Impact of low-intensity pulsed ultrasound on transcription and metabolite compositions in proliferation and functionalization of human adipose-derived mesenchymal stromal cells

To investigate the effect of low-intensity pulsed ultrasound (LIPUS) on the proliferation of human adipose-derived mesenchymal stromal cells (hASCs) and uncovered its stimulation mechanism. LIPUS at 30 mW/cm2 was applied for 5 min/day to promote the proliferation of hASCs. Flow cytometry was used to study the cell surface markers, cell cycle, and apoptosis of hASCs. The proliferation of hASCs was detected by cell counting kit-8, cell cycle assay, and RT-PCR. The expression of hASCs cytokines was determined by ELISA. The differences between transcriptional genes and metabolites were analyzed by transcript analysis and metabolomic profiling experiments. The number of cells increased after LIPUS stimulation, but there was no significant difference in cell surface markers. The results of flow cytometry, RT-PCR, and ELISA after LIPUS was administered showed that the G1 and S phases of the cell cycle were prolonged. The expression of cell proliferation related genes (CyclinD1 and c-myc) and the paracrine function related gene (SDF-1α) were up-regulated. The expression of cytokines was increased, while the apoptosis rate was decreased. The results of transcriptome experiments showed that there were significant differences in 27 genes;15 genes were up-regulated, while 12 genes were down-regulated. The results of metabolomics experiments showed significant differences in 30 metabolites; 7 metabolites were up-regulated, and 23 metabolites were down-regulated. LIPUS at 30 mW/cm2 intensity can promote the proliferation of hASCs cells in an undifferentiating state, and the stem-cell property of hASCs was maintained. CyclinD1 gene, c-myc gene, and various genes of transcription and products of metabolism play an essential role in cell proliferation. This study provides an important experimental and theoretical basis for the clinical application of LIPUS in promoting the proliferation of hASCs cells.

Scientific RepoRtS | (2020) 10:13690 | https://doi.org/10.1038/s41598-020-69430-z www.nature.com/scientificreports/ Mesenchymal stromal cells (MSCs) are separated from bone marrows, and they are a group of non-phagocytes with morphological characteristics of fibroblast-like adherent cells. Subsequent studies have shown that MSCs have been successfully separated from different organs, e.g., bone marrow derived mesenchymal stromal cells (BM-MSCs), adipose-derived mesenchymal stromal cells (ASCs), stem cells from the umbilical cord, soft bone and skin 8,9 . Because ASCs have abundant sources and can be easily obtained, they are becoming the primary source of seeding cells for next-generation tissue engineering 10 .
With the rapid development of stem cell research in recent years, the studies and applications of stem cell biology have become more advanced. hASCs have been widely used in diabetes, heart repair, Parkinson's disease, bone healing, wound healing, and tumor treatments. Consequently, the success of hASC applications promotes the development of stem cell transplantation and regenerative medicine [10][11][12] . The maximum number of ASCs obtained from 100 mL adipose tissue is approximately 9.06 × 10 5 stem cells 12 . However, the minimum number of stem cell transfusion therapy requires 2 × 10 6 cells, while most treatment needs 10 8 cells. A cell therapy course would require a substantial amount of ASCs cells 13 , which cannot be obtained from patients themselves or donators, and thus limits the application of hASCs. Therefore, the exploration and development of high-efficiency in vitro expansion of stem cells and the shortening of treatment time will be beneficial to patients in need of stem cells.
A cell's microenvironment refers to the local physiological surroundings composed of cells, extracellular matrix, stromal cells, cytokines, and immune cells. Cell-cell interactions, cytokine interactions are expressed in this microenvironment. The morphology and biological behavior of cells, and even the differentiation of cells, are affected by the chemical composition of the extracellular matrix 14 . Stem cells, and their local microenvironment (or niche) regulate cell fate and behavior through signaling under the action of external mechanical forces. In vitro, synthetic models of stem cell niches can be used to precisely control and manipulate the biophysical and biochemical properties of the stem cell microenvironment to guide stem cell differentiation and function. The fundamental insights on the mechanisms of mechanics stem-cell biology also provide information for the design of artificial cells to support stem cell regeneration therapy 15,16 .
