Elucidate the potential mechanism of Eucommiae Cortex against osteoporosis by network pharmacology and RNA-sequencing 

Elucidate the potential mechanism of Eucommiae Cortex against osteoporosis by network pharmacology and RNA-sequencing | 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 Research Article Elucidate the potential mechanism of Eucommiae Cortex against osteoporosis by network pharmacology and RNA-sequencing Yun Liu, Jianbin Tan, Chengliang Xie, Weiling Huang, Zhi Lu, Hong Lin, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-1987008/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 4 You are reading this latest preprint version Abstract Purpose Eucommiae Cortex ( Eucommia ulmoides Oliv. , cortex) had possessed multiple curative effect since ancient time. Nevertheless, the mechanism of EC serves as anti-osteoporotic herb remains further investigated. Methods Cytotoxicity assay and osteogenesis assay were adopted to filtrate the TCMs and osteoporosis model rats of was utilized to verify the anti-osteoporosis ability of EC. Network pharmacology was used to investigate the potential mechanisms of the EC against osteoporosis. The database including TCMSP, BATMAN TCM and TCMID were utilized to obtain the active compounds of EC, and their potential targets were predicted by SwissTarget-Prediction. Osteoporosis related targets were found by OMIM, DisGeNET and Gene Cards databases. The target interaction network was analyzed by STRING, GO enrichment and KEGG pathway analysis were carried out by DAVID database. Results Results of in vitro and in vivo experiments illustrated that EC showed no cytotoxicity and exhibited anti osteoporosis effect. A total number of 19 active components and 124 osteoporosis related targets of the EC were selected. KEGG pathway enrichment from bioinformatics suggested that EC prevented osteoporosis through the HIF-1 signaling pathway and estrogen signaling pathway, while results of RNA- sequencing suggesting HIF-1 signaling pathway. Moreover, genes Akt1, MAPK3 and EGFR may serve as the critical targets regulated by EC. Conclusion Our results showed that HIF-1 signaling pathway was vital pathway in EC against osteoporosis, with the participation of gene AkT1, MAPK3 and EGFR. Estrogen and VEGF signaling pathway were synergetic pathway of anti-osteoporosis TCM Osteogenesis Estrogen signaling pathway Network pharmacology Eucommia ulmoides Oliv. Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Introduction Osteoporosis is a kind of metabolic diseases accompanied by bone loss, bone microstructure changes, resulting in bone systemic metabolic bone disease that increases fragility and is prone to pathological fractures[ 1 ]. As considerable burden to affected persons, caregivers and society, osteoporotic fractures and osteoporosis have become the major public health problems worldwide. The prevalence of osteoporotic fractures in the Chinese population is uncertain and few individuals receive drug treatment to prevent fracture. Other studies indicate that about 6.5% of the population in China was treated with anti-osteoporotic agents under 6 months after the fracture had occurred[ 2 ]. Bone remodeling approves catabolic of old and damaged bone. The maintenance of mineral and acid-base homoeostasis also supports by bone turnover [ 3 ].Menopause often chaperones decline of estrogens levels which lead to acceleration of bone resorption and finally result in postmenopausal osteoporosis[ 4 ]. In molecular biology, bone turnover based on the activity of bone resorbing cells (also commonly known as osteoclasts) and bone forming cells (also commonly known as osteoblasts)[ 5 ]. Estrogen can also directly inhibit bone remodeling, decrease bone resorption and active bone formation by acting on osteocytes, osteoclasts and osteoblasts[ 6 ]. However, estrogen therapy of postmenopausal osteoporosis brings about high risk of breast carcinoma[ 7 ]. Thus, a higher efficacy and safety therapeutic strategy are urgent to lucubrate for the prevention and treatment of osteoporosis. Possessing the properties of safety, good efficacy, few side effects, traditional Chinese medicine (TCM) becomes a novel strategy to prevent and treat diverse diseases[ 8 ]. To improve the safety and efficiency, further molecular mechanism of TCM was urged to be verified. Multi-component characteristics of the TCMs contribute to the relatively complex biological molecular mechanism, which had augmented the difficulty of further investigation in molecular mechanism of TCMs by animal or cellular studies[ 9 ]. A comprehensive analysis method was necessary to put forward. As an approach to analysis including network analysis, systems biology, connectivity, redundancy and pleiotropy, network pharmacology has offered a way of thinking about the mechanism investigation of TCMs and provided a novel strategy to probe the correlation between TCMs and diseases[ 10 , 11 ]. We had searched and identified TCMs therapy of osteoporosis relevant studies from China National Knowledge Infrastructure (CNKI, www.cnki.net ) and the Wan fang Database( www.wanfangdata.com.cn ), gathering and analyzing the TCMs compound preparation. The TCMs were mainly applied in clinical compound preparation for osteoporosis therapy such as xianlingubao[ 12 ], dangguibuxue tang[ 13 ], erxian decoction[ 14 ], Qing' E Formula[ 15 ]and many of others, that were gathered for the subsequent studies. The alternative TCMs were as followed: Rehmanniae Radix Praeparata (RRP) from Rehmannia glutinosa Libosch., root , Hedysarum Multijugum Maxim (HMM) from Astragalus membranaceus, root , Eucommiae Cortex (EC) from Eucommia ulmoides Oliv., cortex . Among the alternative TCMs, Eucommiae Cortex(EC)is a TCM with extensive medicinal value, which is derived from the dried bark of Eucommia ulmoides Oliv. [ 16 ]. EC can be used as the nourishment of liver and kidney, enhancement of the muscles and bones, prevention of abortion in Chinese Pharmacopoeia[ 17 ]. Because of the multifunction like antidiabetic, anti-hypertension, anti-obesity, anti-osteoporosis, anti-inflammatory, anti-thrombotic, and anti-tumor activities, EC has caught considerable attention over the years[ 17 , 18 ]. Nevertheless, anti-osteoporosis efficiency of EC remains to be further explored. There are few existing studies on the anti-osteoporosis effect of EC, among which experimental method is mainly used for OVX- rats[ 19 ], SAMP6 model[ 20 ] and MC3T3-E1 pre-osteoblasts[ 21 ]. We adopted the combination of in vitro and in vivo methods to illustrate the anti-osteoporosis ability of EC. As methods of bioinformatics analysis, network pharmacology is underpinned by the interaction network consist of gene, protein target and disease[ 10 ]. Deep exploration of EC against osteoporosis molecular mechanisms using network pharmacology is of great significance. High-throughput sequencing was applied to compare with the results of network pharmacology. Therefore, functional verification of EC was carried out on in vitro and in vivo osteogenesis assay, bioinformatics analysis and high-throughput sequencing was utilized to find out the potential mechanism of EC to treat OP in this study. Materials And Methods Materials The extract of TCMs were provided by Inifinus (China) Company Ltd. (Guangzhou, China), including Rehmanniae Radix Praeparata (Batch Number: CSDH-C-924188), Hedysarum Multijugum Maxim (Batch Number: CHNQ-A-901371), Eucommiae Cortex (Batch Number: CDUZ-C-923806). All subjects were stored in sealed, away from light environment, normal temperature, dry conditions. More information including subjects, abbreviations, plant origin, extraction solvent, extraction ratio were shown in Table S1. Cytotoxicity assay Preosteoblast MC3T3-E1 cells (iCell-m031) were purchased from iCell Bioscience Inc (Shanghai, China). Cell were cultured in α-MEM culture medium which was supplemented with 10% fetal bovine serum (FBS), 100 µg/ml streptomycin and 100 U/mL penicillin at 37℃with a humidified 5% CO2 atmosphere. The accessory factors (50 µg/ml ascorbic acid and 5 mM β-glycerophosphate) were added to induce differentiation. Cytotoxicity was measured using the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazoliumbromide (MTT) assay. Briefly, after seeded in 96-well plates for 24h, the cells were incubated in the media containing various concentrations of 15 candidates TCMs (0, 0.1, 1, 5, 10,50µg/mL). While 48h incubation was finished, culture medium was replaced by 100µLfresh media containing0.05% MTT for an additional 4 hours. After discarding the supernatant, 200 µL dimethyl sulfoxide were added to each well to dissolve the insoluble formazan products, and the absorbance at 570nm of each well was detected using a microplate spectrophotometer (Thermo Fisher Scientific, MA, USA). Alkaline phosphatase (ALP) staining To evaluated the ALP activity of treaded cells, MC3T3-E1 cells were incubated in medium with TCMs of different concentration and osteogenic inducing medium for 7 days. Then, a BCIP/NBT Alkaline Phosphatase Color Development Kit (Beyotime Biotechnology, Shanghai, China) was utilized according to the protocol. After fixing in 4% polyformaldehyde for 30min, the cells were washed with PBS and then react with the BCIP/NBT dye for 30 min. The Nikon Eclipse Ti-S fluorescence microscope (NIKON, Japan) was applied to capture. Bone mineralization assay To assess the degree of bone mineralization, MC3T3-E1 cells were incubated in inducing medium with various concentrations of EC (0, 1, 5, 10, 20 µg/mL) for 21 days and medium was replaced every three days. After treated, the cells were washed with PBS and fixed with 4% polyformaldehyde for 30 min. the fixed cells were stained with Alizarin red S solution (Solarbio, Beijing, China) (1%, pH 4.2) for 2 h at room temperature and washed by distilled water three times to wipe off the excess solution before captured with Nikon Eclipse Ti-S fluorescence microscope (NIKON, Japan). Alkaline phosphatase (ALP) assay To investigate the ALP activity of EC-treated MC3T3-E1 cells, the cells were seeded and allowed to attach for 24 h, then cultured with different concentration of 4 TCMs (0, 1, 5, 10, 20 µg/mL) for 7days and were measured using enzymatic assay (Beyotime Institute of Biotechnology, Shanghai, China). Briefly, cells were obtained and mixed with the protease inhibitor free lysis buffer (Beyotime Institute of Biotechnology, Shanghai, China) on ice, and the lysate was collected to centrifuge for 10 minutes under 12,000 rpm. After incubated with substrate for 30 min at 37 o C, the absorbance of each well was detected with a microplate spectrophotometer under 405nm. The nmol of p-nitrophenyl phosphate(pNP) produced per mg protein per assay time represents the ALP activity. Establishment of osteoporosis models To further verify the osteogenesis ability of EC, osteoporosis model was utilized for evaluation. Healthy 12 weeks old female specific-pathogen-free Sprague Dawley rats were purchased from Guangdong Medical Laboratory Animal Center and undergo bilateral ovariectomy. Briefly, the osteoporosis model rat was established by bilateral ovariectomy under anesthesia. SD rats were randomly divided into three groups as follows: sham operation group (n = 10), OVX group (n = 10) and OVX combined with EC group (500mg/kg BW, equal to 30 times of human clinical dose). The sham operation group was subjected to sham operation, while OVX group and OVX combined with EC group were surgically ovariectomized. Above groups were performed the operation under anesthesia of isoflurane and which were pre-fasting for 12h. After 2 weeks of postoperative recovery, the EC extract solution was intragastrically administrated for OVX combined with EC group, while purified water for sham operation and OVX group every day for 18 weeks. After the experiment, serum was prepared by centrifugation of the whole blood which was drawn from all rats under anesthesia at 3000 rpm for 10 min and femurs were removed after the rats were sacrificed. All experimental procedures were approved by the Ethics Committee of Guangzhou Center for Disease Control and Prevention. Measurement of biochemical indicators As markers of osteogenesis, serum ALP levels were measured by Alkaline Phosphatase Assay Kit (Beyotime Institute of Biotechnology, Shanghai, China), and serum TRAP levels were measured by Tartrate Resistant Acid Phosphatase Assay Kit to evaluate the condition of bone resorption. Biochemical indicators of serum alanine aminotransferase (ALT) and aspartate aminotransferase (AST) levels were detected by automatic biochemistry analyzer (7600-020, Hitachi, Tokyo, Japan) to evaluate the liver function. Measurement of BMC and BMD Measurements of BMC and BMD of femurs were performed with Dual Energy X-Ray Absorptiometry (Hologic, Inc., USA). The right femur that needed to be measured was removed after the rats were sacrificed. The area that was needed to be scanned is automatically identified by the instrument and the stationary area detector uses ultra-high-resolution pixels. Data preparation Identification of active ingredients in EC Traditional Chinese Medicine Systems Pharmacology Database (TCMSP) ( https://tcmsp-e.com/ ), Bioinformatics Analysis Tool for Molecular mechanism of Traditional Chinese Medicine (BATMAN-TCM)( http://bionet.ncpsb.org/batman-tcm/ ) and the Traditional Chinese Medicine Information Database (TCM-ID) ( http://www.megabionet.org/tcmid/ ) were used to retrieve the components of EC. The condition of oral bioavailability (OB) and drug similarity (DL) larger than 0.18 and 30% respectively, which were set to contract the candidate active compounds of EC, and then those 2D molecular structure were verified and obtained by PubChem database ( https://pubchem.ncbi.nlm.nih.gov/ ). Targets prediction and screening of active ingredients in EC Bioactivities of candidate compounds were screened with the following conditions in SwissADME ( http://www.swissadme.ch/ ) database. GI absorption should be shown as ‘High’ and both of parameters like Lipinski, Ghose, Veber, Egan, and Muegge should be shown as ‘Yes’. The putative target of qualified active ingredients were gathered from the SwissTargetPrediction ( http://www.swisstargetprediction.ch/)databas e, and recruit criteria were probability > 0. Related targets collection of osteoporosis The target organism was set as Homo sapiens, then, osteoporosis-associated targets were collected from three databases namely Online Mendelian Inheritance in Man database (OMIM, https://www.omim.org/ ), DisGeNET database ( https://www.disgenet.org/ ) and GeneCards database ( https://www.genecards.org/ ). The key word “osteoporosis” was used to search the disease-targets in the three databases and the integrating disease-targets were prepared for network construction subsequently. Network construction Comparation and analyzation of EC-targets and osteoporosis-associated targets A dataset containing the common targets, scilicet OP relative targets that base on the EC components predictive targets were obtained. Interaction network was constructed and analyzed by Cytoscape 3.8 and common targets were obtained by Venny 2.1.0 ( https://bioinfogp.cnb.csic.es/tools/venny/index.html ). After obtaining the common target of osteoporosis-associated targets and predicted EC targets, the interaction network between the active ingredient and the target gene was also constructed. Protein-protein interaction (PPI) network construction STRING database was used to import the official gene name of the OP relative targets that base on the EC components to construct the PPI network with Homo sapiens as the target organism. To investigate the interactions of target genes and to obtain the parameters of PPI network, the results of the STRING database were imported into Cytoscape (version 3.8) and calculated by Network Analyzer. Bioinformatics analyses To investigate the core mechanism of the pathway and biological process that associated with EC and OP, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and Gene Ontology (GO) enrichment analyses were conducted to access the critical information. DAVID Bioinformatics Resources 6.8( https://david.ncifcrf.gov/ ) was employed to process the KEGG pathway and GO enrichment analysis of hub co-targets in PPI network which was successfully constructed. The acquired terms match the condition of p < 0.05 and Benjamini-Hochberg (BH) value lower than 0.5 were considered as meaningful and ponderable. Results visualization were implemented by using R software. RNA-seq analysis The RNA-seq assay was carried out with total RNA that extracted from of MC3T3-E1 cells using the TRIzol reagent (Invitrogen), and then RNA-seq analysis were performed by the Beijing Genomics Institute (BGI) (Shenzhen, China) via the BGISEQ-500 platform (BGI, Wuhan, China). The FPKM mapped was utilized to calculate the gene expression levels and gene with FPKM larger than 1 were recruited for analysis and exhibition. Fold changes (FC) were considered as significant when the absolute value (Log2FC) is greater than 0.5, with a Q value < 0.05. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and Gene ontology (GO) enrichment analyses were conducted to analyze the differential gene. Statistical analysis The mean and standard deviation were used to express the raw data, at least three replicates were implemented for each sample. ANOVA were used to analyze the between-group differences. Visualization of statistical analysis and calculation of Tuckey’s HSD test was obtained by GraphPad Prism 6 software (GraphPad software Inc., La Jolla, CA). Results Cell viability and osteogenesis ability evaluation of candidate TCM As a preliminary screening, 3 TCMs were chosen to process a cell viability assay, including RRP, HMM and EC. As showed in Fig. 1 a, all 3 TCMs had shown no viable damage of MC3T3-E1 cells at the concentration of 0.1 to 50 µg/mL, which showed TCMs would not inhibit the proliferation of cells. In accordance with proliferating promotion of MC3T3-E1, RRP, EC, HMM were chosen for the subsequent osteogenesis experiments. The ability of Osteogenesis Promotion of candidate TCMs The dose of 0.1, 1, 5, 10µg/mL TCMs (RRP, EC and HMM) was used in the subsequent experiment, scilicet ALP staining assay and mineralization assays. As showed in the result, RRP, EC and HMM were evaluated the ALP activity significantly in a 7-day culture compared to the control-treated cultures (Fig. 1 b). Meanwhile, Alizarin Red S staining assay demonstrated that RRP, EC and HMM increased the matrix mineralization of MC3T3-E1 cells in a 21-day culture compared to the control group (Fig. 1 c). An optimum concentration of 1 µg/mL was equal among 3 TCMs for stimulating osteoblastic differentiation. Then EC was selected for further evaluated. EC attenuated the loss of bone mass in osteoporosis model rats Body weight of both OVX groups were significantly increased compare to sham operation group (Fig. 2 a). As markers of bone transformation, Trap and ALP were significantly increased in the model group respectively compared with the sham operation group, indicating that bone metabolism was exuberant and bone metabolism diseases occurred (Fig. 2 c). Comparing with the model group, Trap and ALP levels of the EC-treated group had slightly recovered, indicating that the EC has the effect of alleviating bone loss. The alternative trend of liver function indexes was also up regulated in model group and restored in the EC group (Fig. 2 b), indicating that the EC had an additional effect of liver protection. To explore the actual changes in bone mass, dual-energy X-ray absorptiometry was used to detect the BMD and BMC of the rat femur. The results showed that the BMD and BMC of the model group were both decreased, while the EC treatment group showed an increase in BMD and BMC compared with the model group (Fig. 2 d). The above results indicated that EC possess the effect of alleviating osteoporosis and had additional liver protection. Network pharmacology analysis Active ingredients of EC and Target prediction A total number of 215 active compounds of EC were collected from three databases initially. The result of each database was as followed: A total of 28 compounds in TCMSP, a total of 128 compounds in TCMID and a total of 59 compounds in BATMANTCM. After removing the replicated compounds and were verified by PubChem, a total number of 86 ingredients were identified according to the corresponding 2D structures from PubChem after which were screened by the SwissADME, and a total of 19 ingredients in EC were recruited for the next investigation (Table 1 ). Because of the synergistic action among multiple compounds and the target genes had determined the effectiveness of the EC against OP, targets prediction of ingredients found out to be critical to proceed. Thus, putative targets of 19 candidate compounds were intended to be predicted by SwissTargetPrediction subsequently. A total of 527 target genes were obtained and prepared for network construction with Cytoscape (Fig. 3 ). According to EC active compounds and predictive target gene, a total number of 561 nodes and 2586 edges were obtained and analyzed for the network. Table 1 The 19 active compounds of EC. ID CID Name Database Mol 1 73117 (+)-Eudesmin TCMSP Mol 2 73399 Pinoresinol TCMID BATMAN-TCM Mol 3 91458 Aucubin TCMID BATMAN-TCM Mol 4 94175 Epiquinidine TCMID BATMAN-TCM Mol 5 94253 Vulgarin TCMID BATMAN-TCM Mol 6 165225 Dehydrodieugenol TCMSP TCMID BATMAN-TCM Mol 7 181681 Medioresinol TCMSP TCMID Mol 8 443028 Yangambin TCMSP Mol 9 637584 Epipinoresinol TCMID Mol 10 717531 3,4-Dimethoxycinnamic acid TCMID BATMAN-TCM Mol 11 5280457 Pinosylvin TCMID BATMAN-TCM Mol 12 5280489 beta-Carotene TCMSP Mol 13 5280863 Kaempferol TCMSP TCMID BATMAN-TCM Mol 14 5280961 Genistein TCMID BATMAN-TCM Mol 15 5281953 Syringetin TCMSP Mol 16 5317205 Erythraline TCMSP TCMID BATMAN-TCM Mol 17 5320287 Ombuin TCMID BATMAN-TCM Mol 18 5351950 Tabernemontanine TCMID BATMAN-TCM Mol 19 6710676 Kobusone TCMSP To explore the relationship of target gene between OP and EC, OMIM, DisGeNet and GeneCards database were employed to retrieve osteoporosis-related targets. A total of 191, 172 and 1032 targets were collected from three databases respectively and then the result was integrated and after the reduplicative data were removed. Retrieval osteoporosis relative targets by count of 1179 were compared with the predicted EC targets to gather 124 common targets (Fig. 4 a). These124 common targets became follow-up subjects that represent potentially significant in the mechanism of EC influences osteoporosis. Construction and analysis of compounds-Target Interaction network Compounds-target interaction network was constructed with the common target of EC compounds and osteoporosis-associated proteins, which consist of 143 nodes and 309 edges (Fig. 4 b). According the connections of targets, top six of degree were identified as Genistein (Mol14) with degree equal to 32, Vulgarin (Mol5) with degree equal to 29, Ombuin (Mol17) with degree equal to 29, Syringetin (Mol15) with degree equal to 29, Pinosylvin (Mol11) with degree equal to 28 and Kaempferol (Mol13) with degree equal to 28, indicating that flavonol and isoflavone are critical components in EC against OP. PPI network of common targets between compounds STRING database was utilized to construct a network consisting of 124 common targets. To understand how multiple targets function in complicated illnesses like OP, the PPI networks become an indispensable research method. The PPI network that was construed with 124 common targets had shown in Fig. 5 . The genes Akt1, MAPK3, EGFR, CASP3, SRC, MAPK1, STAT3, PTGS2, ESR1, CXCL8, MMP9 with node degree higher than 50 were regarded as the critical targets influenced by EC. To help focus on the key node, that degree greater than 20 were selected to construct a PPI network the cluster consisted of 54 nodes and 755 edges. Critical nodes with greater degree were present in the colour of light red as AKT1, EGFR, MAPK3, CASP3 and SRC (Fig. S1). KEGG and GO enrichment analysis. To find out the mechanisms of the EC against osteoporosis, a total of 124 common target of EC and OP were analysis by KEGG and GO enrichment using DAVID. Results of enrichment were visualized by R software in the form of a bubble diagram (Fig. 6 b). Top three of high degree nodes AKT1, MAPK3 and EGFR were mainly implicated in HIF-1 signaling pathway, estrogen signaling pathway, thyroid hormone signaling pathway, VEGF signaling pathway. Numerous investigations indicate that estrogen signaling pathway was closely related postmenopausal osteoporosis. To visualize the relationship between signal pathways and critical genes, network was constructed with the filtered data using the Cytoscape software (Fig. 6 a). Take the GO enrichment results together, counts of genes and P value were critical parameters to filter the term of biological processes, molecular function and cellular component. On the basis of the condition above, biological processes involving in EC against