arginin, and Perlecan, were also associated with ECM receptors herein. These genes directly activate various classes of cellular membrane receptors, such as Integrins, Proteoglycan, Glycoprotein, Ig-SF, and other combinations. Besides, some ECM genes, such as \u003cem\u003eCol2a\u003c/em\u003e, \u003cem\u003eCol23\u003c/em\u003e, and \u003cem\u003eLamc3\u003c/em\u003e, were still upregulated. Our data indicate that ECM genes are not selectively sorted into EXs; however, their expression in UCMSC-EX still reflects these particles' critical role in modulating ECM interactions.\u003c/p\u003e \u003cp\u003eWe further extended our analysis to identify genes comprising the top GO terms. The top five enriched MF GO terms for differential genes are related to binding activities, such as cytoskeletal protein binding, microtubule binding, RNA binding, tubulin binding, and structural constituent of ribosome (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ec). Top five BP GO terms for differential genes are related to cellular proliferation, such as nuclear division, organelle fission, cell division, and mitotic cell cycle (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ed). We found over 200 genes contributing to the three most significant BP GO terms: cytoskeleton organization, mitotic cell cycle, and mitotic cell cycle process. These data reinforce that exosomal RNAs regulate cellular proliferation, relevant to injury healing.\u003c/p\u003e \u003cp\u003e \u003cb\u003eUCMSC-EXs promote the wound-healing process\u003c/b\u003e \u003cb\u003ein vitro\u003c/b\u003e\u003c/p\u003e \u003cp\u003eTo address a part of the hypothesis generated from the bioinformatics analysis, we examined the capacity of EXs on the proliferation and migration of human dermal fibroblasts and keratinocytes, as well as mouse fibroblast NIH3T3, in 2D cultures. Results showed that UCMSC-EXs stimulated the proliferation of all three cell types compared to the control (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ea). Interestingly, the EXs induced the migration of two skin cell lines, NIH3T3 and HaCaT, but not the primary human dermal fibroblasts, compared to the control (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eb-c). These may be correlated to the data of protein-coding genes in EXs associated with the cell growth and cycle processes described in the section above.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\n\u003ch3\u003eUCMSC-EX penetration into the dermis and uptake by fibroblasts\u003c/h3\u003e\n\u003cp\u003eFollowing the examination of EXs to enhance cell migration and proliferation, we further investigated the mechanism that EXs use to trigger cell behaviors using human skin models and fibroblasts in 2D cultures. Data showed that UCMSC-EXs injected into the epidermis could penetrate the dermis and disperse evenly in the dermis (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ea \u0026amp; b). Observation showed that EXs were also close to the nucleus, indicating the EXs internalized into the dermis cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ec). Additionally, 2D cell cultures revealed that EXs were uptaken by fibroblasts (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ed). These data indicate that UCMSC-EXs can internalize into cells and distribute to other layers of skin.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eUCMSC-EXs promote the wound-healing process\u003c/b\u003e \u003cb\u003ein vivo\u003c/b\u003e\u003c/p\u003e \u003cp\u003eWe further tested the capacity of UCMSC-EXs in stimulating wound healing using burned skin mouse models. The healing process was followed up to 14 days. Results showed that the animal groups treated with EXs expressed a greater healing rate than the control and PBS-treated animals after being wounded until 10 days after treatment. However, the healing rate was similar for all treated groups from day 10. Interestingly, on the 14th, wounded areas associated with EX treatment healed faster than PBS treatment, but there was no difference among the other groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eb-c). These data indicate that EXs stimulate the healing process in the early period of the wound in this circumstance.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eEvidence has been increasing for the importance of mesenchymal stem cell-derived EXs for therapeutic purposes. Especially, EXs from UCMSCs have been shown to be involved in wound healing processes due to their potential to protect cells from oxidative stress-induced cell apoptosis \u003cem\u003ein vitro\u003c/em\u003e \u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e and promote cutaneous wound healing \u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e and human skin rejuvenation \u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. Therefore, UCMSC-derived EXs are promising candidates for developing effective cutaneous wound-healing therapeutic products. Hence, in this study, we evaluated the mRNA profile in EXs released by primary human UCMSCs and the association of these molecules with wound healing processes \u003cem\u003ein vitro\u003c/em\u003e and animal models. We first isolated UCMSC-derived EXs and demonstrated that these particles expressed typical cup-shaped morphology with a size between 40\u0026ndash;150 nm and biomarkers of CD9, CD63, and AGO2. These were typical characteristics of EXs as described in previous reports \u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e,\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eDifferent molecules in EXs were reported to affect target cell functions. Focusing on skin wound healing and regeneration, several crucial growth factors essential for skin biology and healing have been reported previously \u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e,\u003cspan additionalcitationids=\"CR33\" citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e. Genetic materials, such as exosomal microRNAs, have also been reported to have a role in healing \u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e. In this study, using RNA-seq as a proxy for transcriptome profiling, we discovered the identity of protein-encoding genes in EXs; more than 2000 genes are upregulated, indicating that these genes may be selectively sorted into EXs. Pathway enrichment reveals these genes' involvement in GO terms and KEGG pathways associated with cell growth and the cell cycle. This leads to our hypothesis that UCMSC-derived EXs play a role in wound healing.\u003c/p\u003e \u003cp\u003eInterestingly, we detect genes that are selectively enriched in exosomes, which are conserved across cell types and biological tissues. For instance, we found \u003cem\u003eTrack2\u003c/em\u003e to be one of the most enriched transcripts in EXs (Log\u003csub\u003e2\u003c/sub\u003eFC\u0026thinsp;=\u0026thinsp;6.70, padj\u0026thinsp;=\u0026thinsp;1.59x10\u003csup\u003e-50\u003c/sup\u003e), which is similar to O'Grady et al. (2022), but the difference in the cell type of human umbilical vein endothelial cells \u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. Various mRNAs found to be enriched EXs reported by O'Grady were also reproduced in our dataset, notably \u003cem\u003eRab13\u003c/em\u003e, \u003cem\u003eAnp32b\u003c/em\u003e, and ribosomal genes such as \u003cem\u003eRpl14\u003c/em\u003e and \u003cem\u003eRpl26\u003c/em\u003e. Of these genes, \u003cem\u003eAnp32b\u003c/em\u003e was also one of the most enriched genes in EXs in our dataset (Log\u003csub\u003e2\u003c/sub\u003eFC\u0026thinsp;=\u0026thinsp;5.38, padj\u0026thinsp;=\u0026thinsp;2.69x10\u003csup\u003e-21\u003c/sup\u003e); this gene modulates T lymphocyte phenotype and associated immunomodulatory pathways, leading to an autoreactive state \u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e. Notably, many EX-enriched genes have functions relevant to wound healing. This function is relevant to wound healing, which requires fine-tuned control of inflammation as the initial step. Genes, including \u003cem\u003eKif1c\u003c/em\u003e, \u003cem\u003eNet1\u003c/em\u003e, \u003cem\u003eMap4k4\u003c/em\u003e, \u003cem\u003eCoro1c\u003c/em\u003e, \u003cem\u003eDdr2\u003c/em\u003e, \u003cem\u003eMmp2\u003c/em\u003e, and \u003cem\u003eZeb1\u003c/em\u003e, enriched with the largest fold changes in UCMSC-derived EXs, could be potentiators of wound healing. \u003cem\u003eKif1c\u003c/em\u003e modulates directional cell migration - a process that is of vital importance to wound healing by stabilization of an extended and tense cell tail, facilitating persistent cell migration \u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e. \u003cem\u003eKif1c\u003c/em\u003e is also involved in the turnover of podosome - actin-rich adhesions that enable cells to migrate \u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e. Moreover, \u003cem\u003eNet1\u003c/em\u003e knockdown reduced the wound-healing capacity of AGS gastric cancer cells by lowering their cell migration properties \u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e. Similarly, \u003cem\u003eMap4k4\u003c/em\u003e inhibition ameliorated the wound-healing and migratory properties of MDA-MB-231 breast cancer cells. \u003cem\u003eCoro1c\u003c/em\u003e perturbation dampened persistent forward migration of mesenchymal cells in 1D and 3D cell culture systems by causing a loss in cell polarity \u003csup\u003e\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e. Notably, the gene \u003cem\u003eDdr2\u003c/em\u003e is a tyrosine kinase receptor whose phosphorylation directly drives skin fibroblasts' capacity for proliferation, migratory capacity in response to chemotactic stimuli, and secretion of key factors involved in skin wound healing, such as \u003cem\u003eMmp2\u003c/em\u003e and fibrillar collagen \u003csup\u003e\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e. In animal models, \u003cem\u003eDdr2\u003c/em\u003e ablation directly delayed the healing of skin injuries, in conjunction with the attenuated secretion of \u003cem\u003eMmp2\u003c/em\u003e, collagen type I, and crosslinking molecules that regulate the tensile strength of the skin \u003csup\u003e\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e. The transcription factor \u003cem\u003eZeb1\u003c/em\u003e was also upregulated in EXs. It is a well-established potentiator of wound healing across diverse tissues, including the skin and cornea, by accelerating cellular proliferation, migration, and angiogenesis \u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e,\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e,\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e. All of these genes enriched in UCMSC-derived EXs confirm the above hypothesis that UCMSC-derived EXs have roles in the wound healing process.