Low-intensity pulsed ultrasound (LIPUS) transmits mechanical stimulation through the skin to biological tissues in the form of high frequency, small amplitude, and pulsed pressure waves. LIPUS, as a non-invasive treatment method, has been widely applied [17][18][19] . Since Duarte and Xavier first reported the success of LIPUS in treating refractory bone nonunion in 1983; successive generations of LIPUS devices have been developed. Previous studies have shown that LIPUS could stimulate the synthesis of DNA and proteins in vascular cells [20][21][22] , as well as promote cell activity, cytokine release, gene expression, etc. [23][24][25] , indicating that LIPUS can be used in clinical applications. Some researchers are using LIPUS to stimulate the proliferation of human hematopoietic progenitor stem cells (hHSCs) 26 , h-BM-MSCs 27,28 , human amniotic mesenchymal nerve 29 , and neural crest stem cells derived from pluripotent stem cells 30 . These results suggest that more numbers of stem cells can be obtained through LIPUS stimulations for clinical application. However, the intensity and stimulation duration of LIPUS acting on different cells were inconsistent, and the changes in the biochemical and metabolic components in the cells after the stimulation and the specific mechanism were still unclear, which deserves further study.
Researchers have made significant progress in using LIPUS to stimulate other types of stem cells. However, the effect of LIPUS stimulation on the proliferation and function of ASCs has rarely been reported, and its mechanism was remain unclear. Here, our study showed that 30 mW/cm 2 of LIPUS could promote the effective proliferation of hASCs. Cell proliferation may be the result of the up-regulation of Cyclin D1 and c-myc genes as well as the regulation of transcriptional genes and metabolites through a variety of pathways. These results may provide substantial evidence supporting the use of LIPUS in promoting stem cell activity and proliferation. Tissue engineering and clinical therapy may benefit from the use of LIPUS proliferated stem cells.
Ultrasound stimulation device. SonaCell (IntelligentNano Inc. Canada) is used to generate LIPUS at 1.5 MHz, with pulse repetition of 1 kHz at a 20% duty cycle. Average output intensity adjusted between 0 mW/ cm 2 to 80 mW/cm 2 . The ultrasound transducer was attached to the bottom of the cell culture dish. Ultrasound gel was applied to help the transmission wave of ultrasound entering the cells. In this study, LIPUS intensities of 10 mW/cm 2 , 20 mW/cm 2 , 30 mW/cm 2 , 40 mW/cm 2 , 50 mW/cm 2 , 60 mW/cm 2 , 80 mW/cm 2 were used for cell stimulation in the stimulated experimental group while 0 mW/cm 2 was used as the control group. To avoid LIPUS wave interference, only 6 holes were used in the 12-hole plate. Transcript analysis. The standard operating procedure of RNeasy Mini Kit was used for total RNA extraction, then mRNA enrichment and rRNA removal, fragmentation, synthesis of one-and two-strand cDNA, endfilling, 3′-end addition A, splicing, PCR amplification, library quality control, library standardization and clustering, and sequencing. The original sequencing data was processed by Fastp software through the disjointing sequence and low-quality sequence. The data after quality control were compared to the Homo sapiens genome (hg38); the HISAT2 v.2.0.5 software was used. The matched reads were further annotated and quantified with stringtie software (Johns Hopkins University, USA), and the R package edagR (Justus-Liebig-Universitat, Germany) was used for standardization and statistics analysis.
Metabolomic profiling. Sample pretreatment: 1,000 μL methanol:acetonitrile : water (V/V, 4:4:2) solution was added to the tube containing cells, vortexed for 60 s, and ultrasonic crushing was conducted in a water bath at 4℃ for 10 min. The solution was placed in liquid nitrogen for 1 min, warmed to room temperature, and immersed in a water bath at 4℃ for ultrasonic crushing for 10 min (repeated 3 times). The samples were placed at − 20℃ for 1 h and centrifuged at 4℃ with 13,000 rpm for 15 min and then the supernatant was extracted for testing. Untargeted metabolomics analysis was performed by LC/MS Data Acquisition (Version B.08.00, Agilent Technologies, USA) coupled with QTOF 6,545 (Agilent Technologies, USA). For chromatographic separation, ACQUITY UPLC HSS T3 column (2.1 mm × 100 mm, 1.8 μm, Waters, USA) was used at 35 °C. Parameters of mass spectrometry were as follows: the gas temperature was 320 °C and gas flow of 8 L/min, sheath gas flow of 12 L/min, and sheath gas temperature maintained at 350 °C. Capillary voltage (VCap) was the anion mode of 3,500 V and the positive ion mode of 4,000 V.
