Construction of an interactome network among circRNA-miRNA-mRNA reveals new biomarkers in hBMSCs osteogenic differentiation

Construction of an interactome network among circRNA-miRNA-mRNA reveals new biomarkers in hBMSCs osteogenic differentiation | 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 Construction of an interactome network among circRNA-miRNA-mRNA reveals new biomarkers in hBMSCs osteogenic differentiation Kaixin Su, Xinyan Cui, Jian Zhou, Qiao Yi, Ousheng Liu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4603272/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 18 Oct, 2024 Read the published version in Scientific Reports → Version 1 posted 10 You are reading this latest preprint version Abstract Human bone marrow mesenchymal stem cells (hBMSCs) are adult stem cells residing in the bone marrow, characterized by their capacity for multi-directional differentiation, self-renewal, migration, and engraftment. Serving as seed cells, BMSCs play a pivotal role in the regeneration of bone defects. Hence, investigating the transcription factors and signaling pathways involved in the regulation of osteogenic differentiation in BMSCs holds significant importance. Recent re-search has unveiled that certain circular RNAs (circRNAs) can function as molecular sponges, influencing the osteogenic differentiation process of mesenchymal stem cells. However, many circRNAs remain undiscovered, and their precise mechanisms remain elusive. Therefore, the objective of this study is to construct an osteogenic differentiation-related circRNA-miRNA-mRNA network in hBMSCs through bioinformatics analysis. Subsequently, circRNAs associated with the osteogenic differentiation of hBMSCs, as identified by bioinformatics analysis, along with their potential miRNA-mRNA axes, will be validated through in vitro experiments. Biological sciences/Molecular biology Biological sciences/Stem cells Earth and environmental sciences/Biogeochemistry Health sciences/Biomarkers Health sciences/Molecular medicine circRNA miRNA osteogenesis hBMSCs Figures Figure 1 Figure 2 Figure 3 Figure 4 1. Introduction Mesenchymal stem cells (MSCs) hold a prominent position in regenerative medicine due to their multipotency, self-renewal capabilities, and low immunogenicity. MSCs possess the remarkable ability to differentiate into various cell types, including osteoblasts, adipocytes, and chondrocytes, both in vivo and in vitro [ 1 ] . Among MSCs, human bone marrow mesenchymal stem cells (hBMSCs) are extensively utilized in clinical trials for bone tissue regeneration and show promising therapeutic outcomes for skeletal disorders such as bone defects and osteoporosis [ 2 ] . Glucocorticoids and dexamethasone (DEX) are commonly employed clinically to induce osteogenic differentiation in BMSCs [ 3 ] . In recent years, there has been significant attention directed towards understanding the osteogenic differentiation of BMSCs, which involves a myriad of transcription factors and signaling pathways [ 4 ] . Competing endogenous RNA (ceRNA), proposed in 2011, introduced a novel mechanism of RNA interaction, expanding the biological functions of mRNA and non-coding RNA (ncRNA) [ 5 , 6 ] . Besides, circular RNAs (circRNAs) or long non-coding RNAs (lncRNAs) primarily act as molecular sponges for miRNAs, adsorbing miRNAs and relieving their suppressive effects on target mRNA [ 7 ] . CircRNA, characterized by a covalently closed, circular structure, is derived from the reverse splicing of mRNA precursors and has emerged as a significant component of the transcriptome [ 8 , 9 ] . In recent years, the functional and clinical significance of ceRNA networks in various diseases, including cancer, cardiovascular diseases, and neurological disorders, has been increasingly recognized, offering potential avenues for disease treatment research [ 10 , 11 ] . In 2017, Yu et al. first reported the correlation between circRNAs and stem cell differentiation, confirming that downstream circRNAs regulate stem cell differentiation through the ceRNA mechanism [ 12 ] . Recent studies have identified numerous circRNAs that exhibit differential expression during MSC osteogenesis, some of which have been shown to regulate the osteogenic differentiation process [ 13 – 16 ] . However, the specific roles of many circRNAs and their associated ceRNA networks in BMSC osteogenic differentiation remain unexplored. Therefore, to gain a comprehensive understanding of the impact of the ceRNA mechanism on BMSC osteogenic differentiation, it is imperative to elucidate the circRNA-miRNA-mRNA regulatory network. In this study, we employed bioinformatic analysis to analyze RNA expression data and establish a competitive regulatory network of circRNA-miRNA-mRNA during early osteogenic differentiation of hBMSCs. Furthermore, we verified the key circRNAs' important binding sites through in vitro studies. The objective of this research is to uncover detailed molecular mechanisms and potential biomarkers involved in BMSC osteogenic differentiation. 2. Results 2.1. Identification of Differentially Expressed circRNAs, miRNAs and mRNAs To investigate the early molecular events underlying osteogenic differentiation, we obtained three microarray datasets which were listed in Table S3. These datasets profiled the expression patterns at 7 days post chemical induction of osteogenic differentiation in human bone marrow-derived mesenchymal stromal cells (hBMSCs). We included mRNA, miRNA, and circRNA expression profiles of BMSCs undergoing osteogenesis and normal cells in our study. A total of 80 differentially expressed circRNAs (DEcircRNAs) were identified in the osteogenic induction group compared to the uninduced group in BMSCs at 7 days, with a significance threshold of P 0.5 (Fig. 1 a). Among these, 41 circRNAs were upregulated, while 39 were downregulated. Additionally, 98 differentially expressed miRNAs (DEmiRNAs) were detected during osteogenic differentiation ( P 0.5) (Fig. 1 b), with 41 upregulated and 57 downregulated DE-miRNAs. Furthermore, a total of 814 differentially expressed mRNAs (DEmRNAs) were identified using a significance threshold of P 1.2, comprising 478 upregulated and 336 downregulated DE-mRNAs (Fig. 1 c). Subsequently, volcano plots were generated using the pheatmap package, and 80 DE-circRNAs, 98 DE-miRNAs, and 814 DE-mRNAs were selected for further analysis. 2.2. Function Enrichment Analysis To explore the role of circRNAs as miRNA sponges in modulating the osteogenic differentiation of BMSCs, we utilized an online database to predict circRNAs corresponding to the identified miRNAs. Our analysis revealed that 61 DEcircRNAs interacted with 3,184 miRNAs from circbank. Furthermore, by intersecting the circRNAs-targeted miRNAs with the DEmiRNAs from GEO, we identified 56 overlapping miRNAs (Fig. 2 a). Subsequently, we predicted that 7,648 mRNAs contained binding sites for the overlapped miRNAs. Through further analysis, we detected 215 overlapping mRNAs by intersecting the miRNAs-targeted mRNAs with the DEmRNAs (Fig. 2 b). To elucidate the functional roles of these 215 mRNAs, we conducted GO enrichment analysis using the DAVID online database. Our analysis revealed that these mRNAs were significantly enriched in biological processes related to transcriptional regulation, proliferation, and differentiation ( P < 0.05) (Fig. 2 c). Notably, 35 of these mRNAs were specifically enriched in biological processes associated with osteogenesis and cell proliferation, including GO: 0008284 ~ positive regulation of cell proliferation, GO: 0001503 ~ ossification, GO: 0008285 ~ negative regulation of proliferation, and GO: 0002053 ~ positive regulation of mesenchymal cell proliferation. These processes are closely associated with osteogenesis, calcification, and cell differentiation. Consequently, we selected the 35 mRNAs enriched in these processes for further investigation. 2.3. Construction of the circRNA–miRNA–mRNA Interaction Network related to osteogenic differentiation Based on the analysis of differential expression in microarray data and the ceRNA mechanism, we identified a set of interconnected molecules to construct a circRNA-miRNA-mRNA network relevant to osteogenic differentiation. Utilizing published literature, we selected 15 mRNAs closely associated with stem cell differentiation. Among the 56 overlapping miRNAs, 17 were found to interact with the previously mentioned 15 mRNAs. Furthermore, out of the 61 differentially expressed circRNAs, 22 were found to interact with the 17 miRNAs. Consequently, we posit that these 22 circRNAs, 17 miRNAs, and 15 mRNAs mutually interact and are closely linked to hBMSCs osteogenic differentiation. Employing Cytoscape software, we constructed a ceRNA network diagram containing: circRNAs: hsa_circ_0001063, hsa_circ_0001600, hsa_circ_0002415, hsa_circ_0002474, hsa_circ_0003552, hsa_circ_0003563, hsa_circ_0003611, hsa_circ_0004418, hsa_circ_0005991, hsa_circ_0006006, hsa_circ_0007933, hsa_circ_0008621, hsa_circ_0016956, hsa_circ_0022502, hsa_circ_0034293, hsa_circ_0057104, hsa_circ_0057105, hsa_circ_0063756, hsa_circ_0068465, hsa_circ_0072387, hsa_circ_0072678, hsa_circ_0088062 miRNAs: hsa-miR-199b-5p, hsa-miR-15a-5p, hsa-miR-424-5p, hsa-miR-504-5p, hsa-miR-383-5p, hsa-miR-335-5p, hsa-miR-20b-5p, hsa-miR-200b-3p, hsa-miR-30c-2-3p, hsa-miR-30a-5p, hsa-miR-203a-3p, hsa-let-7i-5p, hsa-miR-942-5p, hsa-miR-9-3p, hsa-miR-335-3p, hsa-miR-3200-3p, hsa-miR-542-3p mRNAs: LIF, ZBTB16, VEGFA, SOST, SOD2, SMAD1, SFRP4, LRRC17, IL6, IGF2, FOXP1, FGF9, CLEC3B, BMP7, AREG (Fig. 2 d). 