Introduction

Osteoporosis is a common bone metabolic disease, characterized by bone strength and bone mineral density (BMD) decrease, leading to chronic pain, disability and, in severe cases, life threatening [1, 2]. Previous studies have shown that osteoporosis is more common in postmenopausal women and increases the risk of fractures [3]. Osteogenic differentiation is a key factor in bone regeneration, it is significant to clarify the regulatory mechanism of osteogenic differentiation and calcification for improving the treatment of osteoporosis [4]. A better understanding of the molecular mechanisms that participate in osteogenesis may help to treat osteoporosis. BMD changes are a major risk factor for osteoporosis, and more than 60% of the variation in BMD is due to genetic factors [5]. Therefore, identifying new therapeutic targets and biomarkers associated with osteoporosis has clinical significance.

Osteogenesis is a complex dynamic gene-modified program of osteoblasts that leads to the production of a collagenous mineralized matrix, playing a crucial role in bone homeostasis [6]. Bone formation controlled by osteoblasts involves multiple genetic and epigenetic regulation mechanisms [7]. Cyclin A1 (CCNA1) protein is a member of cyclin family, and is a positive regulator of cell cycle [8]. In addition, CCNA1 is involved in the occurrence, development, invasion and metastasis of a variety of tumors [9, 10]. Earlier bioinformatics analysis results demonstrated that CCNA1 was aberrant expressed gene in osteoporosis. Therefore, we aims to seek for the function of CCNA1 and the underlying mechanisms in osteoporosis, thereby to open up new ideas for the treatment of osteoporosis and other bone metabolism-related diseases.

Materials and methods

Microarray analysis

A microarray profile GSE100609 related to osteoporosis was downloaded from the Gene Expression Omnibus (GEO) database. All differentially expressed genes (DEGs) of osteoporotic group (n = 3) and non-osteoporotic group (n = 3) were identified and then screened under the standard od P < 0.05 and |log2FC| ≥ 1.5. After that, pearson correlation analysis was performed between DEGs, and the Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis was applied to analyze the related-pathways of enriched genes.

Patients

Approved by the Ethics Committee of Bei**g Geriatric Hospital, 20 patients with osteoporosis diagnosed in Bei**g Geriatric Hospital and 20 non-osteoporosis controls who volunteered to participate in this study signed informed consent. Then, 5 mL Fasting blood was collected from all subjects, and the isolated serum samples were stored at minus 80 ℃ for subsequent experiments.

Osteoporosis model cell establishment

The mouse cranial osteoblast MC3T3-E1 cells were obtained from Shanghai Institute of Biochemistry and Cell Biology (Shanghai, China), and cultured in Dulbecco’s modified Eagle medium (Hyclone, Logan, USA) containing 10% fetal bovine serum (FBS, Gibco, Carlsbad, USA), 100 mg/mL streptomycin, and 100 U/mL penicillin (Solarbio, Bei**g, China).

For osteoporosis model cell establishment, MC3T3-E1 cells at a density of 104 cells per well were seeded into 6-well plates and cultured until the cells reached to over 60% confluence. Then 100 µM dexamethasone (DEX; Sigma-Aldrich; Merck, USA) [11], 10 mM beta-glycerophosphate (Sigma-Aldrich; Merck, USA) and 50 µg/mL ascorbic acid Sigma-Aldrich; Merck, USA) [12, 13] were added into the medium, and replenished every 3 days.

Alizarin red staining

Alizarin Red staining was applied to measure matrix mineralization deposition in MC3T3-E1 cells [14]. In brief, DEX-induced osteoporosis cells were fixed in 4% paraformaldehyde (aladdin, Shanghai, China) for 10 min, and then washed with distilled water and stained with 1% Alizarin Red in accordance with the manufacturer’s protocol (Leagene, Bei**g, China). Finally, the stained cells were rinsed with distilled water, matrix calcification was observed, and red deposition were observed under the microscope (Nikon, Tokyo, Japan).