Data Processing and Analysis: MSDIAL software was used to perform peak search, peak alignment, normalization, and other data processing on the data. Meanwhile, metlin, MassBank, MoNA, and HMDB databases were Scientific RepoRtS | (2020) 10:13690 | https://doi.org/10.1038/s41598-020-69430-z www.nature.com/scientificreports/ independently integrated based on the first and second level database search, and the identification results were obtained. For the identified data of MSDIAL alignment, the coefficient of variation (CV) value of the sample index was controlled by quality control (QC) samples to be less than 50%, and the ion peak with the missing value greater than 50% in the group was deleted. The auto-scaling method was applied for normalization, and MetaboAnalyst 4.0 software was applied for difference analysis and enrichment analysis. The quality error of the first level is controlled at 10PPM. The retention time limit is less than 0.15 min. After alignment, the unidentified difference indicators are re-identified to improve the identification rate of the different indicators.

Statistical analysis.
For all measurements, we have performed at least three independent experiments. All data was collected and analyzed using SPS 20.0 statistical software. Means ± standard deviation (SD) were used to present quantitative data. The two independent samples t-test was used to compare two group data, and the one way-ANOVA method was used to compare more group data. p < 0.05 was considered statistically significant.

Results
Selection of optimal LIPUS stimulation conditions. To find the optimal intensity for LIPUS to stimulate the growth of hASCs, the LIPUS generating device, SonaCell, was set to intensities between 30-80 mW/cm 2 .
The stimulation lasted 5 min for each instance for 4 consecutive days. After 72 h, the cell viability of 30 mW/cm 2 , 40 mW/cm 2 , and 60 mW/cm 2 of LIPUS was better than the control (p < 0.05) as discovered by the CCK-8 kit.
Among the groups, 30 mW/cm 2 was the best with a significant difference (Fig. 1b). Then, LIPUS intensities were further reduced to between 10 and 50 mW/cm 2 . The results showed that 20 mW/cm 2 , 30 mW/cm 2 and 40 mW/ cm 2 of LIPUS can stimulate hASCs proliferation, with 30 mW/cm 2 intensity achieving the best results (Fig. 1c). A similar treatment for the hASCs of P3, P6, and P8 was studied. All results showed that 30 mW/cm 2 of LIPUS had the best positive effects on hASCs (Fig. 1d). To uncover the impact of stimulation duration on the proliferation of hASCs, 10 min of LIPUS was administered. The results showed that the cell viability experienced an  www.nature.com/scientificreports/ obvious decrease compared to the control (p < 0.01) (Fig. 1e). Therefore, the 30 mW/cm 2 intensity of LIPUS and 5 min/day treatment was selected for our late experiments ( Supplementary Fig. 1). The change of fibroblast-like cell morphology was not observed in with and without LIPUS stimulations by microscope (Fig. 1a).

Analysis of hASCs cell surface markers after stimulation by LIPUS.
To investigate whether the cell surface markers of hASCs were changed after LIPUS stimulation, the surface markers of adipose mesenchymal stromal cells (CD73, CD105, HLA-ABC, CD45, CD34, and CD14) were detected by flow cytometry. The results showed that there was no significant difference in cell surface markers in the stimulation group (30 mW/cm 2 ) compared with that of the control group (0 mW/cm 2 ) ( Results of cytokine detection. To understand the cytokine secretion potential of hASCs after stimulation by LIPUS, the cytokines of IL-6, IL-2, FGF2, and EGF were measured by ELISA. The results showed that Results of apoptosis assay. To analyze the apoptosis of hASCs after treatment by LIPUS, Annexin V-FITC/PI apoptosis kit was used in detecting hASCs apoptosis. The results showed that there was no difference in late apoptosis (Q2) between the two groups, while the early apoptosis (Q4) in the stimulation group was decreased (p < 0.05) (Fig. 3).