2.4. Validation of Key circRNAs and miRNAs in the ceRNA Network In the control group, hBMSCs were cultured in complete medium without osteogenic induction, whereas in the experimental group, hBMSCs were treated with osteogenic induction fluid for 7 days. RT-qPCR was performed to assess the expression levels of 11 molecules corresponding to differentially expressed circRNAs identified through bioinformatics analysis. Compared to the control group, the expression levels of hsa_circ_0001600, hsa_circ_0002415, hsa_circ_0063756, hsa_circ_0072678, and hsa_circ_0005991 were significantly upregulated in the 7-day osteogenic induction group, while the expression of hsa_circ_0008621 was downregulated ( P < 0.05) (Fig. 3 a). Similarly, compared to the control group, the expression levels of hsa-miR-20b-5p, hsa-miR-335-3p, hsa-miR-942-5p, hsa-miR-424-5p, and hsa-miR-542-3p were significantly decreased in the osteogenic induction group, whereas the expression of hsa-miR-203a-3p, hsa-miR-30a-5p, hsa-miR-30c-2-3p, and hsa-miR-199b-5p was increased ( P < 0.05) (Fig. 3 b). 2.5. The interaction between circRNAs and miRNAs within the ceRNA Network During the osteogenic differentiation of hBMSCs, the expression of hsa_circ_0005991 and hsa_circ_0001600 shows an increasing trend, indicating that the two molecules may be involved in the regulation of cell osteogenic differentiation. hsa_circ_0001600 and hsa_circ_0005991 were selected as candidate circRNAs. According to the circBank database prediction, hsa_circ_0001600 (circBank ID: hsa_circFKBP5_002) has one binding site (position: 739) with hsa-miR-542-3p in the miRanda algorithm, and four binding sites (positions: 3624, 752, 3629, 758) in the Targetscan algorithm. hsa_circ_0005991 (circBank ID: hsa_circAPBB2_013) has one binding site (position: 584) with hsa-miR-424-5p in the miRanda algorithm prediction, and two binding sites (positions: 598, 604) according to the Targetscan algorithm. hBMSCs were osteogenically induced for 0, 3, and 7 days, and qPCR was employed to assess the expression levels of hsa_circ_0001600, hsa-miR-542-3p, hsa_circ_0005991, and hsa-miR-424-5p. The findings revealed a progressive increase in the expression of hsa_circ_0001600 throughout osteogenic induction (Fig. 3 c), while the expression of hsa-miR-542-3p decreased gradually with prolonged osteogenic induction. Additionally, the expression of hsa_circ_0005991 exhibited a gradual increase over the osteogenic induction period (Fig. 3 d), whereas the expression of hsa-miR-424-5p decreased progressively with the extension of osteogenic induction time. The experimental design included the use of siRNA to suppress the expression of hsa_circ_0001600. Initial investigation was conducted to determine the optimal siRNA, transfection concentration, and duration. The determined concentration of the target gene siRNA was 50nM, and the transfection duration was 48 hours. qPCR analysis indicated a significant reduction in hsa_circ_0001600 expression with si-hsa_circ_0001600 2 in hsa_circ_0001600 siRNA, achieving a knockdown efficiency of 70% (Fig. 3 e). The hsa_circ_0001600 siRNA transfection knockdown group exhibited an increase in hsa-miR-542-3p expression compared to the negative control group (Fig. 3 f). 2.6. Downregulation of hsa_circ_0001600 expression reduces the osteogenic differentiation capacity of hBMSCs The circular RNA hsa_circ_0001600 is generated through the reverse splicing of the FKBP5 gene, representing a newly discovered circular molecule with unknown biological function and molecular mechanism (Fig. 4 a). Compared to linear RNAs, circRNAs are more stable and longer-lasting because they lack a free end for RNA enzyme-mediated degradation. Circular RNAs are generated by the back-splicing process, and they are covalently closed loops, keeping them highly stable to RNase R digestion. Using qPCR, the expression changes of hsa_circ_0001600 and its parental gene FKBP5 in RNase R-digested total RNA (RNase R+) were analyzed. The non-digested group (RNase R-) served as the control group, with the internal reference in the RNase R- group used as the calculation standard. The qPCR results demonstrated no significant alteration in the expression level of hsa_circ_0001600 in the experimental group compared to the control group. However, there was a notable reduction in the expression of FKBP5, indicating that hsa_circ_0001600 may be resistant to RNase R, whereas its parental gene FKBP5 is predominantly digested by RNase R (Fig. 4 b). hBMSCs were seeded into 6-well plates and induced with osteogenic induction medium for 14 days. Throughout this period, siRNA (si-hsa_circ_0001600 and si-NC) was refreshed every 3 days. Alizarin Red staining was performed for both the control and experimental groups. Microscopic observation revealed a significant reduction in red staining in the hsa_circ_0001600 siRNA knockdown group compared to the control group. Furthermore, after transfecting hBMSCs with hsa_circ_0001600 siRNA for 2 days, the medium was switched to osteogenic induction medium for 3 days. The control group comprised hBMSCs transfected with negative control siRNA for 2 days, followed by a 3-day osteogenic induction. ALP staining was conducted for both the control and experimental groups. Microscopic observation revealed a significant reduction in red staining in the hsa_circ_0001600 siRNA knockdown group compared to the control group, indicating a clear decrease in ALP expression (Fig. 4 c). qPCR analysis was carried out for both the control and experimental groups, demonstrating reduced expression of osteogenic-related genes COL1A1 and RUNX2 in the knockdown group with hsa_circ_0001600 siRNA transfection, as compared to the negative control group (Fig. 4 d). Furthermore, Western Blot analysis showed decreased expression of osteogenic-related proteins COL1A1, OCN, and RUNX2 in the knockdown group with hsa_circ_0001600 siRNA transfection, as compared to the negative control (Fig. 4 e, 4 f). The raw bands are shown in Figure S1 . 3. Discussion In the bioinformatics analysis section of this study, we gathered gene expression matrix data of circRNAs, miRNAs, and mRNAs during the early osteogenic differentiation of hBMSCs induced by osteogenic induction medium for 7 days. Through predictive modeling, we identified 22 circRNAs, 17 miRNAs, and 15 mRNAs predicted to interact with each other, successfully constructing a ceRNA network relevant to hBMSCs osteogenic differentiation. Among the identified mRNAs, members of the Bone Morphogenetic Protein (BMP) family, such as BMP7, known for their upregulation during BMSCs osteogenic differentiation, were included [ 18 ] . Additionally, Vascular Endothelial Growth Factor A (VEGFA) and Fibroblast Growth Factor 9 (FGF9) were implicated in the network and associated with osteoblast differentiation. VEGFA, as an inducer of angiogenesis, has been shown to regulate bone repair and regeneration by affecting the generation of bone vasculature [ 19 ] . FGF9 is a factor regulating skeletal development, playing a significant role in skeletal development and cartilage formation. Secreted Frizzled-Related Protein 4 (SFRP4) can directly activate the canonical Wnt signaling pathway, and through regulating osteoblasts and osteoclasts, it plays a key role in bone development and remodeling, and reducing its expression can prevent age-related bone loss [ 20 ] . Among the predicted 17 miRNAs, studies have shown that downregulation of miR-542-3p can target BMP7 to promote mouse vascular smooth muscle cell and osteoblast osteogenic differentiation [ 21 ],[ 22 ] . ZEB1 and VEGF can be targeted by miR-942-5p, thereby promoting BMSCs osteogenesis and vasculogenesis [ 23 ] . Research has indicated a close association of hsa-miR-335-5p, hsa-miR-200b-3p, and hsa-miR-335-3p with osteoarthritis [ 24 ] . Among the 22 circRNAs unearthed in this study, hsa_circ_0008621 and hsa_circ_0072387 can inhibit glioma progression through miR-338-5p/IKBIP [ 25 ] . hsa_circ_0072387 is a novel circRNA that can serve as a valuable biomarker for oral squamous cell carcinoma [ 26 ],[ 27 ] . However, the regulatory roles of the screened circRNAs in osteogenic differentiation are not yet clear, and further research on their regulatory mechanisms is needed. Based on the constructed ceRNA network, 11 circRNAs and 11 miRNAs were selected for qPCR validation of expression level changes. According to the results and molecular function, two sets of relationships were selected for hsa_circ_0001600, hsa-miR-542-3p, and hsa_circ_0005991, hsa-miR-424-5p. In vitro cell experiments proved that hsa_circ_0001600 may play an important role in the osteogenic differentiation of hBMSCs, and its possible mechanism is the targeted regulation of hsa-miR-542-3p. hsa_circ_0001600 is a circular RNA formed by the reverse cleavage of the FKBP5 gene, with a length of 4534 base pairs. CircRNA can also directly regulate the expression of the host gene. The host gene FKBP5 of hsa_circ_0001600 is a molecular associated with heat shock proteins and has a strong stress response [ 28 ] . Mutations in FKBP5 are significantly associated with the risk of mental disorders such as anxiety, depression, and post-traumatic stress disorder (PTSD) [ 29 ] . Studies have shown that FKBP5 also plays a positive role in the early osteogenic differentiation of bone marrow mesenchymal stem cells and adipose stem cells, as well as in cartilage and adipogenic differentiation [ 30 ],[ 31 ] . Furthermore, FKBP5 mutations may lead to Paget's disease by affecting osteoclast formation [ 32 ] . Overall, hsa_circ_0001600 may regulate osteogenic differentiation by directly regulating the host gene. Meanwhile, qPCR proves that hsa-miR-542-3p is negatively correlated with BMSCs osteogenic differentiation and knocking down hsa_circ_0001600 will increase the expression of hsa-miR-542-3p. Previous studies have shown that hsa-miR-542-3p inhibits the proliferation, migration, and invasion of tumor cells such as osteosarcoma and glioma cells [ 33 ]–[ 35 ] . On the other hand, miR-542-3p positively regulates differentiation and regulates osteogenesis under conditions of bone loss [ 36 ] . At the same time, hsa-miR-542-3p has strong osteogenic potential by bioinformatics prediction targeting the highly bone-inducing BMP7. Therefore, we speculate that hsa-miR-542-3p is regulated by hsa_circ_0001600 to inhibit the osteogenic differentiation of hBMSCs. 