OP were phosphatidylinositol-mediated signaling, protein autophosphorylation, regulation of phosphatidylinositol 3-kinase signaling, signal transduction and platelet activation (Fig. S2). The molecular function involving in EC against OP were steroid binding, enzyme binding, insulin-like growth factor I binding, phosphatidylinositol-4,5-bisphosphate 3-kinase activity and heme binding (Fig. S2). The cellular component involving in EC against OP were plasma membrane, extracellular space, protein complex, caveola and phosphatidylinositol 3-kinase complex. The enrichment results showed that the mechanism of EC against OP was associated with a battery of steroid hormone biochemical reaction and phosphatidylinositol 3-kinase activity (Fig. S2). Transcriptome profiling and functional enrichment analysis of High-throughput sequencing To ensure the reliability of the results, the raw data of sequencing contains reads with low quality, adapter contamination, and high nitrogen content of unknown bases were removed before data analysis. According to the selection criteria for DEGs, 52 DEGs were identified between EC group and Con group (Fig. 7 c, f), and 6418 DEGs were identified between the NC group and Con group (Fig. 7 d, e). Moreover, 40 common DEGs were founded according to comparison of two clusters of DEGs, which were used for subsequent analysis. PPI network construction and enrichment analysis of DEGs To demonstrate the results from RNA-sequencing, overlapping targets were recruited according the comparison of Con vs NC group and EC vs Con group (Fig. 7 a). Then, 40 mouse DEGs were converted to human gene name and a total of 35 genes name were returned by the UniProt database. The PPI network was analyzed using the STRING database and visualized by Cytoscape software with 24 recruited genes, after removing the unclustered data, the network was shown in Fig. 7 b. KEGG pathway enrichment of 35 converted common genes were conducted by DAVID database. A total of 3 terms were returned with P < 0.05, which were HIF-1 signaling pathway, Central carbon metabolism in cancer and Apelin signaling pathway, as shown in Table 2 . The first two pathways were also returned from DAVID database in network pharmacology analysis. Table 2 Annotation of KEGG pathways Term ID Description Count P value Genes hsa04066 HIF-1 signaling pathway 4 0.0020 EGLN1, PFKL, SLC2A1, HK2 hsa05230 Central carbon metabolism in cancer 3 0.0114 PFKL, SLC2A1, HK2 hsa04371 Apelin signaling pathway 3 0.0412 EGR1, CCN2, APLN hsa00052 Galactose metabolism 2 0.0702 PFKL, HK2 hsa00051 Fructose and mannose metabolism 2 0.0746 PFKL, HK2 hsa05166 Human T-cell leukemia virus 1 infection 3 0.0940 EGR1, SLC2A1, FOS To further explore the molecular mechanisms of the EC anti-osteoporotic activity, GO enrichment was conducted and take the results together, counts of genes and P value were critical parameters to filter the term of biological processes, molecular function and cellular component. Total numbers of 17, 5 and 5 were the results returned from GO enrichment corresponding to BP, CC, MF. Detailed information of the GO enrichment is presented in Tables S2, S3 and S4. A significative term was returned as a response to estradiol in biological processes indicating that anti-osteoporotic effect of EC involving estradiol related biological processes. Discussion Network pharmacology has been ubiquitously used as a rational strategy to analyze the potential biological mechanism of TCMs. The basic concept of Network pharmacology is regarding the drug action as the result of interactions network, rather than a single specific action[ 22 ]. Due to the complicate components, the action mechanisms of Chinese medicines are often elusive [ 12 ]. Thus, it is significant to integrate network pharmacology to provide a holistic view for the molecular mechanism of Chinese medicines[ 23 ]. OP is a common form of secondary osteoporosis, which has been a risk factor of fracture among many patients, especially in postmenopausal women[ 24 ]. Estrogen is a main hormonal regulator of bone metabolism both in women and men. Deficiency of estrogen is common in senile people and usually accompanied by postmenopausal osteoporosis[ 5 ]. According to the results of in vitro experiment, EC had shown well osteogenesis ability, the mechanism of EC against osteoporosis was profound significative to be investigated, particularly of the influence of estrogen. In this study 3 TCMs were selected for cytotoxicity assay according to the literature and then were performed osteogenic assay for osteogenic capability assessment. After primary evaluation as preeminent osteogenesis ability, EC was chosen for the in vivo assessment of osteogenic capability with osteoporosis model rats and the potential anti-osteoporosis molecular mechanism investigation utilizing network pharmacology and RNA-seq analysis. In vivo experiments show that EC can alleviate the bone loss caused by bilateral ovariectomy and possess additional liver protective effects. Although the EC had the effect of alleviating bone loss, the changes in bone mass were less pronounced, possibly due to the limitations of the trial period. In the mechanism exploration section, we collected 86 EC compounds from TCMSP, TCMD and BATMAN TCM after were verified by PubChem, and 19 compounds were selected by ADME and conduct follow-up targets prediction in Swiss Target Prediction and a total of 527 target gene were identified. According to EC active compounds and predictive target gene, a network with 546 nodes and 1174 edges was constructed and analyzed. With the utilization of OMIM, GeneCards and DisGeNet databases, a count of1179 OP- related gene entries were collected. After comparing with the predicted EC targets, we had collected 124 common targets as the key targets for subsequent mechanism research of the EC compounds. Compounds-targets network was constructed according to the common targets, results indicating that flavonol and isoflavone are critical components in EC against OP. Flavonoids are naturally occurring bioactive polyphenols with anti-inflammatory and antioxidant properties, and some studies have suggested a link between flavonoid intake and bone health[ 25 , 26 ]. As two important active ingredients in flavonoids, flavonols and isoflavone were revealed that possess the ability of osteoclastogenesis and osteoprotection[ 27 , 28 ]. Candidate targets were identified based on PPI network analysis, key nodes were obtained as Akt1, MAPK3, EGFR, CASP3, SRC, MAPK1, STAT3, PTGS2, ESR1, CXCL8, MMP9 according to the degree of each node. To explore the KEGG pathway and GO enrichment, all assumed target genes were gathered for the following investigation. A total number of 33 KEGG pathway terms were collected and classified to visualize as a bubble diagram. Results of GO enrichment were also visualized by a bubble diagram. The key nodes mostly belong to HIF-1(hypoxia-inducible factor 1) signaling pathway and estrogen signaling pathway, following by thyroid hormone signaling pathway and VEGF signaling pathway. Playing an essential role to maintain the oxygen homeostasis inside the metazoan organisms, α-subunit of HIF-1 factor is regulated by hypoxia as functional subunit[ 29 , 30 ]. As an indispensable member of HIF-1 signaling pathway regulating hypoxia reactions, Hypoxia-inducible factor‐1α (HIF‐1α) playing an important role in bone modeling, remodeling, and homeostasis[ 31 ]. As a transcription factor, HIF-1α crucially function in regulating VEGF, and VEGF signaling pathway which was also closely related postmenopausal osteoporosis[ 32 , 33 ]. As the results of KEGG pathways return, 7 of 14 associated gene in estrogen signaling pathway were also key node in PPI network, which were SRC, ESR1, MMP9, EGFR, AKT1, MAPK1, MAPK3. The result of the enrichment and analysis had shown that the sex hormone estrogen activates its nuclear receptor ESR1 (estrogen receptor alpha) to trigger the relative components derived growth factors to protect bone loss[ 34 , 35 ]. As for the Src, plays an indispensable role in adhesion and motility. Recent studies have shown that Src inhibitors may have therapeutic value in tumor suppressor, tumor angiogenesis and bone resorption[ 36 , 37 ]. Both women and men require estrogen as a major hormonal regulator to maintain bone metabolism[ 38 ]. Therefore, the reduction of estrogen consequence in the acceleration of bone resorption, reflecting the importance of estrogen to keep the activation of bone formation at the cellular level[ 39 ]. One of the most important biological role of estrogen is to inhibit the maturation of osteoclasts via RANKL/RANK/OPG pathway[ 40 ]. What is more, estrogen can effects directly on osteoblasts and osteocytes, which would approve the maintenance of bone formation[ 41 ]. Thus, to unravel the pleiotropic effects and profound meaning of the relationship between signal pathways and critical genes in osteoporosis prevention and treatment, another network was constructed. Genes that interact with greater pathways were PIK3CD, PIK3CB, PIK3CG, AKT1, MAPK1, MAPK3 and PIK3CA. The results from RNA-sequencing were also enriched by KEGG pathway and GO enrichment. The HIF-1 signaling pathway was also returned in the results. The gene AkT1, MAPK3 and EGFR were involved in HIF-1 signaling pathway whether in network pharmacology analysis or RNA-sequencing analysis. Several studies have shown that HIF-1 is involved in osteogenesis, osteocytes apoptosis and osteoclast activation[ 42 – 44 ]. During menopause, estrogen deficiency leads to the accumulation of HIF1α protein in osteoclasts, leading to osteoclast activation and bone loss[ 42 ]. The combined effects of EC target genes produced osteogenesis and anti-osteoporosis effects. Main components of EC that target the key node including Epiquinidine, Vulgarin, Dehydrodieugenol, 3,4-Dimethoxycinnamic acid, Pinosylvin, Kaempferol, Genistein, Syringetin, Erythraline, Ombuin Tabernemontanine and Kobusone, and which of those components also target at estrogen relative genes. It was suggested that the EC extract process the ability of osteogenesis improvement by influencing the HIF-1 signaling pathway with gene AkT1, MAPK3 and EGFR. In addition, estrogen signaling pathway and VEGF signaling pathway also plays a role in osteogenesis of EC. Conclusion Osteogenesis effect of EC was verified via in vitro and in vivo experiments and the molecular mechanism was investigated by network pharmacology and RNA-sequencing analysis. Our results showed that HIF-1 signaling pathway was vital pathway in EC against osteoporosis, with the participation of gene AkT1, MAPK3 and EGFR. Estrogen and VEGF signaling pathway were synergetic pathway of anti-osteoporosis. Abbreviations TCM, traditional Chinese medicine; EC, Eucommiae Cortex;Akt1, AKT serine/threonine kinase 1; MAPK3, mitogen-activated protein kinase 3; EGFR, epidermal growth factor receptor; CASP3, caspase 3; SRC, SRC proto-oncogene, non-receptor tyrosine kinase; MAPK1, mitogen-activated protein kinase 1; STAT3, signal transducer and activator of transcription 3; PTGS2, prostaglandin-endoperoxide synthase 2; ESR1, estrogen receptor 1; CXCL8, C-X-C motif chemokine ligand 8; VEGF, vascular endothelial growth factor; OP, osteoporosis; RRP, Rehmanniae Radix Praeparata; HMM, Hedysarum Multijugum Maxim; EC, Eucommiae Cortex. Declarations Ethical approval Approval was obtained from the Ethics Committee of Guangzhou Center for Disease Control and Prevention. Consent to Participate All the authors discussed and agreed on the final manuscript. Competing interests All the authors have no competing interests to declare that are relevant to the content of this article. Author contributions Min Zhao , Xingfen Yang and Chengliang Xie conceived the present study, supervised the study design, supported data interpretation and revised the manuscript; Yun Liu and Jianbin Tan designed the experiments and wrote the manuscript; Zhi Lu provided experimental samples; Weiling Huang and Hong Lin performed the experiments; Mansi Luo and Ying Jiang analyzed the data; Hongxia Wang and Kexin Wang finished the literature research. Funding The work was funded by National Key R&D Program of China [grant number 2018YFC1602105] Ministry of Science and Technology of China; The Key Areas Research Development Projects of Guangdong Province [grant numbers 2019B020210001, 2019B020210002]; Medical Scientific Research Foundation of Guangdong Province, China [grant number A2019431]. Data availability statement The data that supports the findings in this study are available in the supplementary material of this article. The complete dataset is available from the researchers upon request. References Aspray TJ, Hill TR (2019) Osteoporosis and the Ageing Skeleton. 