Results of cell cycle analysis.
To analyze the cell cycle of hASCs treated by LIPUS, flow cytometry was used to detect the cell cycle of hASCs. The results showed that the G1 phase and S phase of cells in the stimulation group were higher than those in the control group (p < 0.05). The G2 phase was significantly lower in the stimulation group than those in the control group. (p < 0.05) (Fig. 4). Table 2. Comparison of hASC cell surface markers between the stimulation group and the control group (P3, n = 3). The expressions of hASCs surface markers (CD105-PE, CD73-PE, HLA-ABC-PE, CD14-FITC, CD34-PE, and CD45-PE) were determined by flow cytometry in the stimulation group and the control group. The experimental data were statistically analyzed using two-independent sample t-tests. Means ± standard deviation (SD) were used to present quantitative data.

Results of transcriptome experiments.
To analyze the differences in transcriptional level of hASCs after LIPUS treatment, cells from the stimulation group and the control group were collected for transcriptome experiments.
Analysis of gene difference. EdgeR software was used to analyze the differential expression of genes. First, relative expression volume was generated based on the number of original reads of the gene in units of CPM (count per million). Then the differentially expressed genes were calculated according to their grouping. The differential expression multiples were clustered over the log2 conversion. The screening threshold of significantly differentially expressed genes was p < 0.05 and |log2 (FC) |≥ 1. Figure 6a shows the volcano map of significantly differentially expressed genes, and Fig. 6b shows the heat map of significantly differentially expressed genes. The results of differentially expressed genes showed that after treatment by LIPUS, 15    GO pathway and KEGG pathway annotation and enrichment analysis of differential genes. The significance (q-value < 0.05) results from the group difference gene comparison were used to annotate and enrich by the gene ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG). Annotation and enrichment analysis was performed using the R language clusterProfiler extension package and FDR method for multiple false-positive corrections. The significantly enriched GO and KEGG pathways were labeled in the form of bubble maps, and directed acyclic maps were drawn. At the same time, the main pathways at the GO 2 and KEGG 2 level were annotated, and bar charts were drawn. The results of GO analysis main concentrations were in cell components (including cell-cell, cellular components, organelles, and the cell membrane, etc.), biological processes (cells, metabolic process, many cell biological processes, development process, cell signaling, and cell proliferation, etc.) and molecular functions (molecular binding, catalytic activity and the activity of transcription regulation, etc.) (Fig. 7a). KEGG analysis showed that the related genes were mainly concentrated in signal transduction, transport, catabolism, and endocrine system of functions related to cell proliferation (Fig. 7b).

Results of metabolome experiments.
In this experiment, the data from 7 QC samples were analyzed and evaluated using two methods: total ion flow spectrogram comparison and principal component analysis. When the peaks were obtained from the experimental samples, QC samples were extracted, and PCA analysis was performed after auto-scaling. The QC samples, as shown in the PCA score graph, were clustered together, indicating excellent repeatability of the experiment in this study (n = 6).
Screening of difference indicators. Screening results of difference indexes: in this study, P value < 0.05, fold change > 2 times, and VIP value > 1 were selected as the screening indexes of different metabolic indexes (Table 3). Cluster analysis of difference indicators: Hierarchical clustering was carried out for each group of samples using the expression amount of qualitative significantly different metabolites. As shown in Fig. 8, the samples of the stimulus group and the samples of the control group can appear in the same Cluster through clustering.
Scientific RepoRtS | (2020) 10:13690 | https://doi.org/10.1038/s41598-020-69430-z www.nature.com/scientificreports/ Therefore, it is speculated that the metabolites clustered in the same cluster have similar expression patterns and maybe in relatively close reaction steps in the metabolic process.
Bioinformatics analysis. Metabolic pathway analysis: The different metabolites obtained by the stimulus group and the control groups were submitted to the online website https ://metab oanal yst.ca to utilize their metaboanalyst 4.0 function for relevant pathway analysis, to understand which metabolic pathways significantly changed under the experimental conditions. Pathway analysis is a path analysis based on KEGG metabolic pathways, and univariate analysis, network topology analysis, and other novel algorithms are integrated.