4. Methods 4.1. Dataset Collection The microarray data involved in this study were obtained from GEO(Gene Expression Omnibus) database(( http://www.ncbi.nlm.nih.gov/geo/ ). The circRNA, miRNA and mRNA expression profiles downloaded from GSE135883 (GPL21825 Arraystar Human CircRNA microarray V2,6 pairs of hBMSCs), GSE135586 (GPL18573 Illumina NextSeq 500 (Homo sapiens), 6 pairs of hBMSCs) and GSE18043 (GPL570, Affymetrix Human Genome U133 Plus 2.0 Array, 3 pairs of hBMSCs), respectively. The inclusion criteria for these three groups are hBMSCs chemically induced chemically osteogenic differentiation for 7 days. 4.2. Differential Expression Analysis The expression matrix used FastQC to complete quality checking. By using R limma package Subsequently, the DEcircRNAs, DEmiRNAs, and DEmRNAs were screened out and drawn with the R package pheatmap. The criteria of P 1.2 were identified as significantly differentially expressed mRNAs (DE-mRNAs). For circRNAs and miRNAs, we utilized the criteria of P 0.5 to identify significantly differentially expressed circRNAs (DE-circRNAs) and miRNAs (DE-miRNAs), respectively. Subsequently. The pheatmap package in R software was used to generate volcano plots for the differentially expressed genes. 4.3. Construction of ceRNA network To discover and establish the potential relationship between the DEcircRNAs, DEmiRNAs, and DEmRNAs, two databases were selected named circBank ( http://www.circbank.cn ) and miRTarBase ( http://miRTarBase.cuhk.edu.cn/ ) [ 17 ] to predict the targeting miRNAs and mRNAs. The circRNA–miRNA–mRNA network was constructed with intersection of miRNA and mRNA predicted by online databases and DEcircRNAs, DEmiRNAs, and DEmRNAs. A ceRNA network was shown using Cytoscape 3.7.2 software. 4.4. GO and KEGG enrichment analyses To find genes that are closely related to our research, we used the DAVID database ( https://david.ncifcrf.gov ) to perform Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis of DEmRNAs. 4.5. BMSCs culture and osteoblast differentiation The bone marrow-derived mesenchymal stem cells (three donors) were purchased from ScienCell Research Laboratories (Carlsbad, CA, USA). The BMSCs were cultured in mesenchymal stem cell medium (MSCM) (ScienCell, CA, United States) containing 5% fetal bovine serum, 1% penicillin-streptomycin, and 1% mesenchymal stem cell growth supplement. The culture medium was replenished every 2–3 days, and the cells were maintained at 37°C in a 5% CO2 cell culture incubator. Subsequent experiments utilized hBMSCs from the 3rd to 5th passages. For osteogenic differentiation, hBMSCs were seeded in six-well plates at a density of 1×10 4 cells/cm 2 . Upon reaching 80–90% confluency, the routine media was replaced with osteogenic media containing 50µg/ml ascorbic acid, 10mM β-glycerophosphate (Sigma, USA), 10 nM dexamethasone(Invitrogen, USA), 10% FBS, 1% penicillin-streptomycin and 1% glutamine. The media was replenished every 2–3 days. After 3 days or 7 days, osteogenic differentiation was evaluated by ALP staining and qPCR. 4.6. Alizarin Red Staining BMSCs osteogenic capacity was detected using alizarin red staining. The hBMSCs were inoculated into 6-well plates and induced with osteogenic induction medium for 14 days, during which siRNA (si-hsa_circ_0001600 and si-NC) was re-placed every 3 days. The plates were rinsed with PBS, fixed with 4% paraformaldehyde for 30 min, washed with ddH2O, and then stained with 1% alizarin red aqueous solution (Solarbio, Beijing, China) for 15 min at room temperature, then washed with ddH2O to observe the staining under the microscope. 4.7. Alkaline Phosphatase (ALP) Staining ALP activity was analyzed using the NBT/BCIP staining kit (Beyotime, Shanghai, China). hBMSCs were seeded in 6-well plates and cultured in osteogenic medium for 7 days. Cells were washed with PBS and fixed with 4% polyformaldehyde for 30min and stained for 20min at 37℃. 4.8. Real-Time Quantitative Reverse Transcriptase PCR (RT-qPCR) and RNase R enzyme digestion RT-qPCR was used to check the expression of miRNAs, circRNAs, and mRNAs and to confirm the expression of osteogenic differentiation markers. The hBMSCs nuclear and cytoplasmic RNA was isolated with the TRIzol reagent (Invitrogen, USA) at osteogenic 3 days or 7 days. For cDNA synthesis, a stem loop reverse transcription kit (Vazyme, China) was used for reversing mature miRNA. circRNAs and mRNA were reverse transcribed using HiScript Reverse Transcriptase (Vazyme, China). The qPCR for detecting gene expression levels was performed by SYBR Green PCR Mix (Vazyme, China) and a QuantStudioTM 3 System (Applied Biosystems). The GAPDH (for mRNA and circRNA) and U6 (for miRNA) were used as endogenous controls respectively. All primers used in this study were listed in Table S1 . After extracting total circRNA, the circRNA was treated with 2U/µg RNase R(GeneSeed, China)digested at 37°C for 10min to digest most of the linear RNA. 4.9. Cell Transfection The si-hsa_circ_0001600 and si-hsa_circ_0005991 and their control vector si-NC were designed and synthesized by Ribobio (Guangzhou, China). The siRNA target sequences were listed in Table S2. The BMSCs were transfected with siRNA(50nM) and si-NC in 6-well plates until 70–80% confluence with riboFECTTM CP kit (Ribobio, Guangzhou, China). The transfection was conducted for up to 48 hours, unless specified otherwise, followed by subsequent cell treatments. 4.10. Western blot analysis The BMSCs were harvested and lysed in RIPA lysis buffer (Beyotime, Shanghai, China) after washing twice by PBS. and the corresponding proteins were determined by the BCA protein analysis kit (Beyotime), according to the manufacturer’s guide. Subsequently, equal quantities of protein samples were added to 12% SDS-PAGE and onto polyvinylidene difluoride (PVDF) membranes after separation. Then, the PVDF membranes were incubated with primary antibody: against RUNX2 (1:1000, Abcam), OCN (1:1000, Abcam), COL1A1 (1:1000, Proteintech), and β-ACTIN (1:1000, Abcam) overnight at 4°C. The membranes were incubated with corresponding secondary antibodies for 1h after washing with PBST three times. The band intensity was measured by Image J software. The signal of all target bands was normalized to that of the β-ACTIN band. 4.11. Statistical Analysis All statistical calculations were performed with GraphPad Prism software (version 8.0). The Student’s t-test, Fisher’s exact test, χ 2 test, Pearson correlation, or one-way ANOVA were used for statistical analyses in our search. Meanwhile, data are presented as means ± standard deviation (SD). P < 0.05 were considered significant statistically. Declarations Author Contributions: Study concept and design, J.Z., Q.Y. and O.L; experiment performed, K.S. and X.C.; data analysis and visualization, K.S. and X.C.; writing—original draft preparation, K.S.; writing—review and editing, J.Z., Q.Y. and O.L.; modification of figures and manuscript, O.L. Besides, K.S. and X.C. contributed equally to this work; Q.Y. and O.L. should be considered joint senior authors. All authors have read and agreed to the published version of the manuscript. Funding: This research was funded by Health and Family Planning Commission of Hunan Province, grant number 20201660; Health Commission of Hunan Province, grant number 202108031817; Beijing Municipal Natural Science Foundation, grant number 7222079. Institutional Review Board Statement: Not applicable. Informed Consent Statement: Not applicable. Data Availability Statement: The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found at: https://www.ncbi.nlm.nih.gov/, GSE135883; https://www.ncbi.nlm.nih.gov/, GSE135586; https://www.ncbi.nlm.nih.gov/, GSE18043. Acknowledgments: The authors acknowledge other participants in our laboratory for their active help in this study. Conflicts of Interest: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. 