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Nature communications 8: 16003. https://doi.org/10.1038/ncomms16003 Xu K, Lu C, Ren X, Wang J, Xu P, Zhang Y (2021) Overexpression of HIF-1alpha enhances the protective effect of mitophagy on steroid-induced osteocytes apoptosis. Environmental toxicology 36 (11): 2123–2137. https://doi.org/10.1002/tox.23327 Additional Declarations No competing interests reported. Supplementary Files Supplementarymaterial20220730.docx Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Major revision 23 Aug, 2022 Editor assigned by journal 23 Aug, 2022 Submission checks completed at journal 22 Aug, 2022 First submitted to journal 22 Aug, 2022 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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Statistical significance in treated groups vs control were shown as \u003csup\u003e*\u003c/sup\u003e\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05, \u003csup\u003e**\u003c/sup\u003e\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01. Osteogenesis assay of RRP, EC, HMM. (b) effect of RRP, EC, HMM on ALP staining after 7-day culture with differentiation medium; (c) Alizarin red S staining after 21-day culture with differentiation medium containing different concentration of RRP, EC, HMM.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-1987008/v1/1749848331aef30068f4c59a.png"},{"id":25712523,"identity":"a85c2fc6-df8f-43a9-a78c-bf37a778a818","added_by":"auto","created_at":"2022-08-26 14:57:14","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":375930,"visible":true,"origin":"","legend":"\u003cp\u003e(a) Body weight trend of osteoporosis model rats during the experiment. (b) ALT, AST, (c) Trap and ALP levels of rat serum. (d) The BMD and BMC of the rat femur detected by dual-energy X-ray absorptiometry. shown as \u003csup\u003e*\u003c/sup\u003e\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05, \u003csup\u003e**\u003c/sup\u003e\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-1987008/v1/1e378f8229e22067556ff5d7.png"},{"id":25712526,"identity":"fc9098fe-10dd-4545-99c1-513bdb0131a2","added_by":"auto","created_at":"2022-08-26 14:57:14","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":3095656,"visible":true,"origin":"","legend":"\u003cp\u003eNetwork of targets predicted using the EC-derived compounds. Green nodes represent the active compounds, the blue nodes represent the predicted targets and darker blue nodes represent the common targets. The edges represent the interaction between compounds and targets, and the node size is proportional to the degree of interaction.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-1987008/v1/536fb9f31da045cee41b5822.png"},{"id":25712527,"identity":"7f58d624-c489-4201-afd2-897a2cc7bc95","added_by":"auto","created_at":"2022-08-26 14:57:14","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":5802282,"visible":true,"origin":"","legend":"\u003cp\u003e(a) The 128matched targets common between the predicted EC targets and the osteoporosis-associated targets. (b) the interaction network of compounds and common target.\u0026nbsp;\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-1987008/v1/9823be305c1cc2b032d5ba6a.png"},{"id":25712919,"identity":"a03b718f-cc77-4b6c-ba42-e0c92d65a5cc","added_by":"auto","created_at":"2022-08-26 15:02:14","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":5037905,"visible":true,"origin":"","legend":"\u003cp\u003eThe PPI network of common target genes constructed using Cytoscape and analyzed using Network Analyzer. Node size correspond to the degree of target genes.\u003c/p\u003e","description":"","filename":"Figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-1987008/v1/4e2534f2fc64d6e9150c30c6.png"},{"id":25713031,"identity":"9ccd9545-7121-4f12-a829-cce95a78dcc4","added_by":"auto","created_at":"2022-08-26 15:07:14","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":14501292,"visible":true,"origin":"","legend":"\u003cp\u003e(a) The interaction network of KEGG pathways and common targets. (b)KEGG pathway enrichment analysis of the anti-osteoporosis targets of EC. Pathway enrichment results at P \u0026lt; 0.01.\u0026nbsp;\u003c/p\u003e","description":"","filename":"Figure6.png","url":"https://assets-eu.researchsquare.com/files/rs-1987008/v1/d7d32af97835777944af0e3a.png"},{"id":25712530,"identity":"3bd5ee59-aaa1-4c8a-815e-d380f1e76122","added_by":"auto","created_at":"2022-08-26 14:57:14","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":1794197,"visible":true,"origin":"","legend":"\u003cp\u003e(a) Venn diagram comparison of DEGs from cluster EC-vs-Con and NC-vs-Con. (b) the PPI network of common DEGs. Node size correspond to the degree of DEGs. Results of RNA-sequencing were shown as heat map for (c) NC-vs-Con (d) EC-vs-Con. Volcano plot of differentially expressed genes post-treated (green or orange represents the significantly up or down-regulated genes and gray for non-significant) between (e) NC and Con, (f) Con and EC.\u003c/p\u003e","description":"","filename":"Figure7.png","url":"https://assets-eu.researchsquare.com/files/rs-1987008/v1/b133be7cf4beae7bacd229f4.png"},{"id":25713032,"identity":"2621300e-e1af-4af3-9a5a-021560221afa","added_by":"auto","created_at":"2022-08-26 15:07:17","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":624987,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-1987008/v1/e49a97dc-9c51-4088-98a4-0dc737a3dca6.pdf"},{"id":25712524,"identity":"f448c771-f151-4ab8-9462-0a1b55bec333","added_by":"auto","created_at":"2022-08-26 14:57:14","extension":"docx","order_by":11,"title":"","display":"","copyAsset":false,"role":"supplement","size":2001894,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarymaterial20220730.docx","url":"https://assets-eu.researchsquare.com/files/rs-1987008/v1/c0d94b1edea30b110857c947.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Elucidate the potential mechanism of Eucommiae Cortex against osteoporosis by network pharmacology and RNA-sequencing ","fulltext":[{"header":"Introduction","content":"\u003cp\u003eOsteoporosis is a kind of metabolic diseases accompanied by bone loss, bone microstructure changes, resulting in bone systemic metabolic bone disease that increases fragility and is prone to pathological fractures[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. As considerable burden to affected persons, caregivers and society, osteoporotic fractures and osteoporosis have become the major public health problems worldwide. The prevalence of osteoporotic fractures in the Chinese population is uncertain and few individuals receive drug treatment to prevent fracture. Other studies indicate that about 6.5% of the population in China was treated with anti-osteoporotic agents under 6 months after the fracture had occurred[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Bone remodeling approves catabolic of old and damaged bone. The maintenance of mineral and acid-base homoeostasis also supports by bone turnover [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].Menopause often chaperones decline of estrogens levels which lead to acceleration of bone resorption and finally result in postmenopausal osteoporosis[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. In molecular biology, bone turnover based on the activity of bone resorbing cells (also commonly known as osteoclasts) and bone forming cells (also commonly known as osteoblasts)[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Estrogen can also directly inhibit bone remodeling, decrease bone resorption and active bone formation by acting on osteocytes, osteoclasts and osteoblasts[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. However, estrogen therapy of postmenopausal osteoporosis brings about high risk of breast carcinoma[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Thus, a higher efficacy and safety therapeutic strategy are urgent to lucubrate for the prevention and treatment of osteoporosis.\u003c/p\u003e \u003cp\u003ePossessing the properties of safety, good efficacy, few side effects, traditional Chinese medicine (TCM) becomes a novel strategy to prevent and treat diverse diseases[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. To improve the safety and efficiency, further molecular mechanism of TCM was urged to be verified. Multi-component characteristics of the TCMs contribute to the relatively complex biological molecular mechanism, which had augmented the difficulty of further investigation in molecular mechanism of TCMs by animal or cellular studies[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. A comprehensive analysis method was necessary to put forward.\u003c/p\u003e \u003cp\u003eAs an approach to analysis including network analysis, systems biology, connectivity, redundancy and pleiotropy, network pharmacology has offered a way of thinking about the mechanism investigation of TCMs and provided a novel strategy to probe the correlation between TCMs and diseases[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eWe had searched and identified TCMs therapy of osteoporosis relevant studies from China National Knowledge Infrastructure (CNKI, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e\u003ca href=\"http://www.cnki.net\" target=\"_blank\"\u003ewww.cnki.net\u003c/a\u003e\u003c/span\u003e\u003cspan address=\"http://www.cnki.net\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) and the Wan fang Database(\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e\u003ca href=\"http://www.cnki.net\" target=\"_blank\"\u003ewww.wanfangdata.com.cn\u003c/a\u003e\u003c/span\u003e\u003cspan address=\"http://www.wanfangdata.com.cn\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), gathering and analyzing the TCMs compound preparation. The TCMs were mainly applied in clinical compound preparation for osteoporosis therapy such as xianlingubao[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], dangguibuxue tang[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], erxian decoction[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e], Qing' E Formula[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]and many of others, that were gathered for the subsequent studies. The alternative TCMs were as followed: Rehmanniae Radix Praeparata (RRP) from \u003cem\u003eRehmannia glutinosa Libosch., root\u003c/em\u003e, Hedysarum Multijugum Maxim (HMM) from \u003cem\u003eAstragalus membranaceus, root\u003c/em\u003e, Eucommiae Cortex (EC) from \u003cem\u003eEucommia ulmoides Oliv., cortex\u003c/em\u003e.\u003c/p\u003e \u003cp\u003eAmong the alternative TCMs, Eucommiae Cortex(EC)is a TCM with extensive medicinal value, which is derived from the dried bark of \u003cem\u003eEucommia ulmoides Oliv.\u003c/em\u003e[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. EC can be used as the nourishment of liver and kidney, enhancement of the muscles and bones, prevention of abortion in Chinese Pharmacopoeia[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Because of the multifunction like antidiabetic, anti-hypertension, anti-obesity, anti-osteoporosis, anti-inflammatory, anti-thrombotic, and anti-tumor activities, EC has caught considerable attention over the years[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Nevertheless, anti-osteoporosis efficiency of EC remains to be further explored. There are few existing studies on the anti-osteoporosis effect of EC, among which experimental method is mainly used for OVX- rats[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e], SAMP6 model[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e] and MC3T3-E1 pre-osteoblasts[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. We adopted the combination of in vitro and in vivo methods to illustrate the anti-osteoporosis ability of EC. As methods of bioinformatics analysis, network pharmacology is underpinned by the interaction network consist of gene, protein target and disease[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Deep exploration of EC against osteoporosis molecular mechanisms using network pharmacology is of great significance. High-throughput sequencing was applied to compare with the results of network pharmacology.