(1) Figure 9a,b show the metabolic pathways involved in the stimulus group and the control group.
(2) Figure. 10 shows the results of the pathway analysis in the form of a bubble diagram, where each bubble represents a metabolic pathway. The abscise-coordinate of the bubble and the size of the bubble represent the size of the pathway's influence factor in the topological analysis. The ordinate of the bubble's location, and the color of the bubble represent the P-value of the enrichment analysis (negative natural logarithm, i.e., − log (P)). Darker color corresponds to a smaller P-value was, and the more significant degree of enrichment. The results showed that the Citrate cycle (TCA cycle) and Pyruvate metabolism had a higher influence value, suggesting that the metabolic pathway was significantly changed.  To search for genes that interacted with metabolites, the selected metabolite names were searched in the stitch database (https ://stitc h.embl.de/) for the genes interacting with them. Among these metabolites, the two differentially expressed metabolites (fraxetin and estrone 3-glucuronide) were found to have interacting genes in the stitch database (Fig. 11).

Discussions
Our study showed that LIPUS could promote the proliferation of hASCs. We compared the effects of LIPUS of differening intensities on hASCs proliferation. The results showed that 30 mW/cm 2 and 5 min/day was the best stimulation setting. Cell proliferation was significantly different after the second-time stimulation, and the promoted proliferation in different passages (P3, P6, and P8) was also observed. However, the proliferation of hASCs cells was inhibited by 10 min/day stimulation. The morphology of the cells after proliferation was consistent with that of mesenchymal stromal cells, which grew in a spindle and vortex shape 31,32 . After stimulation, the cell surface markers CD105, CD73, and HLA-ABC were positively expressed, while CD14, CD34, and CD45 were negatively expressed, which showed no significant difference compared with the cell surface markers of the control group. The cell surface markers were accorded with the characteristics of mesenchymal stromal cells and were consistent with previous studies 33,34 .
hASCs can regulate the fate of T cells and their own immune function. It also shows obvious adaptability to environmental stress and secretes a variety of paracrine factors that promote tissue regeneration, which is Scientific RepoRtS | (2020) 10:13690 | https://doi.org/10.1038/s41598-020-69430-z www.nature.com/scientificreports/ expected to achieve successful immunotherapeutic effects and tissue repairability 10,35 . In our study, after LIPUS stimulations, the release capability of hASCs cytokines (IL-6, IL-2, FGF2, and EGF) in culture medium was enhanced, and the expression of paracrine gene SDF-1α was up-regulated. Additionally, the apoptosis rate was decreased, and the proliferation ability of cells was increased. These results suggest the enhanced functionality of hASCs after LIPUS processing. Previous studies on LIPUS promoting different stem cell proliferation pathways have generally been consistent. Ling et al. used LIPUS to treat human amnion-derived mesenchymal stromal cells (hAD-MSCs). The results showed that cell proliferation plays a role through the ERK1/2 and PI3K-AKT signaling pathways 29  www.nature.com/scientificreports/ of cell cycle signaling molecules that drive cells into the next phase of the cell cycle 36 . In our experiment, G1 and S phase of hASCs cell cycle were significantly increased, and the expression of CyclinD1 gene was up-regulated after LIPUS stimulation, which was consistent with previous reports. Interestingly, c-myc gene expression was also up-regulated after LIPUS stimulation in our experiment. This was consistent with what Paula et al. reported 37 , human adipose tissue-derived stem cells cultured in the absence of exogenous culture conditions enhance c-myc gene expression and promote proliferation. Therefore, we hypothesized that the effect of LIPUS stimulation on the up-regulation of CyclinD1 and c-myc gene expression and hASCs proliferation was due to the activation of various upstream signaling elements and the activation of MAPK/ERK and PI3K/AKT signaling pathways. First, the activated MAPK/ERK signaling pathway promotes the transcription of CyclinD1, a major regulator of cell proliferation, through phosphorylation, and helped hASCs complete the process of the cell cycle. Second, phosphorylated AKT promotes the expression of c-myc and myc-related factor X (MAX) form complexes that promote the transcription of Cyclin-D1. Finally, the hASC cell cycle was promoted from the G1 phase to the S phase, and cell proliferation was promoted as well. These results were similar to the cell proliferation model hypothesized by Budhiraja et al. 27 .