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Understanding the Molecular Mechanisms Underpinning Gene by Environment Interactions in Psychiatric Disorders: The FKBP5 Model. Biol. Psychiatry 2018 , 83 (10), 821–830. DOI:10.1016/j.biopsych.2018.01.021. Criado-Marrero, M.; Rein, T.; Binder, E.B.; et al. Hsp90 and FKBP51: Complex Regulators of Psychiatric Diseases. Philos. Trans. R. Soc. B Biol. Sci. 2018 , 373 (1738), 20160532. DOI:10.1098/rstb.2016.0532. Liu, T.M.; Martina, M.; Hutmacher, D.W.; et al. Identification of Common Pathways Mediating Differentiation of Bone Marrow- and Adipose Tissue-Derived Human Mesenchymal Stem Cells into Three Mesenchymal Lineages. Stem Cells 2007 , 25 (3), 750–760. DOI:10.1634/stemcells.2006-0394. Kuçi, S.; Kuçi, Z.; Schäfer, R.; et al. Molecular Signature of Human Bone Marrow-Derived Mesenchymal Stromal Cell Subsets. Sci. Rep. 2019 , 9 (1), 1774. DOI:10.1038/s41598-019-38517-7. Lu, B.; Jiao, Y.; Wang, Y.; et al. A FKBP5 Mutation Is Associated with Paget’s Disease of Bone and Enhances Osteoclastogenesis. Exp. Mol. Med. 2017 , 49 (5), e336–e336. DOI:10.1038/emm.2017.64. Cai, W.; Xu, Y.; Zuo, W.; et al. MicroR-542-3p Can Mediate ILK and Further Inhibit Cell Proliferation, Migration and Invasion in Osteosarcoma Cells. Aging 2019 , 11 (1), 18–32. DOI:10.18632/aging.101698. Jia, Z.; Wang, Y.; Sun, X.; et al. Effect of lncRNA XLOC_005950 Knockout by CRISPR/Cas9 Gene Editing on Energy Metabolism and Proliferation in Osteosarcoma MG63 Cells Mediated by hsa‑miR‑542‑3p. Oncol. Lett. 2021 , 22 (3), 669. DOI:10.3892/ol.2021.12930. Luo, H.; Yi, T.; Huang, D.; et al. circ_PTN Contributes to -Cisplatin Resistance in Glioblastoma via PI3K/AKT Signaling through the miR-542-3p/PIK3R3 Pathway. Mol. Ther. - Nucleic Acids 2021 , 26 , 1255–1269. DOI:10.1016/j.omtn.2021.08.034. Zhang, Y.L.; Liu, L.; Su, Y.W.; et al. miR-542-3p Attenuates Bone Loss and Marrow Adiposity Following Methotrexate Treatment by Targeting sFRP-1 and Smurf2. Int. J. Mol. Sci. 2021 , 22 (20), 10988. DOI:10.3390/ijms222010988. Additional Declarations No competing interests reported. Supplementary Files SupplementaryTable.docx Supplementary Materials: The following supporting information can be downloaded at: www.mdpi.com/xxx. Table S1: Sequences of gene primer applied for RT-PCR; Table S2: siRNA Target Sequence; Table S3: Basic Information of the Three Microarray Datasets from GEO Database; Figure S1: Western Blot Raw Bands. Cite Share Download PDF Status: Published Journal Publication published 18 Oct, 2024 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 24 Jul, 2024 Reviews received at journal 14 Jul, 2024 Reviews received at journal 11 Jul, 2024 Reviewers agreed at journal 04 Jul, 2024 Reviewers agreed at journal 03 Jul, 2024 Reviewers invited by journal 03 Jul, 2024 Editor assigned by journal 03 Jul, 2024 Editor invited by journal 03 Jul, 2024 Submission checks completed at journal 02 Jul, 2024 First submitted to journal 19 Jun, 2024 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. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4603272","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":326715643,"identity":"5145d7e7-202e-449f-8d32-516a5b911e8f","order_by":0,"name":"Kaixin Su","email":"","orcid":"","institution":"Central South University","correspondingAuthor":false,"prefix":"","firstName":"Kaixin","middleName":"","lastName":"Su","suffix":""},{"id":326715644,"identity":"656f77d7-1a7d-45b0-85b8-bd52134e0f34","order_by":1,"name":"Xinyan Cui","email":"","orcid":"","institution":"Central South University","correspondingAuthor":false,"prefix":"","firstName":"Xinyan","middleName":"","lastName":"Cui","suffix":""},{"id":326715645,"identity":"dfdc169e-ea19-4ef5-9702-e2dc4e911a10","order_by":2,"name":"Jian Zhou","email":"","orcid":"","institution":"Capital Medical University","correspondingAuthor":false,"prefix":"","firstName":"Jian","middleName":"","lastName":"Zhou","suffix":""},{"id":326715646,"identity":"b22d94e4-71cf-487b-b0aa-e854145fdf3c","order_by":3,"name":"Qiao Yi","email":"","orcid":"","institution":"Central South University","correspondingAuthor":false,"prefix":"","firstName":"Qiao","middleName":"","lastName":"Yi","suffix":""},{"id":326715647,"identity":"e149a4a5-39a8-4f39-8328-45f3c101bed5","order_by":4,"name":"Ousheng Liu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA4UlEQVRIiWNgGAWjYBACPmYwdQCImQ8wwNn4ABtCC1sCkVoQyngMiNTCzmP4mOfPHTlz/jUfP/5sY5Dju5HA+OFjDj6H8Rgb87Y9M7ac8XazNG8bg7HkjQRmyZnb8Goxk+ZtOJy44cbZbcyMbQxARgIbMy8hLTx/DtdvuHHmGSPQYfVEamE7nGBwvoeNAeiwBAPCWtiKDee2HTbccIPNWJrnnIThzDMPm/H6hZ//8MYHb/4cljc4f/jhxx9lNvJ8x5MPfviIRwsCSCSASSBmbCBGPci+A0QqHAWjYBSMghEHAOuoTiMqWW4dAAAAAElFTkSuQmCC","orcid":"","institution":"Central South University","correspondingAuthor":true,"prefix":"","firstName":"Ousheng","middleName":"","lastName":"Liu","suffix":""}],"badges":[],"createdAt":"2024-06-19 05:12:14","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4603272/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4603272/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-024-76136-z","type":"published","date":"2024-10-18T15:57:36+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":60984373,"identity":"525353bf-0cab-4011-9d4a-fb31e223d1cf","added_by":"auto","created_at":"2024-07-24 09:46:27","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":151778,"visible":true,"origin":"","legend":"\u003cp\u003eThe volcano plot shows the differential expression of circRNAs, miRNAs, and mRNAs between the normal culture group and the osteogenic induction group hBMSCs. (\u003cstrong\u003ea\u003c/strong\u003e) DE-circRNAs (\u003cem\u003eP\u003c/em\u003e\u0026lt;0.05, |log2 fold change|\u0026gt;0.5); (\u003cstrong\u003eb\u003c/strong\u003e) DE-miRNAs (\u003cem\u003eP\u003c/em\u003e\u0026lt;0.05, |log2 fold change|\u0026gt;0.5); (\u003cstrong\u003ec\u003c/strong\u003e) DE-mRNAs(\u003cem\u003eP\u003c/em\u003e\u0026lt;0.05, |log2 fold change|\u0026gt;1.2); Red dots represent upregulated gene expression, blue dots represent downregulated gene expression.\u003c/p\u003e","description":"","filename":"Onlinefloatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-4603272/v1/dc0eb9f8eb30fe2ac9f81f99.png"},{"id":60984372,"identity":"8ac6e67c-4d4b-4473-93c4-7473b7113d76","added_by":"auto","created_at":"2024-07-24 09:46:27","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":363164,"visible":true,"origin":"","legend":"\u003cp\u003eConstruction of the circRNA–miRNA–mRNA Interaction Network. (\u003cstrong\u003ea\u003c/strong\u003e) Venn diagram of the intersection of molecules predicted to be combined with circRNAs and DE-miRNAs by circBank database; (\u003cstrong\u003eb\u003c/strong\u003e) Venn diagram of the intersection of molecules predicted to be combined with miRNAs and DE-mRNAs by mirTarBase database. (\u003cstrong\u003ec\u003c/strong\u003e) GO function annotation bar graph(GO enrichment analysis includes Cellular Component (CC), Molecular Function (MF), and Biological Process (BP); P \u0026lt; 0.05.). (\u003cstrong\u003ed\u003c/strong\u003e) ceRNA interaction network diagram of circRNA-miRNA-mRNA (Green ellipses represent circRNA, blue rectangles represent miRNA, and orange rhombuses represent mRNA).\u003c/p\u003e","description":"","filename":"Onlinefloatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-4603272/v1/5ad2922f2ba6e387fd0f1f8c.png"},{"id":60985220,"identity":"caa4f27a-4882-43c6-a672-997de847ff9f","added_by":"auto","created_at":"2024-07-24 09:54:27","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":332241,"visible":true,"origin":"","legend":"\u003cp\u003eCertain circRNA molecules involved in the regulation of BMSC osteogenic differentiation. (\u003cstrong\u003ea\u003c/strong\u003e) qPCR detection of the expression level changes of circRNAs screened by bioinformatics analysis after osteogenic differentiation induction. (\u003cstrong\u003eb\u003c/strong\u003e) qPCR detects the expression level changes of miRNAs screened by bioinformatics analysis after osteogenic differentiation induction. (\u003cstrong\u003ec\u003c/strong\u003e) qPCR detects the expression level changes of hsa_circ_0001600 and hsa-miR-542-3p during osteogenic differentiation at 0 days, 3 days, and 7 days. (\u003cstrong\u003ed\u003c/strong\u003e) qPCR detects the expression level changes of hsa_circ_0005991 and hsa-miR-424-5p during osteogenic differentiation at 0 days, 3 days, and 7 days. (\u003cstrong\u003ee\u003c/strong\u003e) Transfection of hsa_circ_0001600 expression in hBMSCs at a siRNA concentration of 50nM for 48 hours. (\u003cstrong\u003ef\u003c/strong\u003e) qPCR detects the changes in hsa-miR-542-3p levels in the si-hsa_circ_0001600 2 days after transfection. Compared with the si-NC, the expression of hsa-miR-542-3p increased in the si-hsa_circ_0001600. (si-hsa_circ_0001600 is the hsa_circ_0001600 siRNA transfected knockdown group, si-NC is the negative control group; * represents \u003cem\u003eP\u003c/em\u003e\u0026lt;0.05; ** represents p\u0026lt;0.01; *** represents p\u0026lt;0.001, **** represents p\u0026lt;0.0001)\u003c/p\u003e","description":"","filename":"Onlinefloatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-4603272/v1/dee47db4aa1a0f002d473ccc.png"},{"id":60985222,"identity":"aa606144-8845-4e5a-b3d5-885ad8f50e59","added_by":"auto","created_at":"2024-07-24 09:54:27","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":248558,"visible":true,"origin":"","legend":"\u003cp\u003e(\u003cstrong\u003ea\u003c/strong\u003e) hsa_circ_0001600 generation model diagram; (\u003cstrong\u003eb\u003c/strong\u003e) qPCR detects the expression of hsa_circ_0001600 and FKBP5 before and after RNase R treatment. RNase R+ represents the group treated with RNase R enzyme, RNase R- represents the group without RNase R en-zyme treatment; (\u003cstrong\u003ec\u003c/strong\u003e) The left side shows alizarin red staining after 14 days of osteogenic induction, and the right side shows ALP staining after 3 days of osteogenic induction. (i) and (iii) are the control group, and (ii) and (iv) are the hsa_circ_0001600 siRNA transduction knockdown group; the results showed that compared with the control group, the degree of alizarin red and ALP staining was significantly weakened in the hsa_circ_0001600 siRNA transduction knockout group. (\u003cstrong\u003ed\u003c/strong\u003e) qPCR detection of changes in osteogenesis-related gene expression levels after 3 days of osteogenic induction. In comparison to the si-NC, the expression of COL1A1 and RUNX2 was downregulated