\u003c/p\u003e \u003cp\u003eIn this study, we did not observe the upregulation of ECM genes in exosomal components. The reason may be that the EXs were collected from basal conditions. If the MSCs were under stimulated conditions, such as the co-culture with the wounded fibroblast models, it could be induced by the signal molecules secreted from the target cells, as indicated in the impact of EV physiology on the characteristics of EV-producing cell transcriptomes \u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eTo link the mRNA profile to the experimental cell behaviors, we examined the roles of UCMSC-derived EXs in cell proliferation and migration \u003cem\u003ein vitro\u003c/em\u003e and in burned animal models. Similar to previous data, EXs could stimulate cell proliferation and migration in 2D cultures and heal the wound faster than the control group in burned mice \u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e,\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e. The mechanism under this effectiveness may come from EXs internalized into cultured cells and penetrating into the skin and distributed around the area, as we have reported in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e. This is important to the applicable approach regarding the real application of EXs. Furthermore, the efficacy of the healing rate may be due to the components equipped with EXs that induce regeneration at the wound site. However, the faster healing effect did not last until day 10. This may be due to the intradermal treatment of EXs only for the first three days, indicating a prolonged treatment requirement depending on the wound's severity.\u003c/p\u003e \u003cp\u003eIn conclusion, our study is the first reported mRNA profile in human UCMSC-derived EXs since the first report on exosomal mRNA profiles originated from mouse and human mast cell lines [5]. There have been several investigations on UCMSC-derived exosome miRNAs, but not yet on mRNAs. Despite this study being the pioneer study reported on the mRNAs packed into EXs and their effectiveness in promoting cell proliferation, migration, and wound closure, we have only investigated entire EXs in several wound healing processes. Further investigations are required for the association of exosomal genes with signaling pathways and their influence on other wound healing processes, such as angiogenesis, coagulation, scar formation, and the recovery level of skin structure.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eEthical declarations\u003c/h2\u003e \u003cp\u003e \u003cstrong\u003eEthical approval\u003c/strong\u003e \u003cp\u003e for the use of human MSCs from the umbilical cord and dermal fibroblasts was issued by the Vinmec International General Hospital Joint Stock Company's ethics committee (Ethical approval number: 02/2022/CN-HĐĐĐ VMEC). The umbilical cord tissues were collected from three healthy donors aged 20 to 40, and skin tissues for fibroblasts were collected from women who had undergone plastic surgery. All donors signed written informed consent before donating their samples, and experimental protocols were performed in accordance with the relevant guidelines and regulations and approved by the ethics committee.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e For the use of animals and all experimental protocols involving animals, the study was approved by the Institutional Review Board at Dinh Tien Hoang Institute of Medicine. The Ethical approval number IRB-A 2203. We confirmed that all experiments and methods used in this study were performed in accordance with relevant regulations and the ARRIVE (Animal Research: Reporting of In Vivo Experiments) guideline.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eEX preparation\u003c/h3\u003e\n\u003cp\u003eThe primary UCMSCs at passage 3 (P3) were supplied by the EV group (Vinmec Hi-Tech Center) and expanded to P5 in DMEM/F12 (Gibco, Massachusetts, USA) supplemented with 10% FBS (Gibco, Massachusetts, USA) (v/v) at 5% CO\u003csub\u003e2\u003c/sub\u003e and 37 \u003csup\u003eo\u003c/sup\u003eC. UCMSCs P5 were seeded with a density of 5000 cells/cm\u003csup\u003e2\u003c/sup\u003e in a T75 flask with EV-depleted culture media (90% DMEM/F12 and 10% EV-depleted FBS). To prepare EV-depleted FBS, FBS was centrifuged at 120,000 \u0026times; g / 18 hours /4\u0026deg;C. After four or five days of incubation, when cells reached 80% confluency, the conditioned medium was collected and centrifuged at 300 \u0026times; g / 10 minutes / 4\u0026deg;C to remove cell debris. Then, apoptotic bodies and microvesicles (MV) were removed using sequential centrifugations at 2,000 \u0026times; g / 20 min / 4\u0026deg;C and 16,500 \u0026times; g / 30 min / 4\u0026deg;C, respectively. The remaining supernatant was collected and centrifuged at 100,000 \u0026times; g / 90 min / 4\u0026deg;C for EXs (Optima XPN-100 Ultracentrifuge, Beckman Coulter, California, USA) \u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. All EXs were resuspended in PBS and stored at \u0026minus;\u0026thinsp;80\u0026deg;C for further use.