\u003c/p\u003e \u003cp\u003eTherefore, functional verification of EC was carried out on \u003cem\u003ein vitro\u003c/em\u003e and in vivo osteogenesis assay, bioinformatics analysis and high-throughput sequencing was utilized to find out the potential mechanism of EC to treat OP in this study.\u003c/p\u003e"},{"header":"Materials And Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eMaterials\u003c/h2\u003e \u003cp\u003eThe extract of TCMs were provided by Inifinus (China) Company Ltd. (Guangzhou, China), including Rehmanniae Radix Praeparata (Batch Number: CSDH-C-924188), Hedysarum Multijugum Maxim (Batch Number: CHNQ-A-901371), Eucommiae Cortex (Batch Number: CDUZ-C-923806). All subjects were stored in sealed, away from light environment, normal temperature, dry conditions. More information including subjects, abbreviations, plant origin, extraction solvent, extraction ratio were shown in Table S1.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eCytotoxicity assay\u003c/h2\u003e \u003cp\u003ePreosteoblast MC3T3-E1 cells (iCell-m031) were purchased from iCell Bioscience Inc (Shanghai, China). Cell were cultured in α-MEM culture medium which was supplemented with 10% fetal bovine serum (FBS), 100 \u0026micro;g/ml streptomycin and 100 U/mL penicillin at 37℃with a humidified 5% CO2 atmosphere. The accessory factors (50 \u0026micro;g/ml ascorbic acid and 5 mM β-glycerophosphate) were added to induce differentiation. Cytotoxicity was measured using the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazoliumbromide (MTT) assay. Briefly, after seeded in 96-well plates for 24h, the cells were incubated in the media containing various concentrations of 15 candidates TCMs (0, 0.1, 1, 5, 10,50\u0026micro;g/mL). While 48h incubation was finished, culture medium was replaced by 100\u0026micro;Lfresh media containing0.05% MTT for an additional 4 hours. After discarding the supernatant, 200 \u0026micro;L dimethyl sulfoxide were added to each well to dissolve the insoluble formazan products, and the absorbance at 570nm of each well was detected using a microplate spectrophotometer (Thermo Fisher Scientific, MA, USA).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eAlkaline phosphatase (ALP) staining\u003c/h2\u003e \u003cp\u003eTo evaluated the ALP activity of treaded cells, MC3T3-E1 cells were incubated in medium with TCMs of different concentration and osteogenic inducing medium for 7 days. Then, a BCIP/NBT Alkaline Phosphatase Color Development Kit (Beyotime Biotechnology, Shanghai, China) was utilized according to the protocol. After fixing in 4% polyformaldehyde for 30min, the cells were washed with PBS and then react with the BCIP/NBT dye for 30 min. The Nikon Eclipse Ti-S fluorescence microscope (NIKON, Japan) was applied to capture.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eBone mineralization assay\u003c/h2\u003e \u003cp\u003eTo assess the degree of bone mineralization, MC3T3-E1 cells were incubated in inducing medium with various concentrations of EC (0, 1, 5, 10, 20 \u0026micro;g/mL) for 21 days and medium was replaced every three days. After treated, the cells were washed with PBS and fixed with 4% polyformaldehyde for 30 min. the fixed cells were stained with Alizarin red S solution (Solarbio, Beijing, China) (1%, pH 4.2) for 2 h at room temperature and washed by distilled water three times to wipe off the excess solution before captured with Nikon Eclipse Ti-S fluorescence microscope (NIKON, Japan).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eAlkaline phosphatase (ALP) assay\u003c/h2\u003e \u003cp\u003eTo investigate the ALP activity of EC-treated MC3T3-E1 cells, the cells were seeded and allowed to attach for 24 h, then cultured with different concentration of 4 TCMs (0, 1, 5, 10, 20 \u0026micro;g/mL) for 7days and were measured using enzymatic assay (Beyotime Institute of Biotechnology, Shanghai, China). Briefly, cells were obtained and mixed with the protease inhibitor free lysis buffer (Beyotime Institute of Biotechnology, Shanghai, China) on ice, and the lysate was collected to centrifuge for 10 minutes under 12,000 rpm. After incubated with substrate for 30 min at 37 \u003csup\u003eo\u003c/sup\u003eC, the absorbance of each well was detected with a microplate spectrophotometer under 405nm. The nmol of p-nitrophenyl phosphate(pNP) produced per mg protein per assay time represents the ALP activity.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eEstablishment of osteoporosis models\u003c/h2\u003e \u003cp\u003eTo further verify the osteogenesis ability of EC, osteoporosis model was utilized for evaluation. Healthy 12 weeks old female specific-pathogen-free Sprague Dawley rats were purchased from Guangdong Medical Laboratory Animal Center and undergo bilateral ovariectomy. Briefly, the osteoporosis model rat was established by bilateral ovariectomy under anesthesia. SD rats were randomly divided into three groups as follows: sham operation group (n\u0026thinsp;=\u0026thinsp;10), OVX group (n\u0026thinsp;=\u0026thinsp;10) and OVX combined with EC group (500mg/kg BW, equal to 30 times of human clinical dose). The sham operation group was subjected to sham operation, while OVX group and OVX combined with EC group were surgically ovariectomized. Above groups were performed the operation under anesthesia of isoflurane and which were pre-fasting for 12h. After 2 weeks of postoperative recovery, the EC extract solution was intragastrically administrated for OVX combined with EC group, while purified water for sham operation and OVX group every day for 18 weeks. After the experiment, serum was prepared by centrifugation of the whole blood which was drawn from all rats under anesthesia at 3000 rpm for 10 min and femurs were removed after the rats were sacrificed. All experimental procedures were approved by the Ethics Committee of Guangzhou Center for Disease Control and Prevention.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eMeasurement of biochemical indicators\u003c/h2\u003e \u003cp\u003eAs markers of osteogenesis, serum ALP levels were measured by Alkaline Phosphatase Assay Kit (Beyotime Institute of Biotechnology, Shanghai, China), and serum TRAP levels were measured by Tartrate Resistant Acid Phosphatase Assay Kit to evaluate the condition of bone resorption. Biochemical indicators of serum alanine aminotransferase (ALT) and aspartate aminotransferase (AST) levels were detected by automatic biochemistry analyzer (7600-020, Hitachi, Tokyo, Japan) to evaluate the liver function.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eMeasurement of BMC and BMD\u003c/h2\u003e \u003cp\u003eMeasurements of BMC and BMD of femurs were performed with Dual Energy X-Ray Absorptiometry (Hologic, Inc., USA). The right femur that needed to be measured was removed after the rats were sacrificed. The area that was needed to be scanned is automatically identified by the instrument and the stationary area detector uses ultra-high-resolution pixels.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eData preparation\u003c/h2\u003e \u003cdiv id=\"Sec12\" class=\"Section3\"\u003e \u003ch2\u003eIdentification of active ingredients in EC\u003c/h2\u003e \u003cp\u003eTraditional Chinese Medicine Systems Pharmacology Database (TCMSP) (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://tcmsp-e.com/\u003c/span\u003e\u003cspan address=\"https://tcmsp-e.com/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), Bioinformatics Analysis Tool for Molecular mechanism of Traditional Chinese Medicine (BATMAN-TCM)(\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://bionet.ncpsb.org/batman-tcm/\u003c/span\u003e\u003cspan address=\"http://bionet.ncpsb.org/batman-tcm/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) and the Traditional Chinese Medicine Information Database (TCM-ID) (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.megabionet.org/tcmid/\u003c/span\u003e\u003cspan address=\"http://www.megabionet.org/tcmid/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) were used to retrieve the components of EC. The condition of oral bioavailability (OB) and drug similarity (DL) larger than 0.18 and 30% respectively, which were set to contract the candidate active compounds of EC, and then those 2D molecular structure were verified and obtained by PubChem database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://pubchem.ncbi.nlm.nih.gov/\u003c/span\u003e\u003cspan address=\"https://pubchem.ncbi.nlm.nih.gov/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section3\"\u003e \u003ch2\u003eTargets prediction and screening of active ingredients in EC\u003c/h2\u003e \u003cp\u003eBioactivities of candidate compounds were screened with the following conditions in SwissADME (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.swissadme.ch/\u003c/span\u003e\u003cspan address=\"http://www.swissadme.ch/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) database. GI absorption should be shown as \u0026lsquo;High\u0026rsquo; and both of parameters like Lipinski, Ghose, Veber, Egan, and Muegge should be shown as \u0026lsquo;Yes\u0026rsquo;. The putative target of qualified active ingredients were gathered from the SwissTargetPrediction (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.swisstargetprediction.ch/)databas\u003c/span\u003e\u003cspan address=\"http://www.swisstargetprediction.ch/)databas\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003ee, and recruit criteria were probability\u0026thinsp;\u0026gt;\u0026thinsp;0.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section3\"\u003e \u003ch2\u003eRelated targets collection of osteoporosis\u003c/h2\u003e \u003cp\u003eThe target organism was set as Homo sapiens, then, osteoporosis-associated targets were collected from three databases namely Online Mendelian Inheritance in Man database (OMIM, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.omim.org/\u003c/span\u003e\u003cspan address=\"https://www.omim.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), DisGeNET database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.disgenet.org/\u003c/span\u003e\u003cspan address=\"https://www.disgenet.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) and GeneCards database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.genecards.org/\u003c/span\u003e\u003cspan address=\"https://www.genecards.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). The key word \u0026ldquo;osteoporosis\u0026rdquo; was used to search the disease-targets in the three databases and the integrating disease-targets were prepared for network construction subsequently.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eNetwork construction\u003c/h2\u003e \u003cdiv id=\"Sec16\" class=\"Section3\"\u003e \u003ch2\u003eComparation and analyzation of EC-targets and osteoporosis-associated targets\u003c/h2\u003e \u003cp\u003eA dataset containing the common targets, scilicet OP relative targets that base on the EC components predictive targets were obtained. Interaction network was constructed and analyzed by Cytoscape 3.8 and common targets were obtained by Venny 2.1.0 (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://bioinfogp.cnb.csic.es/tools/venny/index.html\u003c/span\u003e\u003cspan address=\"https://bioinfogp.cnb.csic.es/tools/venny/index.html\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). After obtaining the common target of osteoporosis-associated targets and predicted EC targets, the interaction network between the active ingredient and the target gene was also constructed.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section3\"\u003e \u003ch2\u003eProtein-protein interaction (PPI) network construction\u003c/h2\u003e \u003cp\u003eSTRING database was used to import the official gene name of the OP relative targets that base on the EC components to construct the PPI network with Homo sapiens as the target organism. To investigate the interactions of target genes and to obtain the parameters of PPI network, the results of the STRING database were imported into Cytoscape (version 3.8) and calculated by Network Analyzer.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section3\"\u003e \u003ch2\u003eBioinformatics analyses\u003c/h2\u003e \u003cp\u003eTo investigate the core mechanism of the pathway and biological process that associated with EC and OP, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and Gene Ontology (GO) enrichment analyses were conducted to access the critical information. DAVID Bioinformatics Resources 6.8(\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) was employed to process the KEGG pathway and GO enrichment analysis of hub co-targets in PPI network which was successfully constructed. The acquired terms match the condition of p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 and Benjamini-Hochberg (BH) value lower than 0.5 were considered as meaningful and ponderable. Results visualization were implemented by using R software.