in the si-hsa_circ_0001600. (\u003cstrong\u003ee\u003c/strong\u003e) Western Blot detection of protein changes after 3 days of osteogenic induction; the band diagram shows that the bands of COL1A1, OCN, and RUNX2 in the si-hsa_circ_0001600 are noticeably lighter compared to the si-NC. (\u003cstrong\u003ef\u003c/strong\u003e) The protein quantification diagram shows reduced protein expression levels of COL1A1, OCN, and RUNX2 in the si-hsa_circ_0001600 compared to the si-NC. (si-hsa_circ_0001600 is the hsa_circ_0001600 siRNA transfected knockdown group, si-NC is the negative control group; * represents \u003cem\u003eP\u003c/em\u003e\u0026lt;0.05; ** represents p\u0026lt;0.01; *** represents p\u0026lt;0.001, **** represents p\u0026lt;0.0001)\u003c/p\u003e","description":"","filename":"Onlinefloatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-4603272/v1/ee3a93e3b905fc6dccf7d871.png"},{"id":67148963,"identity":"33962a47-552d-4493-a939-f743f4923e61","added_by":"auto","created_at":"2024-10-21 16:10:23","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1719896,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4603272/v1/42dd068f-0d6a-4529-92c5-f2d1daa844e0.pdf"},{"id":60985786,"identity":"56646182-aa76-4217-9e61-5e72c2ba08af","added_by":"auto","created_at":"2024-07-24 10:02:27","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":23848,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary Materials: \u003c/strong\u003eThe following supporting information can be downloaded at: \u003cu\u003ewww.mdpi.com/xxx.\u003c/u\u003eTable S1: Sequences of gene primer applied for RT-PCR; Table S2: siRNA Target Sequence; Table S3: Basic Information of the Three Microarray Datasets from GEO Database; Figure S1: Western Blot Raw Bands.\u003c/p\u003e","description":"","filename":"SupplementaryTable.docx","url":"https://assets-eu.researchsquare.com/files/rs-4603272/v1/e6e7ac6c1ebdac775e5a45b0.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Construction of an interactome network among circRNA-miRNA-mRNA reveals new biomarkers in hBMSCs osteogenic differentiation","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eMesenchymal stem cells (MSCs) hold a prominent position in regenerative medicine due to their multipotency, self-renewal capabilities, and low immunogenicity. MSCs possess the remarkable ability to differentiate into various cell types, including osteoblasts, adipocytes, and chondrocytes, both in vivo and in vitro\u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]\u003c/sup\u003e. Among MSCs, human bone marrow mesenchymal stem cells (hBMSCs) are extensively utilized in clinical trials for bone tissue regeneration and show promising therapeutic outcomes for skeletal disorders such as bone defects and osteoporosis\u003csup\u003e[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eGlucocorticoids and dexamethasone (DEX) are commonly employed clinically to induce osteogenic differentiation in BMSCs\u003csup\u003e[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]\u003c/sup\u003e. In recent years, there has been significant attention directed towards understanding the osteogenic differentiation of BMSCs, which involves a myriad of transcription factors and signaling pathways\u003csup\u003e[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eCompeting endogenous RNA (ceRNA), proposed in 2011, introduced a novel mechanism of RNA interaction, expanding the biological functions of mRNA and non-coding RNA (ncRNA)\u003csup\u003e[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]\u003c/sup\u003e. Besides, circular RNAs (circRNAs) or long non-coding RNAs (lncRNAs) primarily act as molecular sponges for miRNAs, adsorbing miRNAs and relieving their suppressive effects on target mRNA\u003csup\u003e[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003c/sup\u003e. CircRNA, characterized by a covalently closed, circular structure, is derived from the reverse splicing of mRNA precursors and has emerged as a significant component of the transcriptome\u003csup\u003e[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/sup\u003e. In recent years, the functional and clinical significance of ceRNA networks in various diseases, including cancer, cardiovascular diseases, and neurological disorders, has been increasingly recognized, offering potential avenues for disease treatment research\u003csup\u003e[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/sup\u003e. In 2017, Yu et al. first reported the correlation between circRNAs and stem cell differentiation, confirming that downstream circRNAs regulate stem cell differentiation through the ceRNA mechanism\u003csup\u003e[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/sup\u003e. Recent studies have identified numerous circRNAs that exhibit differential expression during MSC osteogenesis, some of which have been shown to regulate the osteogenic differentiation process\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 specific roles of many circRNAs and their associated ceRNA networks in BMSC osteogenic differentiation remain unexplored. Therefore, to gain a comprehensive understanding of the impact of the ceRNA mechanism on BMSC osteogenic differentiation, it is imperative to elucidate the circRNA-miRNA-mRNA regulatory network.\u003c/p\u003e \u003cp\u003eIn this study, we employed bioinformatic analysis to analyze RNA expression data and establish a competitive regulatory network of circRNA-miRNA-mRNA during early osteogenic differentiation of hBMSCs. Furthermore, we verified the key circRNAs' important binding sites through in vitro studies. The objective of this research is to uncover detailed molecular mechanisms and potential biomarkers involved in BMSC osteogenic differentiation.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e"},{"header":"2. Results","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Identification of Differentially Expressed circRNAs, miRNAs and mRNAs\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eTo investigate the early molecular events underlying osteogenic differentiation, we obtained three microarray datasets which were listed in Table S3. These datasets profiled the expression patterns at 7 days post chemical induction of osteogenic differentiation in human bone marrow-derived mesenchymal stromal cells (hBMSCs). We included mRNA, miRNA, and circRNA expression profiles of BMSCs undergoing osteogenesis and normal cells in our study.\u003c/p\u003e \u003cp\u003eA total of 80 differentially expressed circRNAs (DEcircRNAs) were identified in the osteogenic induction group compared to the uninduced group in BMSCs at 7 days, with a significance threshold of \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 and |log2 fold change|\u0026gt;0.5 (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea). Among these, 41 circRNAs were upregulated, while 39 were downregulated. Additionally, 98 differentially expressed miRNAs (DEmiRNAs) were detected during osteogenic differentiation (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, |log2 fold change|\u0026gt;0.5) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb), with 41 upregulated and 57 downregulated DE-miRNAs. Furthermore, a total of 814 differentially expressed mRNAs (DEmRNAs) were identified using a significance threshold of \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 and |log2 fold change|\u0026gt;1.2, comprising 478 upregulated and 336 downregulated DE-mRNAs (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ec).\u003c/p\u003e \u003cp\u003eSubsequently, volcano plots were generated using the pheatmap package, and 80 DE-circRNAs, 98 DE-miRNAs, and 814 DE-mRNAs were selected for further analysis.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Function Enrichment Analysis\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eTo explore the role of circRNAs as miRNA sponges in modulating the osteogenic differentiation of BMSCs, we utilized an online database to predict circRNAs corresponding to the identified miRNAs. Our analysis revealed that 61 DEcircRNAs interacted with 3,184 miRNAs from circbank. Furthermore, by intersecting the circRNAs-targeted miRNAs with the DEmiRNAs from GEO, we identified 56 overlapping miRNAs (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea). Subsequently, we predicted that 7,648 mRNAs contained binding sites for the overlapped miRNAs. Through further analysis, we detected 215 overlapping mRNAs by intersecting the miRNAs-targeted mRNAs with the DEmRNAs (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb).\u003c/p\u003e \u003cp\u003eTo elucidate the functional roles of these 215 mRNAs, we conducted GO enrichment analysis using the DAVID online database. Our analysis revealed that these mRNAs were significantly enriched in biological processes related to transcriptional regulation, proliferation, and differentiation (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec). Notably, 35 of these mRNAs were specifically enriched in biological processes associated with osteogenesis and cell proliferation, including GO: 0008284\u0026thinsp;~\u0026thinsp;positive regulation of cell proliferation, GO: 0001503\u0026thinsp;~\u0026thinsp;ossification, GO: 0008285\u0026thinsp;~\u0026thinsp;negative regulation of proliferation, and GO: 0002053\u0026thinsp;~\u0026thinsp;positive regulation of mesenchymal cell proliferation. These processes are closely associated with osteogenesis, calcification, and cell differentiation. Consequently, we selected the 35 mRNAs enriched in these processes for further investigation.