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eWestern blot\u003c/h2\u003e \u003cp\u003eEXs were mixed with RIPA buffer (Thermo Scientific, USA) in an equivalent volume, incubated for 30 min at 4\u0026deg;C, and then centrifuged at 16,000 x g for 20 min at 4 \u003csup\u003eo\u003c/sup\u003eC for protein extraction. Protein concentration was determined using the Pierce\u003csup\u003e\u0026trade;\u003c/sup\u003e BCA Protein Assay Kit (Thermo Scientific, USA) and the optical densitometry method (Optical density - OD) at 560nm. A total 10\u0026ndash;20 \u0026micro;g exosome proteins was loaded into each well and separated using a 4\u0026ndash;12% NuPAGE gel (Invitrogen, USA) at 200 V for 60 min at 4\u0026deg;C prior to being transferred to a PVDF membrane (AmershamTM, GE Healthcare Life Science, Illinois, US) at 200 mA for 2 hours at 4\u0026deg;C. After that, membranes were incubated with primary antibodies diluted in TBST solution for anti-CD63 (dilution 1:200), anti-CD9 (dilution 1:100), anti-HSP70 (dilution 1:200), and anti-AGO2 (dilution 1:100) (Abcam, Cambridge, UK) overnight at 4\u0026deg;C. The primary antibodies were washed before incubating with secondary antibody Mouse IgG (Amersham ECL Mouse IgG, HRP-linked whole Ab, GE Healthcare Life Sciences, Pittsburgh, USA). Antibody binding was detected by ECL chemiluminescent substrate (Sigma-Aldrich, Singapore) and imaged on an ImageQuant LAS 500 (GE Healthcare Life Science, Illinois, US) \u003csup\u003e\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eTransmission electron microscopy (TEM)\u003c/h2\u003e \u003cp\u003eEXs were fixed with 4% paraformaldehyde and subsequently placed onto a carbon grid (Ted Pella Inc., California, USA). Samples were then washed before being stained and dried at room temperature. Finally, samples were examined and photographed by a Transmission Electron Microscopy JEOL 1100 (TEM, JEOL Ltd., Tokyo, Japan) at 80 kV at the National Institute of Hygiene and Epidemiology (NIHE) \u003csup\u003e\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eExosome label, uptake, and penetration\u003c/h2\u003e \u003cp\u003e EXs were stained using the ExoGlow-Membrane EV Labeling Kit (System Biosciences, USA) according to the manufacturer's protocol. In brief, the labeling buffer and dye were mixed with 100 \u0026micro;g of EXs and incubated for 30 minutes at room temperature in the dark. The reaction mixture was then applied to a PD SpinTrap G-25 column (Cytiva Sweden, UK) to eliminate unbound dye and centrifuged at 800 \u0026times; g for 2 minutes. The labeled EXs were collected in the first eluate \u003csup\u003e\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eEX uptake assays were conducted using human dermal fibroblasts provided by the EV group (Vinmec HiTech Center). Cells were seeded into a 96-well plate and incubated with labeled EXs. After four hours of incubation at 37\u0026deg;C, the medium containing excess labeled EXs was removed, and the cells were washed with PBS. Then, cells were fixed with PFA 4% for 20 minutes, followed by nuclear staining with DAPI (4\u0026prime;,6-diamidino-2-phenylindole) (Thermo Fisher Scientific). EX uptake was evaluated by using confocal microscopy \u003csup\u003e\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eEX penetration examinations were tested on \u003cem\u003eex vivo\u003c/em\u003e human skin models. The skin was cut into approximately 1 x 1 cm in length and placed on clean dishes. 100 \u0026micro;L of fluorescence-labeled EX solution (50 \u0026micro;g of exosomal protein) was injected into the epidermis (five injection sites) using a 1 mL syringe equipped with a 32G needle. Skin explants injected with fluorescence-labeled EXs were cultured for 12 hours before being fixed and stained to investigate the penetration of EXs into the dermis \u003csup\u003e\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eRNA library preparation and transcription sequencing\u003c/h2\u003e \u003cp\u003eTotal RNAs from EXs and secreting UCMSCs were extracted using Trizol\u003csup\u003e\u0026trade;\u003c/sup\u003e method. Extracted RNA was quantified using Qubit RNA HS Assay Kit (Thermo Fisher, USA) to measure total RNA concentration. The optimal range for purified RNA is from 5 ng/\u0026micro;L to 10 ng/\u0026micro;L in RNase/DNase-free water. RNA integrity (RIN) was measured by the Agilent 4200 TapeStation system using High Sensi RNA ScreenTape (Agilent, USA). An amount of 50 ng total RNA was used for reverse transcription using random hexamer primers to synthesize the first cDNA strand. The second cDNA strand was synthesized by DNA polymerase using