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section3\"\u003e \u003ch2\u003eRNA-seq analysis\u003c/h2\u003e \u003cp\u003eThe RNA-seq assay was carried out with total RNA that extracted from of MC3T3-E1 cells using the TRIzol reagent (Invitrogen), and then RNA-seq analysis were performed by the Beijing Genomics Institute (BGI) (Shenzhen, China) via the BGISEQ-500 platform (BGI, Wuhan, China). The FPKM mapped was utilized to calculate the gene expression levels and gene with FPKM larger than 1 were recruited for analysis and exhibition. Fold changes (FC) were considered as significant when the absolute value (Log2FC) is greater than 0.5, with a Q value\u0026thinsp;\u0026lt;\u0026thinsp;0.05. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and Gene ontology (GO) enrichment analyses were conducted to analyze the differential gene.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eThe mean and standard deviation were used to express the raw data, at least three replicates were implemented for each sample. ANOVA were used to analyze the between-group differences. Visualization of statistical analysis and calculation of Tuckey\u0026rsquo;s HSD test was obtained by GraphPad Prism 6 software (GraphPad software Inc., La Jolla, CA).\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec22\" class=\"Section2\"\u003e\n\u003ch2\u003eCell viability and osteogenesis ability evaluation of candidate TCM\u003c/h2\u003e\n\u003cp\u003eAs a preliminary screening, 3 TCMs were chosen to process a cell viability assay, including RRP, HMM and EC. As showed in Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003ea, all 3 TCMs had shown no viable damage of MC3T3-E1 cells at the concentration of 0.1 to 50 \u0026micro;g/mL, which showed TCMs would not inhibit the proliferation of cells. In accordance with proliferating promotion of MC3T3-E1, RRP, EC, HMM were chosen for the subsequent osteogenesis experiments.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec23\" class=\"Section2\"\u003e\n\u003ch2\u003eThe ability of Osteogenesis Promotion of candidate TCMs\u003c/h2\u003e\n\u003cp\u003eThe dose of 0.1, 1, 5, 10\u0026micro;g/mL TCMs (RRP, EC and HMM) was used in the subsequent experiment, scilicet ALP staining assay and mineralization assays. As showed in the result, RRP, EC and HMM were evaluated the ALP activity significantly in a 7-day culture compared to the control-treated cultures (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eb). Meanwhile, Alizarin Red S staining assay demonstrated that RRP, EC and HMM increased the matrix mineralization of MC3T3-E1 cells in a 21-day culture compared to the control group (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003ec). An optimum concentration of 1 \u0026micro;g/mL was equal among 3 TCMs for stimulating osteoblastic differentiation. Then EC was selected for further evaluated.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec24\" class=\"Section2\"\u003e\n\u003ch2\u003eEC attenuated the loss of bone mass in osteoporosis model rats\u003c/h2\u003e\n\u003cp\u003eBody weight of both OVX groups were significantly increased compare to sham operation group (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003ea). As markers of bone transformation, Trap and ALP were significantly increased in the model group respectively compared with the sham operation group, indicating that bone metabolism was exuberant and bone metabolism diseases occurred (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003ec). Comparing with the model group, Trap and ALP levels of the EC-treated group had slightly recovered, indicating that the EC has the effect of alleviating bone loss. The alternative trend of liver function indexes was also up regulated in model group and restored in the EC group (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eb), indicating that the EC had an additional effect of liver protection. To explore the actual changes in bone mass, dual-energy X-ray absorptiometry was used to detect the BMD and BMC of the rat femur. The results showed that the BMD and BMC of the model group were both decreased, while the EC treatment group showed an increase in BMD and BMC compared with the model group (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003ed). The above results indicated that EC possess the effect of alleviating osteoporosis and had additional liver protection.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec25\" class=\"Section2\"\u003e\n\u003ch2\u003eNetwork pharmacology analysis\u003c/h2\u003e\n\u003cdiv id=\"Sec26\" class=\"Section3\"\u003e\n\u003ch2\u003eActive ingredients of EC and Target prediction\u003c/h2\u003e\n\u003cp\u003eA total number of 215 active compounds of EC were collected from three databases initially. The result of each database was as followed: A total of 28 compounds in TCMSP, a total of 128 compounds in TCMID and a total of 59 compounds in BATMANTCM. After removing the replicated compounds and were verified by PubChem, a total number of 86 ingredients were identified according to the corresponding 2D structures from PubChem after which were screened by the SwissADME, and a total of 19 ingredients in EC were recruited for the next investigation (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). Because of the synergistic action among multiple compounds and the target genes had determined the effectiveness of the EC against OP, targets prediction of ingredients found out to be critical to proceed. Thus, putative targets of 19 candidate compounds were intended to be predicted by SwissTargetPrediction subsequently. A total of 527 target genes were obtained and prepared for network construction with Cytoscape (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e). According to EC active compounds and predictive target gene, a total number of 561 nodes and 2586 edges were obtained and analyzed for the network.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003ctable id=\"Tab1\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eThe 19 active compounds of EC.\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eID\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eCID\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eName\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eDatabase\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMol 1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e73117\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e(+)-Eudesmin\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eTCMSP\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMol 2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e73399\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePinoresinol\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eTCMID\u003c/p\u003e\n\u003cp\u003eBATMAN-TCM\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMol 3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e91458\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAucubin\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eTCMID\u003c/p\u003e\n\u003cp\u003eBATMAN-TCM\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMol 4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e94175\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eEpiquinidine\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eTCMID\u003c/p\u003e\n\u003cp\u003eBATMAN-TCM\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMol 5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e94253\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eVulgarin\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eTCMID\u003c/p\u003e\n\u003cp\u003eBATMAN-TCM\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMol 6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e165225\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eDehydrodieugenol\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eTCMSP\u003c/p\u003e\n\u003cp\u003eTCMID\u003c/p\u003e\n\u003cp\u003eBATMAN-TCM\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMol 7\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e181681\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMedioresinol\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eTCMSP\u003c/p\u003e\n\u003cp\u003eTCMID\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMol 8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e443028\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYangambin\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eTCMSP\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMol 9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e637584\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eEpipinoresinol\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eTCMID\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMol 10\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e717531\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3,4-Dimethoxycinnamic acid\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eTCMID\u003c/p\u003e\n\u003cp\u003eBATMAN-TCM\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMol 11\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e5280457\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePinosylvin\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eTCMID\u003c/p\u003e\n\u003cp\u003eBATMAN-TCM\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMol 12\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e5280489\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ebeta-Carotene\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eTCMSP\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMol 13\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e5280863\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eKaempferol\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eTCMSP\u003c/p\u003e\n\u003cp\u003eTCMID\u003c/p\u003e\n\u003cp\u003eBATMAN-TCM\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMol 14\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e5280961\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eGenistein\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eTCMID\u003c/p\u003e\n\u003cp\u003eBATMAN-TCM\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMol 15\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e5281953\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSyringetin\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eTCMSP\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMol 16\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e5317205\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eErythraline\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eTCMSP\u003c/p\u003e\n\u003cp\u003eTCMID\u003c/p\u003e\n\u003cp\u003eBATMAN-TCM\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMol 17\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e5320287\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eOmbuin\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eTCMID\u003c/p\u003e\n\u003cp\u003eBATMAN-TCM\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMol 18\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e5351950\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eTabernemontanine\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eTCMID\u003c/p\u003e\n\u003cp\u003eBATMAN-TCM\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMol 19\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e6710676\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eKobusone\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eTCMSP\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTo explore the relationship of target gene between OP and EC, OMIM, DisGeNet and GeneCards database were employed to retrieve osteoporosis-related targets. A total of 191, 172 and 1032 targets were collected from three databases respectively and then the result was integrated and after the reduplicative data were removed. Retrieval osteoporosis relative targets by count of 1179 were compared with the predicted EC targets to gather 124 common targets (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003ea). These124 common targets became follow-up subjects that represent potentially significant in the mechanism of EC influences osteoporosis.