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Construction of the circRNA\u0026ndash;miRNA\u0026ndash;mRNA Interaction Network related to osteogenic differentiation\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eBased on the analysis of differential expression in microarray data and the ceRNA mechanism, we identified a set of interconnected molecules to construct a circRNA-miRNA-mRNA network relevant to osteogenic differentiation. Utilizing published literature, we selected 15 mRNAs closely associated with stem cell differentiation. Among the 56 overlapping miRNAs, 17 were found to interact with the previously mentioned 15 mRNAs. Furthermore, out of the 61 differentially expressed circRNAs, 22 were found to interact with the 17 miRNAs. Consequently, we posit that these 22 circRNAs, 17 miRNAs, and 15 mRNAs mutually interact and are closely linked to hBMSCs osteogenic differentiation. Employing Cytoscape software, we constructed a ceRNA network diagram containing:\u003c/p\u003e \u003cp\u003ecircRNAs: hsa_circ_0001063, hsa_circ_0001600, hsa_circ_0002415, hsa_circ_0002474, hsa_circ_0003552, hsa_circ_0003563, hsa_circ_0003611, hsa_circ_0004418, hsa_circ_0005991, hsa_circ_0006006, hsa_circ_0007933, hsa_circ_0008621, hsa_circ_0016956, hsa_circ_0022502, hsa_circ_0034293, hsa_circ_0057104, hsa_circ_0057105, hsa_circ_0063756, hsa_circ_0068465, hsa_circ_0072387, hsa_circ_0072678, hsa_circ_0088062\u003c/p\u003e \u003cp\u003emiRNAs: hsa-miR-199b-5p, hsa-miR-15a-5p, hsa-miR-424-5p, hsa-miR-504-5p, hsa-miR-383-5p, hsa-miR-335-5p, hsa-miR-20b-5p, hsa-miR-200b-3p, hsa-miR-30c-2-3p, hsa-miR-30a-5p, hsa-miR-203a-3p, hsa-let-7i-5p, hsa-miR-942-5p, hsa-miR-9-3p, hsa-miR-335-3p, hsa-miR-3200-3p, hsa-miR-542-3p\u003c/p\u003e \u003cp\u003emRNAs: LIF, ZBTB16, VEGFA, SOST, SOD2, SMAD1, SFRP4, LRRC17, IL6, IGF2, FOXP1, FGF9, CLEC3B, BMP7, AREG (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ed).\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4. Validation of Key circRNAs and miRNAs in the ceRNA Network\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eIn the control group, hBMSCs were cultured in complete medium without osteogenic induction, whereas in the experimental group, hBMSCs were treated with osteogenic induction fluid for 7 days. RT-qPCR was performed to assess the expression levels of 11 molecules corresponding to differentially expressed circRNAs identified through bioinformatics analysis. Compared to the control group, the expression levels of hsa_circ_0001600, hsa_circ_0002415, hsa_circ_0063756, hsa_circ_0072678, and hsa_circ_0005991 were significantly upregulated in the 7-day osteogenic induction group, while the expression of hsa_circ_0008621 was downregulated (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea). Similarly, compared to the control group, the expression levels of hsa-miR-20b-5p, hsa-miR-335-3p, hsa-miR-942-5p, hsa-miR-424-5p, and hsa-miR-542-3p were significantly decreased in the osteogenic induction group, whereas the expression of hsa-miR-203a-3p, hsa-miR-30a-5p, hsa-miR-30c-2-3p, and hsa-miR-199b-5p was increased (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eb).\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5. The interaction between circRNAs and miRNAs within the ceRNA Network\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eDuring the osteogenic differentiation of hBMSCs, the expression of hsa_circ_0005991 and hsa_circ_0001600 shows an increasing trend, indicating that the two molecules may be involved in the regulation of cell osteogenic differentiation. hsa_circ_0001600 and hsa_circ_0005991 were selected as candidate circRNAs. According to the circBank database prediction, hsa_circ_0001600 (circBank ID: hsa_circFKBP5_002) has one binding site (position: 739) with hsa-miR-542-3p in the miRanda algorithm, and four binding sites (positions: 3624, 752, 3629, 758) in the Targetscan algorithm. hsa_circ_0005991 (circBank ID: hsa_circAPBB2_013) has one binding site (position: 584) with hsa-miR-424-5p in the miRanda algorithm prediction, and two binding sites (positions: 598, 604) according to the Targetscan algorithm. hBMSCs were osteogenically induced for 0, 3, and 7 days, and qPCR was employed to assess the expression levels of hsa_circ_0001600, hsa-miR-542-3p, hsa_circ_0005991, and hsa-miR-424-5p. The findings revealed a progressive increase in the expression of hsa_circ_0001600 throughout osteogenic induction (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ec), while the expression of hsa-miR-542-3p decreased gradually with prolonged osteogenic induction. Additionally, the expression of hsa_circ_0005991 exhibited a gradual increase over the osteogenic induction period (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ed), whereas the expression of hsa-miR-424-5p decreased progressively with the extension of osteogenic induction time.\u003c/p\u003e \u003cp\u003eThe experimental design included the use of siRNA to suppress the expression of hsa_circ_0001600. Initial investigation was conducted to determine the optimal siRNA, transfection concentration, and duration. The determined concentration of the target gene siRNA was 50nM, and the transfection duration was 48 hours. qPCR analysis indicated a significant reduction in hsa_circ_0001600 expression with si-hsa_circ_0001600 2 in hsa_circ_0001600 siRNA, achieving a knockdown efficiency of 70% (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ee). The hsa_circ_0001600 siRNA transfection knockdown group exhibited an increase in hsa-miR-542-3p expression compared to the negative control group (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ef).\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.6. Downregulation of hsa_circ_0001600 expression reduces the osteogenic differentiation capacity of hBMSCs\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eThe circular RNA hsa_circ_0001600 is generated through the reverse splicing of the FKBP5 gene, representing a newly discovered circular molecule with unknown biological function and molecular mechanism (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea). Compared to linear RNAs, circRNAs are more stable and longer-lasting because they lack a free end for RNA enzyme-mediated degradation. Circular RNAs are generated by the back-splicing process, and they are covalently closed loops, keeping them highly stable to RNase R digestion. Using qPCR, the expression changes of hsa_circ_0001600 and its parental gene FKBP5 in RNase R-digested total RNA (RNase R+) were analyzed. The non-digested group (RNase R-) served as the control group, with the internal reference in the RNase R- group used as the calculation standard. The qPCR results demonstrated no significant alteration in the expression level of hsa_circ_0001600 in the experimental group compared to the control group. However, there was a notable reduction in the expression of FKBP5, indicating that hsa_circ_0001600 may be resistant to RNase R, whereas its parental gene FKBP5 is predominantly digested by RNase R (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eb).\u003c/p\u003e \u003cp\u003ehBMSCs were seeded into 6-well plates and induced with osteogenic induction medium for 14 days. Throughout this period, siRNA (si-hsa_circ_0001600 and si-NC) was refreshed every 3 days. Alizarin Red staining was performed for both the control and experimental groups. Microscopic observation revealed a significant reduction in red staining in the hsa_circ_0001600 siRNA knockdown group compared to the control group. Furthermore, after transfecting hBMSCs with hsa_circ_0001600 siRNA for 2 days, the medium was switched to osteogenic induction medium for 3 days. The control group comprised hBMSCs transfected with negative control siRNA for 2 days, followed by a 3-day osteogenic induction. ALP staining was conducted for both the control and experimental groups. Microscopic observation revealed a significant reduction in red staining in the hsa_circ_0001600 siRNA knockdown group compared to the control group, indicating a clear decrease in ALP expression (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ec). qPCR analysis was carried out for both the control and experimental groups, demonstrating reduced expression of osteogenic-related genes COL1A1 and RUNX2 in the knockdown group with hsa_circ_0001600 siRNA transfection, as compared to the negative control group (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ed). Furthermore, Western Blot analysis showed decreased expression of osteogenic-related proteins COL1A1, OCN, and RUNX2 in the knockdown group with hsa_circ_0001600 siRNA transfection, as compared to the negative control (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ee, \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ef). The raw bands are shown in Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"3. Discussion","content":"\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eIn the bioinformatics analysis section of this study, we gathered gene expression matrix data of circRNAs, miRNAs, and mRNAs during the early osteogenic differentiation of hBMSCs induced by osteogenic induction medium for 7 days. Through predictive modeling, we identified 22 circRNAs, 17 miRNAs, and 15 mRNAs predicted to interact with each other, successfully constructing a ceRNA network relevant to hBMSCs osteogenic differentiation. Among the identified mRNAs, members of the Bone Morphogenetic Protein (BMP) family, such as BMP7, known for their upregulation during BMSCs osteogenic differentiation, were