the first cDNA strand as a template. The cDNA fragments were then end-repaired and A-tailed to generate the 5' overhangs for indexing adapter ligation. The A-tailed cDNA fragments were ligated with an indexing adapter, followed by amplification with i5 and i7 indexing primers for sample multiplexing. The indexed libraries were pooled and hybridized with the Illumina exome sequencing panel (Illumina, USA). Targeted regions of interest were then captured using Streptavidin Magnetic Beads, followed by the final amplification step to achieve an enriched library. The quality of the enriched library was then assessed on Agilent 4200 TapeStation (Agilent, USA) using High-Sensitivity D1000 Tapes. The library concentration was measured by Qubit 4.0 Fluorimeter using Qubit dsDNA BR Assay Kit (Thermo Fisher, USA). The library was diluted to 4 nM using the resuspension buffer (RSB), followed by a denaturing step in the presence of NaOH 0.2 N by ratio 1:1 (v/v). The denatured library was diluted with denaturing buffer HT1 to achieve a 20 pM denatured library solution. The denatured library was then diluted to the final concentration of 1.3 pM in a total volume of 1.3 mL for sequencing. Sequencing was done on the Nextseq 500/550 system using Nextseq High Output v2.5 (300 cycles) (Illumina, USA).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eRNA-seq data analysis\u003c/h2\u003e \u003cp\u003eAt least 9\u0026nbsp;million paired-end reads (2 x 75 base pairs or bp) were obtained for each replicate. Raw quality sequencing was assessed using FastQC v0.11.9 \u003csup\u003e49\u003c/sup\u003e both before and after adapter trimming, and all samples passed scores on all FastQC criteria. Nextera adapter sequences, low-quality base calls (Phred score\u0026thinsp;\u0026lt;\u0026thinsp;15), and short reads (read length\u0026thinsp;\u0026lt;\u0026thinsp;20 base pairs) were trimmed using Trim Galore v0.6.2 \u003csup\u003e50\u003c/sup\u003e. FASTQ paired-end reads were aligned using HISAT2 v2.2.1 \u003csup\u003e51\u003c/sup\u003e to the human GRCh38 genome build from Ensembl \u003csup\u003e\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e\u003c/sup\u003e. The resulting BAM files were sorted by read name and chromosome position with Samtools v1.8 \u003csup\u003e53\u003c/sup\u003e. Transcripts were quantified via the FeatureCounts function of the Bioconductor R package Rsubread v1.6.4 \u003csup\u003e54\u003c/sup\u003e, counting non-strand-specific fragments instead of reads. MultiQC (v1.9) \u003csup\u003e55\u003c/sup\u003e was used to aggregate FastQC, HISAT2, and FeatureCounts results.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eRNA biotype classification and analysis\u003c/h2\u003e \u003cp\u003eTo quantify the presence of different RNA biotypes, including long RNAs (both coding and non-coding) and short RNAs, the MGcount toolkit (v1.1.0) \u003csup\u003e56\u003c/sup\u003ewas used using parameters suitable for unstranded paired-end reads. MGcount hierarchically assigns RNA-seq reads present to genomic annotated features in three pre-defined sequential rounds based on transcript body length: small RNA, long RNA exon, and long RNA introns, then quantifies these RNA features. An integrated GRCh38 .gtf file was used in this analysis to annotate relevant RNA features such as long RNA introns, long RNA exons, snoRNAs, and snaRNAs in the dataset if they are present. The RNA feature expression matrix from MGcount was used as input to DESeq2 for differential analysis of RNA biotype abundance between exosomes and cells, enabling the identification of features enriched in exosomes. RNA biotype distribution and differential abundance were visualized using a series of R packages, including Enhanced Volcano and ggplot2.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eDifferential analysis\u003c/h2\u003e \u003cp\u003eDifferential analysis was performed on the count matrix using R version 4.2 and the R package DESeq2 v3.15 to compare exosomes and cells from which they are excreted \u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. Data was normalized using DESeq2's built-in median-of-ratios method to account for library depth and RNA composition across samples. Genes with low counts (the sum of counts is less than 60 across all samples) were filtered, as they mostly reflect noise in the dataset.. Heatmaps were generated with the R package pheatmap (v1.0.12, available at: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://github.com/raivokolde/pheatmap\u003c/span\u003e\u003cspan address=\"https://github.com/raivokolde/pheatmap\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e).