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec27\" class=\"Section3\"\u003e\n\u003ch2\u003eConstruction and analysis of compounds-Target Interaction network\u003c/h2\u003e\n\u003cp\u003eCompounds-target interaction network was constructed with the common target of EC compounds and osteoporosis-associated proteins, which consist of 143 nodes and 309 edges (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eb). According the connections of targets, top six of degree were identified as Genistein (Mol14) with degree equal to 32, Vulgarin (Mol5) with degree equal to 29, Ombuin (Mol17) with degree equal to 29, Syringetin (Mol15) with degree equal to 29, Pinosylvin (Mol11) with degree equal to 28 and Kaempferol (Mol13) with degree equal to 28, indicating that flavonol and isoflavone are critical components in EC against OP.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec28\" class=\"Section3\"\u003e\n\u003ch2\u003ePPI network of common targets between compounds\u003c/h2\u003e\n\u003cp\u003eSTRING database was utilized to construct a network consisting of 124 common targets. To understand how multiple targets function in complicated illnesses like OP, the PPI networks become an indispensable research method. The PPI network that was construed with 124 common targets had shown in Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e. The genes Akt1, MAPK3, EGFR, CASP3, SRC, MAPK1, STAT3, PTGS2, ESR1, CXCL8, MMP9 with node degree higher than 50 were regarded as the critical targets influenced by EC. To help focus on the key node, that degree greater than 20 were selected to construct a PPI network the cluster consisted of 54 nodes and 755 edges. Critical nodes with greater degree were present in the colour of light red as AKT1, EGFR, MAPK3, CASP3 and SRC (Fig. S1). KEGG and GO enrichment analysis.\u003c/p\u003e\n\u003cp\u003eTo find out the mechanisms of the EC against osteoporosis, a total of 124 common target of EC and OP were analysis by KEGG and GO enrichment using DAVID. Results of enrichment were visualized by R software in the form of a bubble diagram (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003eb). Top three of high degree nodes AKT1, MAPK3 and EGFR were mainly implicated in HIF-1 signaling pathway, estrogen signaling pathway, thyroid hormone signaling pathway, VEGF signaling pathway. Numerous investigations indicate that estrogen signaling pathway was closely related postmenopausal osteoporosis. To visualize the relationship between signal pathways and critical genes, network was constructed with the filtered data using the Cytoscape software (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003ea).\u003c/p\u003e\n\u003cp\u003eTake the GO enrichment results together, counts of genes and \u003cem\u003eP\u003c/em\u003e value were critical parameters to filter the term of biological processes, molecular function and cellular component. On the basis of the condition above, biological processes involving in EC against OP were phosphatidylinositol-mediated signaling, protein autophosphorylation, regulation of phosphatidylinositol 3-kinase signaling, signal transduction and platelet activation (Fig. S2). The molecular function involving in EC against OP were steroid binding, enzyme binding, insulin-like growth factor I binding, phosphatidylinositol-4,5-bisphosphate 3-kinase activity and heme binding (Fig. S2). The cellular component involving in EC against OP were plasma membrane, extracellular space, protein complex, caveola and phosphatidylinositol 3-kinase complex. The enrichment results showed that the mechanism of EC against OP was associated with a battery of steroid hormone biochemical reaction and phosphatidylinositol 3-kinase activity (Fig. S2).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec29\" class=\"Section3\"\u003e\n\u003ch2\u003eTranscriptome profiling and functional enrichment analysis of High-throughput sequencing\u003c/h2\u003e\n\u003cp\u003eTo ensure the reliability of the results, the raw data of sequencing contains reads with low quality, adapter contamination, and high nitrogen content of unknown bases were removed before data analysis. According to the selection criteria for DEGs, 52 DEGs were identified between EC group and Con group (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003ec, f), and 6418 DEGs were identified between the NC group and Con group (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003ed, e). Moreover, 40 common DEGs were founded according to comparison of two clusters of DEGs, which were used for subsequent analysis.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec30\" class=\"Section3\"\u003e\n\u003ch2\u003ePPI network construction and enrichment analysis of DEGs\u003c/h2\u003e\n\u003cp\u003eTo demonstrate the results from RNA-sequencing, overlapping targets were recruited according the comparison of Con vs NC group and EC vs Con group (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003ea). Then, 40 mouse DEGs were converted to human gene name and a total of 35 genes name were returned by the UniProt database. The PPI network was analyzed using the STRING database and visualized by Cytoscape software with 24 recruited genes, after removing the unclustered data, the network was shown in Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003eb.\u003c/p\u003e\n\u003cp\u003eKEGG pathway enrichment of 35 converted common genes were conducted by DAVID database. A total of 3 terms were returned with P\u0026thinsp;\u0026lt;\u0026thinsp;0.05, which were HIF-1 signaling pathway, Central carbon metabolism in cancer and Apelin signaling pathway, as shown in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e. The first two pathways were also returned from DAVID database in network pharmacology analysis.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003ctable id=\"Tab2\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eAnnotation of KEGG pathways\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eTerm ID\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eDescription\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eCount\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eGenes\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ehsa04066\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eHIF-1 signaling pathway\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.0020\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eEGLN1, PFKL, SLC2A1, HK2\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ehsa05230\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eCentral carbon metabolism in cancer\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.0114\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePFKL, SLC2A1, HK2\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ehsa04371\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eApelin signaling pathway\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.0412\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eEGR1, CCN2, APLN\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ehsa00052\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eGalactose metabolism\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.0702\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePFKL, HK2\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ehsa00051\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eFructose and mannose metabolism\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.0746\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePFKL, HK2\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ehsa05166\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eHuman T-cell leukemia virus 1 infection\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.0940\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eEGR1, SLC2A1, FOS\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/div\u003e\n\u003cp\u003eTo further explore the molecular mechanisms of the EC anti-osteoporotic activity, GO enrichment was conducted and take the results together, counts of genes and \u003cem\u003eP\u003c/em\u003e value were critical parameters to filter the term of biological processes, molecular function and cellular component. Total numbers of 17, 5 and 5 were the results returned from GO enrichment corresponding to BP, CC, MF. Detailed information of the GO enrichment is presented in Tables S2, S3 and S4. A significative term was returned as a response to estradiol in biological processes indicating that anti-osteoporotic effect of EC involving estradiol related biological processes.\u003c/p\u003e\n\u003c/div\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eNetwork pharmacology has been ubiquitously used as a rational strategy to analyze the potential biological mechanism of TCMs. The basic concept of Network pharmacology is regarding the drug action as the result of interactions network, rather than a single specific action[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Due to the complicate components, the action mechanisms of Chinese medicines are often elusive [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Thus, it is significant to integrate network pharmacology to provide a holistic view for the molecular mechanism of Chinese medicines[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. OP is a common form of secondary osteoporosis, which has been a risk factor of fracture among many patients, especially in postmenopausal women[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Estrogen is a main hormonal regulator of bone metabolism both in women and men. Deficiency of estrogen is common in senile people and usually accompanied by postmenopausal osteoporosis[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. According to the results of \u003cem\u003ein vitro\u003c/em\u003e experiment, EC had shown well osteogenesis ability, the mechanism of EC against osteoporosis was profound significative to be investigated, particularly of the influence of estrogen.\u003c/p\u003e \u003cp\u003eIn this study 3 TCMs were selected for cytotoxicity assay according to the literature and then were performed osteogenic assay for osteogenic capability assessment. After primary evaluation as preeminent osteogenesis ability, EC was chosen for the in vivo assessment of osteogenic capability with osteoporosis model rats and the potential anti-osteoporosis molecular mechanism investigation utilizing network pharmacology and RNA-seq analysis. In vivo experiments show that EC can alleviate the bone loss caused by bilateral ovariectomy and possess additional liver protective effects. Although the EC had the effect of alleviating bone loss, the changes in bone mass were less pronounced, possibly due to the limitations of the trial period.\u003c/p\u003e \u003cp\u003eIn the mechanism exploration section, we collected 86 EC compounds from TCMSP, TCMD and BATMAN TCM after were verified by PubChem, and 19 compounds were selected by ADME and conduct follow-up targets prediction in Swiss Target Prediction and a total of 527 target gene were identified. According to EC active compounds and predictive target gene, a network with 546 nodes and 1174 edges was constructed and analyzed. With the utilization of OMIM, GeneCards and DisGeNet databases, a count of1179 OP- related gene entries were collected. After comparing with the predicted EC targets, we had collected 124 common targets as the key targets for subsequent mechanism research of the EC compounds. Compounds-targets network was constructed according to the common targets, results indicating that flavonol and isoflavone are critical components in EC against OP. Flavonoids are naturally occurring bioactive polyphenols with anti-inflammatory and antioxidant properties, and some studies have suggested a link between flavonoid intake and bone health[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. As two important active ingredients in flavonoids, flavonols and isoflavone were revealed that possess the ability of osteoclastogenesis and osteoprotection[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eCandidate targets were identified based on PPI network analysis, key nodes were obtained as Akt1, MAPK3, EGFR, CASP3, SRC, MAPK1, STAT3, PTGS2, ESR1, CXCL8, MMP9 according to the degree of each node. To explore the KEGG pathway and GO enrichment, all assumed target genes were gathered for the following investigation. A total number of 33 KEGG pathway terms were collected and classified to visualize as a bubble diagram. Results of GO enrichment were also visualized by a bubble diagram.