included\u003csup\u003e[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]\u003c/sup\u003e. Additionally, Vascular Endothelial Growth Factor A (VEGFA) and Fibroblast Growth Factor 9 (FGF9) were implicated in the network and associated with osteoblast differentiation. VEGFA, as an inducer of angiogenesis, has been shown to regulate bone repair and regeneration by affecting the generation of bone vasculature\u003csup\u003e[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]\u003c/sup\u003e. FGF9 is a factor regulating skeletal development, playing a significant role in skeletal development and cartilage formation. Secreted Frizzled-Related Protein 4 (SFRP4) can directly activate the canonical Wnt signaling pathway, and through regulating osteoblasts and osteoclasts, it plays a key role in bone development and remodeling, and reducing its expression can prevent age-related bone loss\u003csup\u003e[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eAmong the predicted 17 miRNAs, studies have shown that downregulation of miR-542-3p can target BMP7 to promote mouse vascular smooth muscle cell and osteoblast osteogenic differentiation\u003csup\u003e[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e],[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]\u003c/sup\u003e. ZEB1 and VEGF can be targeted by miR-942-5p, thereby promoting BMSCs osteogenesis and vasculogenesis\u003csup\u003e[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]\u003c/sup\u003e. Research has indicated a close association of hsa-miR-335-5p, hsa-miR-200b-3p, and hsa-miR-335-3p with osteoarthritis\u003csup\u003e[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]\u003c/sup\u003e. Among the 22 circRNAs unearthed in this study, hsa_circ_0008621 and hsa_circ_0072387 can inhibit glioma progression through miR-338-5p/IKBIP\u003csup\u003e[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]\u003c/sup\u003e. hsa_circ_0072387 is a novel circRNA that can serve as a valuable biomarker for oral squamous cell carcinoma\u003csup\u003e[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e],[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]\u003c/sup\u003e. However, the regulatory roles of the screened circRNAs in osteogenic differentiation are not yet clear, and further research on their regulatory mechanisms is needed.\u003c/p\u003e \u003cp\u003eBased on the constructed ceRNA network, 11 circRNAs and 11 miRNAs were selected for qPCR validation of expression level changes. According to the results and molecular function, two sets of relationships were selected for hsa_circ_0001600, hsa-miR-542-3p, and hsa_circ_0005991, hsa-miR-424-5p. In vitro cell experiments proved that hsa_circ_0001600 may play an important role in the osteogenic differentiation of hBMSCs, and its possible mechanism is the targeted regulation of hsa-miR-542-3p. hsa_circ_0001600 is a circular RNA formed by the reverse cleavage of the FKBP5 gene, with a length of 4534 base pairs. CircRNA can also directly regulate the expression of the host gene. The host gene FKBP5 of hsa_circ_0001600 is a molecular associated with heat shock proteins and has a strong stress response\u003csup\u003e[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]\u003c/sup\u003e. Mutations in FKBP5 are significantly associated with the risk of mental disorders such as anxiety, depression, and post-traumatic stress disorder (PTSD)\u003csup\u003e[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]\u003c/sup\u003e. Studies have shown that FKBP5 also plays a positive role in the early osteogenic differentiation of bone marrow mesenchymal stem cells and adipose stem cells, as well as in cartilage and adipogenic differentiation\u003csup\u003e[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e],[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]\u003c/sup\u003e. Furthermore, FKBP5 mutations may lead to Paget's disease by affecting osteoclast formation\u003csup\u003e[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]\u003c/sup\u003e. Overall, hsa_circ_0001600 may regulate osteogenic differentiation by directly regulating the host gene. Meanwhile, qPCR proves that hsa-miR-542-3p is negatively correlated with BMSCs osteogenic differentiation and knocking down hsa_circ_0001600 will increase the expression of hsa-miR-542-3p. Previous studies have shown that hsa-miR-542-3p inhibits the proliferation, migration, and invasion of tumor cells such as osteosarcoma and glioma cells\u003csup\u003e[\u003cspan additionalcitationids=\"CR34\" citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]\u0026ndash;[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]\u003c/sup\u003e. On the other hand, miR-542-3p positively regulates differentiation and regulates osteogenesis under conditions of bone loss\u003csup\u003e[\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]\u003c/sup\u003e. At the same time, hsa-miR-542-3p has strong osteogenic potential by bioinformatics prediction targeting the highly bone-inducing BMP7. Therefore, we speculate that hsa-miR-542-3p is regulated by hsa_circ_0001600 to inhibit the osteogenic differentiation of hBMSCs.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e"},{"header":"4. Methods","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e4.1. Dataset Collection\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eThe microarray data involved in this study were obtained from GEO(Gene Expression Omnibus) database((\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.ncbi.nlm.nih.gov/geo/\u003c/span\u003e\u003cspan address=\"http://www.ncbi.nlm.nih.gov/geo/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). The circRNA, miRNA and mRNA expression profiles downloaded from GSE135883 (GPL21825 Arraystar Human CircRNA microarray V2,6 pairs of hBMSCs), GSE135586 (GPL18573 Illumina NextSeq 500 (Homo sapiens), 6 pairs of hBMSCs) and GSE18043 (GPL570, Affymetrix Human Genome U133 Plus 2.0 Array, 3 pairs of hBMSCs), respectively. The inclusion criteria for these three groups are hBMSCs chemically induced chemically osteogenic differentiation for 7 days.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e4.2. Differential Expression Analysis\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eThe expression matrix used FastQC to complete quality checking. By using R limma package Subsequently, the DEcircRNAs, DEmiRNAs, and DEmRNAs were screened out and drawn with the R package pheatmap. The criteria of \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 and |log2Fold change (FC)|\u0026gt;1.2 were identified as significantly differentially expressed mRNAs (DE-mRNAs). For circRNAs and miRNAs, we utilized the criteria of \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 and |log2Fold change (FC)|\u0026gt;0.5 to identify significantly differentially expressed circRNAs (DE-circRNAs) and miRNAs (DE-miRNAs), respectively. Subsequently. The pheatmap package in R software was used to generate volcano plots for the differentially expressed genes.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e4.3. Construction of ceRNA network\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eTo discover and establish the potential relationship between the DEcircRNAs, DEmiRNAs, and DEmRNAs, two databases were selected named circBank (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.circbank.cn\u003c/span\u003e\u003cspan address=\"http://www.circbank.cn\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) and miRTarBase (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://miRTarBase.cuhk.edu.cn/\u003c/span\u003e\u003cspan address=\"http://miRTarBase.cuhk.edu.cn/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e)\u003csup\u003e[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]\u003c/sup\u003e to predict the targeting miRNAs and mRNAs. The circRNA\u0026ndash;miRNA\u0026ndash;mRNA network was constructed with intersection of miRNA and mRNA predicted by online databases and DEcircRNAs, DEmiRNAs, and DEmRNAs. A ceRNA network was shown using Cytoscape 3.7.2 software.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e4.4. GO and KEGG enrichment analyses\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eTo find genes that are closely related to our research, we used the DAVID database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://david.ncifcrf.gov\u003c/span\u003e\u003cspan address=\"https://david.ncifcrf.gov\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) to perform Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis of DEmRNAs.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e4.5. BMSCs culture and osteoblast differentiation\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eThe bone marrow-derived mesenchymal stem cells (three donors) were purchased from ScienCell Research Laboratories (Carlsbad, CA, USA). The BMSCs were cultured in mesenchymal stem cell medium (MSCM) (ScienCell, CA, United States) containing 5% fetal bovine serum, 1% penicillin-streptomycin, and 1% mesenchymal stem cell growth supplement. The culture medium was replenished every 2\u0026ndash;3 days, and the cells were maintained at 37\u0026deg;C in a 5% CO2 cell culture incubator. Subsequent experiments utilized hBMSCs from the 3rd to 5th passages.\u003c/p\u003e \u003cp\u003eFor osteogenic differentiation, hBMSCs were seeded in six-well plates at a density of 1\u0026times;10\u003csup\u003e4\u003c/sup\u003e cells/cm\u003csup\u003e2\u003c/sup\u003e. Upon reaching 80\u0026ndash;90% confluency, the routine media was replaced with osteogenic media containing 50\u0026micro;g/ml ascorbic acid, 10mM β-glycerophosphate (Sigma, USA), 10 nM dexamethasone(Invitrogen, USA), 10% FBS, 1% penicillin-streptomycin and 1% glutamine. The media was replenished every 2\u0026ndash;3 days. After 3 days or 7 days, osteogenic differentiation was evaluated by ALP staining and qPCR.