\u003c/span\u003e P values were adjusted using the FDR method for multiple testing. Significantly differentially expressed genes (DEGs) were selected with an FDR\u0026thinsp;\u0026lt;\u0026thinsp;0.05 and log\u003csub\u003e2\u003c/sub\u003e fold change\u0026thinsp;\u0026ge;\u0026thinsp;1 or \u0026lt;-1 for comparison between exosomes and cells. Volcano plots were built using the R package Enhanced Volcano (v1.16.0) \u003csup\u003e57\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003ePairwise correlations and hierarchical clustering\u003c/h2\u003e \u003cp\u003eThe top significant DEGs in upregulated and downregulated gene sets were filtered according to adjusted p values (adjusted p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) and log\u003csub\u003e2\u003c/sub\u003eFold Change (|log2FC| \u0026gt; 2). Using the average agglomeration method, the distance matrix was constructed using the Pearson correlation coefficient of the logarithm of the normalized expression of DEGs in all samples. The gene-gene correlation heatmap was visualized using the heatmap.2 function of the R package gplots (version 3.1.3) \u003csup\u003e58\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003ePathway enrichment analysis\u003c/h2\u003e \u003cp\u003eSignificant DEGs (adjusted p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 and |Log2FC| \u0026gt; 1) were used to identify over-represented Gene Ontology (GO) terms (GO Biological Process and Molecular Function databases) and enriched pathways annotated in the Kyoto Encyclopedia of genes and genomes (KEGG) database. Enriched pathways with p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 were considered statistically significant. Analysis and visualization of GO term overrepresentation were performed using the R package ClusterProfiler v4.4.4 \u003csup\u003e59\u003c/sup\u003e. KEGG pathway enrichment and visualization were performed via the R package gage (v2.52.0) \u003csup\u003e60\u003c/sup\u003e and KEGG v1.42.0 \u003csup\u003e61\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eNetwork analysis\u003c/h2\u003e \u003cp\u003eProtein-protein interactions of the genes enriched in exosomes or part of the exosome-enriched cluster were constructed using the STRING protein database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://string-db.org/\u003c/span\u003e\u003cspan address=\"https://string-db.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e).\u003c/span\u003e Upregulated genes were filtered based on the following thresholds: adjusted p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 and Log2FC\u0026thinsp;\u0026gt;\u0026thinsp;1. Protein interactions with a confidence score of more than 0.4 were chosen, indicating moderate to strong evidence of protein interaction. The largest subnetwork was selected for further analysis to filter proteins or protein pairs with few interactions with other nodes in the network. Using default parameters, the Cytoscape plug-in Molecular Complex Detection (version 1.32) \u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003ewas used to identify prominent subnetworks and clusters within the protein interaction network. Network clusters with an MCODE score greater than 25 were chosen to analyze upregulated genes.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003eProliferation Assay\u003c/h2\u003e \u003cp\u003eHuman dermal fibroblasts were seeded at 2,500 cells/well of a 96-well plate and incubated in DMEM/F12 supplemented with 10% EV-depleted FBS and 10 \u0026micro;g EXs at 37\u0026deg;C and 5% CO\u003csub\u003e2\u003c/sub\u003e for 48 hours to proliferate. The control group consisted of cells incubated with DMEM/F12 supplemented with 10% EV-depleted FBS. The cell proliferation rate was assessed by performing a 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl tetrazolium bromide (MTT) assay (Abcam, Cambridge, UK) following the manufacturer's protocols. The proliferation rate was equivalent to the relative absorbance measured at 562 nm (SpectraMax M3, Molecular Devices, California, USA) at time points of 0 hours (as used for normalization) and 48 hours, with a higher OD value indicating a higher proliferation rate.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003eMigration Assay\u003c/h2\u003e \u003cp\u003eHuman dermal fibroblasts were seeded at 1.05 \u0026times; 10\u003csup\u003e5\u003c/sup\u003e cells/ well of a 24-well plate at 37\u0026deg;C and 5% CO2 for attachment. After reaching 100% confluency, fibroblasts were incubated with Mitomycin C (10 \u0026micro;g/mL) for 2 hours to inhibit cell proliferation. A physical scratch was created on the cell attachment layer, and detached cells were removed by washing with media. The cells were then treated with DMEM/F12 supplemented with 10% EV-depleted FBS and 10 \u0026micro;g EXs, and the control cells were treated with DMEM/F12 supplemented with 10% EV-depleted FBS. Cell migration to close the wound area was captured by an inverted microscope at multiple time points. The wound area was measured using ImageJ software (version 1.48) and calculated for the closure percentage over time, representing the cell migration rate.