In previous studies, high-intensity LIPUS and prolonged stimulation promoted stem cell differentiation toward osteogenesis and adipogenesis formation [38][39][40][41] . However, in our study, LIPUS of 30 mW/cm 2 , stimulated for 5minutes/day, showed no significant difference in osteogenic, adipogenic, and chondrogenic differentiation Table 3. Screening results of different indexes between stimulation group and control group. www.nature.com/scientificreports/ genes and cell surface markers compared with that of the control group. This suggests that LIPUS of 30 mW/ cm 2 could promote the proliferation of hASCs cells without differentiation, while maintaining the characteristics of stem cells. The transcriptome is the sum of all gene transcriptome probes in a specific tissue or cell, which is related to the genetic information of the genome and the biological function of the proteome. It is an effective means to study the molecular mechanism of different cell processes 25 . On the other hand, metabolomics is a new discipline that conducts a simultaneous qualitative and quantitative analysis of all low molecular weight metabolites of a particular organism or cell in a specific physiological period. It is a branch of system biology which is based on group index analysis, high throughput detection and data processing. Metabolomics aims at information modeling and system integration 42,43 . Metabolomics and transcriptome analysis improve our understanding of stem cell function and are more conducive to the analysis of metabolic pathways and transcriptional gene differences involved in the regulation of stem cell fate, including self-renewal, proliferation, and differentiation 25,44 . In our experiment, transcriptome analysis after LIPUS stimulation revealed significant differences in 27 genes, with 15 genes up-regulated and 12 down-regulated. Among them, KMT2A, APC, DYRK1A, and other genes that played an important role in transcriptional activation 45,46 , cell adhesion 47 , and regulation of cell proliferation signals, were up-regulated 48 . Meanwhile, WFS1 and other genes that participated in the occurrence and development of a variety of diseases, were down-regulated 49 .
The GO analysis revealed the primary pathways leading to enrichment of genetic variations in cell components (including cell-cell and cellular components, organelles, cell membrane, etc.), biological processes (cellular processes, metabolic processes, many cell biological processes, cell signaling, cell proliferation, etc.) and molecular functions (molecular binding, catalytic activity and the activity of transcription regulation, etc.). KEGG analysis showed that the differentially expressed genes were mainly concentrated in signal transduction, transport and catabolism, signal molecules and interaction, cell growth and death, and endocrine system of functions related to cell proliferation. It has been reported that the Ras pathway, once activated, initiates the cascade amplification of serine-threonine kinases. It then recruits Raf-1 serine-threonine kinase from the cytoplasm to the cell membrane, where Raf kinase phosphorylates MAPK kinase (MAPKK, also known as MEK) and MAPKK activates MAPK (also known as ERK). MAPK is activated and then translocated into the cell nucleus to directly activate transcription factors. In addition, MAPK stimulates Fos and Jun transcription factor that forms the transcription factor AP-1, which binds to a specific DNA sequence next to the myc gene to initiate transcription. myc gene products are also transcription factors that activate other genes. Ultimately, these signals converge to induce Cyclin D expression and activity 50 . On the other hand, transcription factor nuclear factor κB (NF-κB) family members (RelA/p65, RelB, c-Rel, and p50/p105) up-regulate the Ras signaling pathway and its downstream gene expression 51 . Interestingly, in the present experiment, we enriched the Rel protein family-associated gene REL(c-Rel), suggesting that hASCs stimulated by LIPUS promote cell proliferation through activation of the Ras signaling pathway and downstream pathway gene expression. The finding is consistent with our hypothesis.
