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

doi:10.21203/rs.3.rs-1987008/v1

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Research Article

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

https://doi.org/10.21203/rs.3.rs-1987008/v1

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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.

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

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 ^oC, 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/)database, 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).

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. 1a, 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. 1b). 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. 1c). 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. 2a). 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. 2c). 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. 2b), 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. 2d). 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. 4a). 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. 4b). 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. 6b). 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. 6a).

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. 7c, f), and 6418 DEGs were identified between the NC group and Con group (Fig. 7d, 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. 7a). 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. 7b.

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.

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.

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.

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.

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.

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

Status:

Version 1

Abstract

Purpose

Methods

Results

Conclusion

Figures

Introduction

Materials And Methods

Materials

Cytotoxicity assay

Alkaline phosphatase (ALP) staining

Bone mineralization assay

Alkaline phosphatase (ALP) assay

Establishment of osteoporosis models

Measurement of biochemical indicators

Measurement of BMC and BMD

Data preparation

Identification of active ingredients in EC

Targets prediction and screening of active ingredients in EC

Related targets collection of osteoporosis

Network construction

Comparation and analyzation of EC-targets and osteoporosis-associated targets

Protein-protein interaction (PPI) network construction

Bioinformatics analyses

RNA-seq analysis

Statistical analysis

Results

Cell viability and osteogenesis ability evaluation of candidate TCM

The ability of Osteogenesis Promotion of candidate TCMs

EC attenuated the loss of bone mass in osteoporosis model rats

Network pharmacology analysis

Active ingredients of EC and Target prediction

Construction and analysis of compounds-Target Interaction network

PPI network of common targets between compounds

Transcriptome profiling and functional enrichment analysis of High-throughput sequencing

PPI network construction and enrichment analysis of DEGs

Discussion

Conclusion

Abbreviations

Declarations

Ethical approval

Consent to Participate

Competing interests

Author contributions

Funding

Data availability statement

References

Additional Declarations

Supplementary Files

Status:

Version 1