\u003c/p\u003e \u003cdiv id=\"Sec23\" class=\"Section3\"\u003e \u003ch2\u003eWound healing animal model\u003c/h2\u003e \u003cp\u003eSwiss male mice (50\u0026ndash;60 g, 8\u0026ndash;10 weeks old) were supplied by the Center of Experimental Animals - Vietnam Military Medical University. Mice were supplied with food and water daily in a 12-hour light/dark cycle condition. The mice were anesthetized with intraperitoneal ketamine (50 mg/mL), a 140 mg/kg body weight dosage. The dorsum of mice was shaved using an electric shaver, and the skin was disinfected with an alcohol swab. A metal plate (1.5 \u0026times; 1.5 \u0026times; 0.3 cm) was sterilized with 70% ethanol and then heated for 5 minutes in boiling water before being placed immediately on the skin for 10 seconds to create burned wounds. A wound would be made on the right side of the dorsum. The mice were randomly divided into three groups (n\u0026thinsp;=\u0026thinsp;3 each), including group 1: non-treated, group 2: injected intradermally with 100 \u0026micro;L PBS, and group 3: injected intradermally with 100 \u0026micro;L EX solution (1 \u0026micro;g/1 \u0026micro;L). Wounded animals were immediately treated with substances as designed after creating the wounds, PBS, and exosome injections for the first three days, and all were followed up for 14 days.\u003c/p\u003e \u003cp\u003eMice were humanely euthanized at the end of the experiment at the Animal Center of the Military Medical Academy by the Center's technicians. The animals were euthanized using CO₂ in a specialized glass chamber. Each mouse was placed into the chamber, which was then filled with 100% compressed CO₂ at a flow rate of 30\u0026ndash;70% of the chamber volume per minute to ensure rapid loss of consciousness and to minimize pain or distress. Each mouse was observed individually to detect cessation of breathing and corneal opacity (gradual clouding or paling of the eyes), which typically occurs after 2\u0026ndash;3 minutes of gas exposure. CO₂ flow was maintained for at least one additional minute after respiratory arrest was confirmed.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec24\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eN represents the number of independent replicates per group, as detailed in each figure legend. The false discovery rate (FDR) was calculated for each statistical test to correct for errors of multiple testing. The Benjamini and Hochberg (BH) method was used to compute the false discovery rate (FDR) for each statistical test. The thresholds for DEG detection were specified in the Methods section. Statistical testing was performed using built-in packages in R (version 4.2) (R Core Team, 2022) and Python (version 3.10).\u003c/p\u003e \u003cp\u003eData from the wet lab were presented in Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD. The student's t-test and ANOVA were used for comparisons between groups. The p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was used to determine the significant difference.\u003c/p\u003e \u003c/div\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eEVs\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Extracellular vesicles\u003c/p\u003e\n\u003cp\u003eEXs\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Exosomes\u003c/p\u003e\n\u003cp\u003eMSCs\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Mesenchymal stem cells\u003c/p\u003e\n\u003cp\u003eUCMSCs\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Umbilical cord-derived\u0026nbsp;mesenchymal stem cells\u003c/p\u003e\n\u003cp\u003eGO\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Gene Ontology\u003c/p\u003e\n\u003cp\u003eKEGG\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Kyoto encyclopedia of genes and genomes\u003c/p\u003e\n\u003cp\u003eDEGs\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Differentially expressed genes\u003c/p\u003e\n\u003cp\u003eGAGE Generally Applicable Gene-set Enrichment\u003c/p\u003e\n\u003cp\u003eDMEM/F12\u0026nbsp; \u0026nbsp;\u0026nbsp;Dulbecco\u0026apos;s Modified Eagle medium/Ham\u0026apos;s F-12\u003c/p\u003e\n\u003cp\u003eFBS\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Fetal bovine serum\u003c/p\u003e\n\u003cp\u003eMVs\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Microvesicles\u003c/p\u003e\n\u003cp\u003ePBS\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Phosphate buffer saline\u003c/p\u003e\n\u003cp\u003eBCA Bicinchoninic acid\u003c/p\u003e\n\u003cp\u003ePVDF Polyvinylidene fluoride\u003c/p\u003e\n\u003cp\u003eTBST \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Tris-buffered saline with Tween\u0026reg; 20\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNTA Nanoparticle tracking analysis\u003c/p\u003e\n\u003cp\u003eTEM\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Transmission electron microscopy\u003c/p\u003e\n\u003cp\u003eFDR\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;False discovery rate\u003c/p\u003e\n\u003cp\u003eBH \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Benjamini and Hochbergw\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgment\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe sincerely thank Dr. Nguyen Thi Nhan for their valuable bioinformatics analysis and review advice.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis project was funded by the VinIF project code VINIF.2021.DA00193.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data generated in this study are provided in the articles and available in online supplementary files. All RNA sequencing data reported in this publication have been deposited in NCBI\u0026apos;s Gene Expression Omnibus and are accessible through the GEO accession number: GSE252017.