In the metabolomics experiment, 30 metabolites showed significant differences; 7 metabolites were up-regulated, and 23 metabolites were down-regulated. Bioinformatics analysis of metabolites showed that the Citrate cycle (TCA cycle) and Pyruvate metabolism had a higher influence value, which might indicate the metabolic pathway has significantly changed. Studies have reported that Citrate cycle and Pyruvate metabolism were closely related to mitochondrial metabolism, cell cycle and stem cell proliferation [52][53][54] . These two differential metabolites, Fraxetin and Estrone 3-glucuronide, were found to interact with genes in the stitch database, and both showed down-regulation effects. Fraxetin has been reported to inhibit cell proliferation, induce and inhibit anti-inflammatory and tumor development 55 www.nature.com/scientificreports/ promote cell proliferation. Estrone 3-glucuronide is closely related to UDP-uridine diphosphate glucuronosyltransferases (UGT) and is involved in UGT's function and material transport 57 . UGT also plays an important role in drug metabolism and detoxification 58 , which may indicate that LIPUS stimulation was less toxic to hASCs cells. Therefore, transcriptome and metabolome studies have shown that LIPUS stimulation of hASC cells promotes cell proliferation through differences in genes related to cell proliferation and significant changes in metabolites in metabolic pathways. The specific mechanism remains to be further studied. Stem cells and their local microenvironment (or niche) use signals to regulate the fate and behavior of their cells when subjected to external mechanical forces. In vitro, synthetic models of stem cell niches can be used to precisely control and manipulate the biophysical and biochemical properties of the stem cell microenvironment and to guide stem cell differentiation and regeneration 15,16 . LIPUS has been widely applied as a non-invasive treatment method for the transmission of mechanical stimulation through the skin to biological tissues in the form of high-frequency, small amplitude, and pulse pressure waves 17,18 . At the cellular level, ultrasound has been reported to promote microbial growth by releasing cell bundles, increasing cell membrane permeability, regulating the medium, and effect on cell composition, cell function, and genetics. At the molecular level, ultrasound www.nature.com/scientificreports/ promotes or destroys enzyme activity by changing the properties of enzymes, substrates, the reaction between enzymes and substrates, and provides an optimal environment for the reaction 59 . Ultrasound treatment at an appropriate frequency and intensity level can induce favorable changes in the conformation of protein molecules without changing their structural integrity, thus improving the enzyme activity 60 . These results suggested that the application of LIPUS with the appropriate intensity will be beneficial to the development of stem cell proliferation and regenerative medicine. Interestingly, both the PPT2-EGFL8 gene and the S-Acetyldihydrolipoamide-E metabolite were shown to be down-regulated in this experiment. PPT2-EGFL8 gene plays an active role in lipid acyl hydrolase activity and fatty acid metabolism 61 . Similarly, S-Acetyldihydrolipoamide-E is a chemical that supports the formation and maintenance of structured and functioning cell or organelle membranes, which, together with proteins and other lipids, maintain the stability of the membrane structure, thereby further strengthening the membrane and reducing its permeability. It acts directly or indirectly with acetyl coenzyme A. It is involved in cellular processes that synthesize or break down lipid molecules to provide energy or storage and plays a vital role in the TCA cycle and Pyruvate metabolism 62,63 (Fig. 9). Therefore, we speculate that the PPT2-EGFL8 gene and S-Acetyldihydrolipoamide-E co-regulate the fatty acid metabolic pathway involved in LIPUS stimulation to promote cell proliferation. The exact mechanism is subject to further investigation.
In conclusion, LIPUS could promote the proliferation of hASCs. LIPUS may activate MAPK/ERK, and PI3K/ AKT signaling pathways by up-regulating the CyclinD1 gene and c-myc gene in hASCs cells without differentiation. The proliferation of cells was facilitated by the significantly different changes in multiple genes of the transcript and various products of metabolism. The results of this study provided important clues for the clinical application of LIPUS in promoting the proliferation of hASCs cells. Figure 10. The summary and analysis of metabolic difference between the stimulation group and the control group. In the bubble diagram, each bubble represents a metabolic pathway. The ordinate, where the bubble was, and the color of the bubble represent the p value of the enrichment analysis (i.e., −log (P)). The darker the color was, the smaller the p value was, and the more significant the enrichment degree was. The Citrate cycle (TCA cycle) and Pyruvate metabolism had a higher influence value, which might be the significantly changed metabolic pathway. Figure 11. Genes of interactive metabolites. To search for genes that interacted with metabolites, the selected metabolite names were searched in the stitch database for the genes interacting with them. Fraxetin (left) and estrone 3-glucuronide (right) were found the genes that interacted in the stitch database.