\u003c/p\u003e \u003cp\u003eThe key nodes mostly belong to HIF-1(hypoxia-inducible factor 1) signaling pathway and estrogen signaling pathway, following by thyroid hormone signaling pathway and VEGF signaling pathway. Playing an essential role to maintain the oxygen homeostasis inside the metazoan organisms, α-subunit of HIF-1 factor is regulated by hypoxia as functional subunit[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. As an indispensable member of HIF-1 signaling pathway regulating hypoxia reactions, Hypoxia-inducible factor‐1α (HIF‐1α) playing an important role in bone modeling, remodeling, and homeostasis[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. As a transcription factor, HIF-1α crucially function in regulating VEGF, and VEGF signaling pathway which was also closely related postmenopausal osteoporosis[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAs the results of KEGG pathways return, 7 of 14 associated gene in estrogen signaling pathway were also key node in PPI network, which were SRC, ESR1, MMP9, EGFR, AKT1, MAPK1, MAPK3. The result of the enrichment and analysis had shown that the sex hormone estrogen activates its nuclear receptor ESR1 (estrogen receptor alpha) to trigger the relative components derived growth factors to protect bone loss[\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. As for the Src, plays an indispensable role in adhesion and motility. Recent studies have shown that Src inhibitors may have therapeutic value in tumor suppressor, tumor angiogenesis and bone resorption[\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. Both women and men require estrogen as a major hormonal regulator to maintain bone metabolism[\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. Therefore, the reduction of estrogen consequence in the acceleration of bone resorption, reflecting the importance of estrogen to keep the activation of bone formation at the cellular level[\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. One of the most important biological role of estrogen is to inhibit the maturation of osteoclasts via RANKL/RANK/OPG pathway[\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. What is more, estrogen can effects directly on osteoblasts and osteocytes, which would approve the maintenance of bone formation[\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. Thus, to unravel the pleiotropic effects and profound meaning of the relationship between signal pathways and critical genes in osteoporosis prevention and treatment, another network was constructed. Genes that interact with greater pathways were PIK3CD, PIK3CB, PIK3CG, AKT1, MAPK1, MAPK3 and PIK3CA. The results from RNA-sequencing were also enriched by KEGG pathway and GO enrichment. The HIF-1 signaling pathway was also returned in the results. The gene AkT1, MAPK3 and EGFR were involved in HIF-1 signaling pathway whether in network pharmacology analysis or RNA-sequencing analysis. Several studies have shown that HIF-1 is involved in osteogenesis, osteocytes apoptosis and osteoclast activation[\u003cspan additionalcitationids=\"CR43\" citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. During menopause, estrogen deficiency leads to the accumulation of HIF1α protein in osteoclasts, leading to osteoclast activation and bone loss[\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. The combined effects of EC target genes produced osteogenesis and anti-osteoporosis effects. Main components of EC that target the key node including Epiquinidine, Vulgarin, Dehydrodieugenol, 3,4-Dimethoxycinnamic acid, Pinosylvin, Kaempferol, Genistein, Syringetin, Erythraline, Ombuin Tabernemontanine and Kobusone, and which of those components also target at estrogen relative genes.\u003c/p\u003e \u003cp\u003eIt was suggested that the EC extract process the ability of osteogenesis improvement by influencing the HIF-1 signaling pathway with gene AkT1, MAPK3 and EGFR. In addition, estrogen signaling pathway and VEGF signaling pathway also plays a role in osteogenesis of EC.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eOsteogenesis effect of EC was verified via in vitro and in vivo experiments and the molecular mechanism was investigated by network pharmacology and RNA-sequencing analysis. Our results showed that HIF-1 signaling pathway was vital pathway in EC against osteoporosis, with the participation of gene AkT1, MAPK3 and EGFR. Estrogen and VEGF signaling pathway were synergetic pathway of anti-osteoporosis.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eTCM, traditional Chinese medicine; EC, Eucommiae Cortex;Akt1, AKT serine/threonine kinase 1; MAPK3, mitogen-activated protein kinase 3; EGFR, epidermal growth factor receptor; CASP3, caspase 3; SRC, SRC proto-oncogene, non-receptor tyrosine kinase; MAPK1, mitogen-activated protein kinase 1; STAT3, signal transducer and activator of transcription 3; PTGS2, prostaglandin-endoperoxide synthase 2; ESR1, estrogen receptor 1; CXCL8, C-X-C motif chemokine ligand 8; VEGF, vascular endothelial growth factor; OP, osteoporosis; RRP, Rehmanniae Radix Praeparata; HMM, Hedysarum Multijugum Maxim; EC, Eucommiae Cortex.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eEthical approval\u003c/h2\u003e\n\u003cp\u003eApproval was obtained from the Ethics Committee of Guangzhou Center for Disease Control and Prevention.\u003c/p\u003e\n\u003ch2\u003eConsent to Participate\u003c/h2\u003e\n\u003cp\u003eAll the authors discussed and agreed on the final manuscript.\u003c/p\u003e\n\u003ch2\u003eCompeting interests\u003c/h2\u003e\n\u003cp\u003eAll the authors have no competing interests to declare that are relevant to the content of this article.\u003c/p\u003e\n\u003ch2\u003eAuthor contributions\u003c/h2\u003e\n\u003cp\u003e\u003cstrong\u003eMin Zhao\u003c/strong\u003e, \u003cstrong\u003eXingfen Yang\u003c/strong\u003e and \u003cstrong\u003eChengliang Xie\u003c/strong\u003e conceived the present study, supervised the study design, supported data interpretation and revised the manuscript; \u003cstrong\u003eYun Liu\u003c/strong\u003e and \u003cstrong\u003eJianbin Tan\u003c/strong\u003e designed the experiments and wrote the manuscript; \u003cstrong\u003eZhi Lu\u003c/strong\u003e provided experimental samples;\u003cstrong\u003e\u0026nbsp;Weiling Huang\u003c/strong\u003e and \u003cstrong\u003eHong Lin\u0026nbsp;\u003c/strong\u003eperformed the experiments; \u003cstrong\u003eMansi Luo\u003c/strong\u003e and \u003cstrong\u003eYing Jiang\u003c/strong\u003e analyzed the data; \u003cstrong\u003eHongxia Wang\u003c/strong\u003e and \u003cstrong\u003eKexin Wang\u003c/strong\u003e finished the literature research.\u003c/p\u003e\n\u003ch2\u003eFunding\u003c/h2\u003e\n\u003cp\u003eThe work was funded by National Key R\u0026amp;D Program of China [grant number 2018YFC1602105] Ministry of Science and Technology of China; The Key Areas Research Development Projects of Guangdong Province [grant numbers 2019B020210001, 2019B020210002]; Medical Scientific Research Foundation of Guangdong Province, China [grant number A2019431].\u003c/p\u003e\n\u003ch2\u003eData availability statement\u003c/h2\u003e\n\u003cp\u003eThe data that supports the findings in this study are available in the supplementary material of this article. The complete dataset is available from the researchers upon request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAspray TJ, Hill TR (2019) Osteoporosis and the Ageing Skeleton. Sub-cellular biochemistry 91: 453\u0026ndash;476. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/978-981-13-3681-2_16\u003c/span\u003e\u003cspan address=\"10.1007/978-981-13-3681-2_16\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang L, Yu W, Yin X, Cui L, Tang S, Jiang N, Cui L, Zhao N, Lin Q, Chen L, Lin H, Jin X, Dong Z, Ren Z, Hou Z, Zhang Y, Zhong J, Cai S, Liu Y, Meng R, Deng Y, Ding X, Ma J, Xie Z, Shen L, Wu W, Zhang M, Ying Q, Zeng Y, Dong J, Cummings SR, Li Z, Xia W (2021) Prevalence of Osteoporosis and Fracture in China: The China Osteoporosis Prevalence Study. 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Environmental toxicology 36 (11): 2123\u0026ndash;2137. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1002/tox.23327\u003c/span\u003e\u003cspan address=\"10.1002/tox.23327\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"journal-of-orthopaedic-surgery-and-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"josr","sideBox":"Learn more about [Journal of Orthopaedic Surgery and Research](http://josr-online.biomedcentral.com)","snPcode":"13018","submissionUrl":"https://submission.nature.com/new-submission/13018/3","title":"Journal of Orthopaedic Surgery and Research","twitterHandle":"@MSKmedBMC","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"TCM, Osteogenesis, Estrogen signaling pathway, Network pharmacology, Eucommia ulmoides Oliv.","lastPublishedDoi":"10.21203/rs.3.rs-1987008/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-1987008/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003ePurpose\u003c/h2\u003e \u003cp\u003eEucommiae Cortex (\u003cem\u003eEucommia ulmoides Oliv.\u003c/em\u003e, cortex) had possessed multiple curative effect since ancient time. Nevertheless, the mechanism of EC serves as anti-osteoporotic herb remains further investigated.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eCytotoxicity assay and osteogenesis assay were adopted to filtrate the TCMs and osteoporosis model rats of was utilized to verify the anti-osteoporosis ability of EC. Network pharmacology was used to investigate the potential mechanisms of the EC against osteoporosis. The database including TCMSP, BATMAN TCM and TCMID were utilized to obtain the active compounds of EC, and their potential targets were predicted by SwissTarget-Prediction. Osteoporosis related targets were found by OMIM, DisGeNET and Gene Cards databases. The target interaction network was analyzed by STRING, GO enrichment and KEGG pathway analysis were carried out by DAVID database.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eResults of in vitro and in vivo experiments illustrated that EC showed no cytotoxicity and exhibited anti osteoporosis effect. A total number of 19 active components and 124 osteoporosis related targets of the EC were selected. KEGG pathway enrichment from bioinformatics suggested that EC prevented osteoporosis through the HIF-1 signaling pathway and estrogen signaling pathway, while results of RNA- sequencing suggesting HIF-1 signaling pathway. Moreover, genes Akt1, MAPK3 and EGFR may serve as the critical targets regulated by EC.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eOur results showed that HIF-1 signaling pathway was vital pathway in EC against osteoporosis, with the participation of gene AkT1, MAPK3 and EGFR. Estrogen and VEGF signaling pathway were synergetic pathway of anti-osteoporosis\u003c/p\u003e","manuscriptTitle":"Elucidate the potential mechanism of Eucommiae Cortex against osteoporosis by network pharmacology and RNA-sequencing ","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2022-08-26 14:57:11","doi":"10.21203/rs.3.rs-1987008/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Major revision","date":"2022-08-23T07:10:23+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2022-08-23T07:09:47+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2022-08-23T02:47:09+00:00","index":"","fulltext":""},{"type":"submitted","content":"Journal of Orthopaedic Surgery and Research","date":"2022-08-22T15:43:22+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"journal-of-orthopaedic-surgery-and-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"josr","sideBox":"Learn more about [Journal of Orthopaedic Surgery and Research](http://josr-online.biomedcentral.com)","snPcode":"13018","submissionUrl":"https://submission.nature.com/new-submission/13018/3","title":"Journal of Orthopaedic Surgery and Research","twitterHandle":"@MSKmedBMC","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"83dbf6c9-b7d9-45ac-8534-a2877797ef6b","owner":[],"postedDate":"August 26th, 2022","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2022-11-03T09:44:36+00:00","versionOfRecord":[],"versionCreatedAt":"2022-08-26 14:57:11","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-1987008","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-1987008","identity":"rs-1987008","version":["v1"]},"buildId":"WrCJVZZCHTDjtuVLN7oU0","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}