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEthical approval for the use of human MSCs from the umbilical cord and dermal fibroblasts was issued by the Vinmec International General Hospital Joint Stock Company\u0026apos;s ethics committee (Ethical approval number: 02/2022/CN-HĐĐĐ VMEC). The umbilical cord tissues were collected from three healthy donors aged 20 to 40, and all donors signed the written informed consent before the samples were collected.\u003c/p\u003e\n\u003cp\u003eThe use of animals in this present study followed guidelines for animal treatment and complied with the relevant legislation from the Institutional Review Board at Dinh Tien Hoang Institute of Medicine (Ethical approval number: IRB-A 2203).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe conception and design of the study: UTTT, NHN, NTMH, and X-HN; Data collection: UTTT, HTTN, QMD, DMV, T-HN, NTMH, THN, X-HN, X-HD, HHD, HTP, QML; Analysis and interpretation of data: UTTT, HTTN, QMD, DMV, THN, NTMH, THN, X-HN, X-HD, HHD, HTP, QML; Manuscript drafting: UTTT, THN, QMD; Manuscript revising, UTTT, X-HN, NTMH, NHN; Final approval: NHN; Funding acquisition: NHN and UTTT.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eLiangsupree, T., Multia, E. \u0026amp; Riekkola, M. 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In this study, we profiled the transcriptome of umbilical cord mesenchymal stem cell (UCMSC)-derived exosomes (EXs) using RNA-seq and explored the functional roles of their transcriptome, particularly in cutaneous wound repair. We detected 4,578 protein-coding genes in UCMSC-derived EXs, of which 2,004 were upregulated, and 2,574 were downregulated relative to their secreting cells. Notably, many EX-enriched genes were associated with wound-healing biology, and pathway analysis revealed that upregulated exosomal genes were involved in GO terms and KEGG pathways related to DNA replication, ribosome function, cell cycle regulation, and pyrimidine metabolism. To validate UCMSC-EX's capability for wound healing predicted through \u003cem\u003ein silico\u003c/em\u003e analyses, we further assessed EX penetration into the dermis, cellular uptake, and therapeutic efficacy in a burned mouse model. UCMSC-derived EXs efficiently penetrated human dermal tissue, were internalized by fibroblasts, and promoted fibroblast and keratinocyte proliferation and migration in 2D culture. \u003cem\u003eIn vivo\u003c/em\u003e, EX treatment accelerated wound closure, particularly during the early stages of healing. Overall, our findings demonstrate selective mRNA enrichment in UCMSC-derived EXs and highlight their promising therapeutic potential in cutaneous wound healing.\u003c/p\u003e","manuscriptTitle":"mRNA profiling of mesenchymal stem cell-derived exosomes reveals their function in accelerating wound healing","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-19 17:01:08","doi":"10.21203/rs.3.rs-8130672/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-02-04T08:35:28+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"327300751324678244569796417770718241960","date":"2026-01-30T08:12:04+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-28T08:57:57+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"226213014498851930463132191132173520520","date":"2026-01-26T04:12:53+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"129261391725951414774402452933134422565","date":"2026-01-26T02:41:33+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"28766121137585636044501016862503033966","date":"2026-01-25T04:41:48+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-22T03:22:26+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"213311066130072170044025515083029275441","date":"2026-01-14T17:45:43+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-01-14T17:33:46+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-12-30T13:22:35+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-12-29T09:28:06+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-12-27T03:04:42+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2025-12-27T02:58:25+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"8771f403-e007-4f95-af56-f0a10469a2bd","owner":[],"postedDate":"January 19th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":61322676,"name":"Biological sciences/Cell biology"},{"id":61322677,"name":"Biological sciences/Molecular biology"},{"id":61322678,"name":"Biological sciences/Stem cells"}],"tags":[],"updatedAt":"2026-03-23T16:06:13+00:00","versionOfRecord":{"articleIdentity":"rs-8130672","link":"https://doi.org/10.1038/s41598-026-45267-w","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2026-03-21 15:58:46","publishedOnDateReadable":"March 21st, 2026"},"versionCreatedAt":"2026-01-19 17:01:08","video":"","vorDoi":"10.1038/s41598-026-45267-w","vorDoiUrl":"https://doi.org/10.1038/s41598-026-45267-w","workflowStages":[]},"version":"v1","identity":"rs-8130672","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8130672","identity":"rs-8130672","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}