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e4.6. Alizarin Red Staining\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eBMSCs osteogenic capacity was detected using alizarin red staining. The hBMSCs were inoculated into 6-well plates and induced with osteogenic induction medium for 14 days, during which siRNA (si-hsa_circ_0001600 and si-NC) was re-placed every 3 days. The plates were rinsed with PBS, fixed with 4% paraformaldehyde for 30 min, washed with ddH2O, and then stained with 1% alizarin red aqueous solution (Solarbio, Beijing, China) for 15 min at room temperature, then washed with ddH2O to observe the staining under the microscope.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e4.7. Alkaline Phosphatase (ALP) Staining\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eALP activity was analyzed using the NBT/BCIP staining kit (Beyotime, Shanghai, China). hBMSCs were seeded in 6-well plates and cultured in osteogenic medium for 7 days. Cells were washed with PBS and fixed with 4% polyformaldehyde for 30min and stained for 20min at 37℃.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003e4.8. Real-Time Quantitative Reverse Transcriptase PCR (RT-qPCR) and RNase R enzyme digestion\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eRT-qPCR was used to check the expression of miRNAs, circRNAs, and mRNAs and to confirm the expression of osteogenic differentiation markers. The hBMSCs nuclear and cytoplasmic RNA was isolated with the TRIzol reagent (Invitrogen, USA) at osteogenic 3 days or 7 days. For cDNA synthesis, a stem loop reverse transcription kit (Vazyme, China) was used for reversing mature miRNA. circRNAs and mRNA were reverse transcribed using HiScript Reverse Transcriptase (Vazyme, China). The qPCR for detecting gene expression levels was performed by SYBR Green PCR Mix (Vazyme, China) and a QuantStudioTM 3 System (Applied Biosystems). The GAPDH (for mRNA and circRNA) and U6 (for miRNA) were used as endogenous controls respectively. All primers used in this study were listed in Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e. After extracting total circRNA, the circRNA was treated with 2U/\u0026micro;g RNase R(GeneSeed, China)digested at 37\u0026deg;C for 10min to digest most of the linear RNA.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003e4.9. Cell Transfection\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eThe si-hsa_circ_0001600 and si-hsa_circ_0005991 and their control vector si-NC were designed and synthesized by Ribobio (Guangzhou, China). The siRNA target sequences were listed in Table S2. The BMSCs were transfected with siRNA(50nM) and si-NC in 6-well plates until 70\u0026ndash;80% confluence with riboFECTTM CP kit (Ribobio, Guangzhou, China). The transfection was conducted for up to 48 hours, unless specified otherwise, followed by subsequent cell treatments.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003e4.10. Western blot analysis\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eThe BMSCs were harvested and lysed in RIPA lysis buffer (Beyotime, Shanghai, China) after washing twice by PBS. and the corresponding proteins were determined by the BCA protein analysis kit (Beyotime), according to the manufacturer\u0026rsquo;s guide. Subsequently, equal quantities of protein samples were added to 12% SDS-PAGE and onto polyvinylidene difluoride (PVDF) membranes after separation. Then, the PVDF membranes were incubated with primary antibody: against RUNX2 (1:1000, Abcam), OCN (1:1000, Abcam), COL1A1 (1:1000, Proteintech), and β-ACTIN (1:1000, Abcam) overnight at 4\u0026deg;C. The membranes were incubated with corresponding secondary antibodies for 1h after washing with PBST three times. The band intensity was measured by Image J software. The signal of all target bands was normalized to that of the β-ACTIN band.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003e4.11. Statistical Analysis\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eAll statistical calculations were performed with GraphPad Prism software (version 8.0). The Student\u0026rsquo;s t-test, Fisher\u0026rsquo;s exact test, χ\u003csup\u003e2\u003c/sup\u003e test, Pearson correlation, or one-way ANOVA were used for statistical analyses in our search. Meanwhile, data are presented as means\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD). \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 were considered significant statistically.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor Contributions:\u003c/strong\u003e Study concept and design, J.Z., Q.Y. and O.L;\u0026nbsp;experiment performed, K.S. and X.C.; data analysis and visualization, K.S. and X.C.; writing—original draft preparation, K.S.; writing—review and editing, J.Z.,\u0026nbsp;Q.Y. and O.L.;\u0026nbsp;modification of figures and manuscript, O.L. Besides, K.S. and X.C. contributed equally to this work; Q.Y. and O.L. should be considered joint senior authors.\u0026nbsp;All authors have read and agreed to the published version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e This research was funded by Health and Family Planning Commission of Hunan Province, grant number 20201660; Health Commission of Hunan Province, grant number 202108031817; Beijing Municipal Natural Science Foundation, grant number 7222079.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInstitutional Review Board Statement:\u0026nbsp;\u003c/strong\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInformed Consent Statement:\u0026nbsp;\u003c/strong\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement:\u003c/strong\u003e The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found at: https://www.ncbi.nlm.nih.gov/, GSE135883; https://www.ncbi.nlm.nih.gov/, GSE135586; https://www.ncbi.nlm.nih.gov/, GSE18043.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments:\u003c/strong\u003e The authors acknowledge other participants in our laboratory for their active help in this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of Interest:\u003c/strong\u003e The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eTavakoli, S.; Ghaderi Jafarbeigloo, H.R.; Shariati, A.; et al. Mesenchymal Stromal Cells; a New Horizon in Regenerative Medicine. \u003cem\u003eJ. Cell. 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Serving as seed cells, BMSCs play a pivotal role in the regeneration of bone defects. Hence, investigating the transcription factors and signaling pathways involved in the regulation of osteogenic differentiation in BMSCs holds significant importance. Recent re-search has unveiled that certain circular RNAs (circRNAs) can function as molecular sponges, influencing the osteogenic differentiation process of mesenchymal stem cells. However, many circRNAs remain undiscovered, and their precise mechanisms remain elusive. Therefore, the objective of this study is to construct an osteogenic differentiation-related circRNA-miRNA-mRNA network in hBMSCs through bioinformatics analysis. Subsequently, circRNAs associated with the osteogenic differentiation of hBMSCs, as identified by bioinformatics analysis, along with their potential miRNA-mRNA axes, will be validated through in vitro experiments.\u003c/p\u003e","manuscriptTitle":"Construction of an interactome network among circRNA-miRNA-mRNA reveals new biomarkers in hBMSCs osteogenic differentiation","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-07-24 09:46:22","doi":"10.21203/rs.3.rs-4603272/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-07-24T18:40:04+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-07-14T06:20:01+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-07-11T08:49:41+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"240237090458040605149079878547092885407","date":"2024-07-04T09:44:44+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"110916714116538393487275479084654637733","date":"2024-07-04T03:12:27+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-07-03T23:37:39+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-07-03T23:33:15+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2024-07-03T14:36:18+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-07-02T12:17:08+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2024-06-19T05:10:59+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":"279bc33e-13d4-4769-bf4a-c8d81813c276","owner":[],"postedDate":"July 24th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":34568708,"name":"Biological sciences/Molecular biology"},{"id":34568709,"name":"Biological sciences/Stem cells"},{"id":34568710,"name":"Earth and environmental sciences/Biogeochemistry"},{"id":34568711,"name":"Health sciences/Biomarkers"},{"id":34568712,"name":"Health sciences/Molecular medicine"}],"tags":[],"updatedAt":"2024-10-21T16:02:09+00:00","versionOfRecord":{"articleIdentity":"rs-4603272","link":"https://doi.org/10.1038/s41598-024-76136-z","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2024-10-18 15:57:36","publishedOnDateReadable":"October 18th, 2024"},"versionCreatedAt":"2024-07-24 09:46:22","video":"","vorDoi":"10.1038/s41598-024-76136-z","vorDoiUrl":"https://doi.org/10.1038/s41598-024-76136-z","workflowStages":[]},"version":"v1","identity":"rs-4603272","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4603272","identity":"rs-4603272","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}