Alkaline phosphatase (ALP) staining

For ALP staining, the MC3T3-E1 cells were fixed in 70% ethanol for 1 h, and then washed with distilled water 3 times. ALP staining was performed with an ALP staining kit (Sidansai, Shanghai, China) according to the manufacturer’s protocol. The stained cells were then photographed with a microscope (Zeiss, Oberkochen, Germany). Then the stain cells were monitored at 562 nm (BioTek, Winooski, USA) to quantify ALP staining intensity.

Cell transfection

Exponential DEX-induced osteoporosis cells were collected for transfection. Two kinds of si-CCNA1 plasmids (1# 5’-CAGCTACACCAAGATTTCTTGGAAA-3’, 2# 5’-CATACCATGTGAGAGCACTTCTGTA-3’) and negative control (si-NC, 5’-TTCTCCGAACGTGTACGTTT-3’) have been designed by GenePharma Company (Shanghai, China). Transfection was performed using Lipofectamine 3000 transfection kits (Invitrogen, Carlsbad, USA). Aftern transfection triumphantly, the expression of CCNA1 of DEX-induced osteoporosis cells was detected by quantitative real-time polymerase chain reaction (qRT-PCR).

qRT-PCR

qRT-PCR was applied to evaluate levels of CCNA1, alkaline phosphatase (ALP), osteocalcin (OCN), osteopontin (OPN), Osterix, and bone morphogenetic protein 2 (BMP2), par-6 family cell polarity regulator alpha (PARD6A) and interferon beta 1 (IFNB1). Firstly, total RNA of DEX-induced osteoporosis cells were extracted by Trizol RNA isolation reagent (Invitrogen, Carlsbad, USA). Agilent RNA 6000 Nano Kit and Agilent 2100 Bioanalyzer (Agilent, Santa Clara, CA) were applied to detect RNA integrity and concentration. Then, qRT-PCR was performed on an ABI 7500 quantitative polymerase chain reaction system (Life Technologies, Carlsbad, USA). The relative expressions of genes were calculated using the 2−ΔΔCt method. Primer sequences were as followed:

CCNA1: forward, 5′-TGAAGTAGACACCGGCACAC-3′;

reverse, 5′-CACTCCTTGTCGCCTCAAGT-3′,

ALP: forward, 5′-CCAACTCTTTTGTGCCAGAGA-3′;

reverse, 5′-GGCTACATTGGTGTTGAGCTTTT-3′,

OCN: forward, 5′-CTGACCTCACAGATCCCAAGC-3′;

reverse, 5′-TGGTCTGATAGCTCGTCACAAG-3′,

OPN: forward, 5′-AATACCCAGATGCTGTGGCC-3′;

reverse, 5′-ACGGCTGTCCCAATCAGAAG-3′,

Osterix: forward, 5′-GAAGCGACCACTTGAGCACAT-3′;

reverse, 5′-TGTCCAAACTCATCAATGTATCT-3′,

BMP2: forward, 5′-ACCCGCTGTCTTCTAGCGT-3′;

reverse, 5′-TTTCAGGCCGAACATGCTGAG-3′,

PARD6A: forward, 5′-GCGGGTTCCAGGAATCTTCA-3′;

reverse, 5′-CACTGTGAAGTCCCTGCCAT-3′,

IFNB1: forward, 5′-TGCTCTGGCACAACAGGTAG-3′;

reverse, 5′-TATGGTCCAGGCACAGTGAC-3′,

GAPDH: forward: 5′-CGAGCCACATCGCTCAGACA-3′;

reverse: 5′-GTGGTGAAGACGCCAGTGGA-3′).

Western blotting

DEX-induced osteoporosis cells were lysed to obtain total protein by RIPA reagent (Sigma, NJ, USA). After quantified by a BCA protein assay (Thermol Fisher, CA, USA), protein was isolated by 10% SDS-PAGE and transferred to polyvinylidene fluoride membranes (Millipore, MA, USA). After being blocked with 5% skim milk, the membranes were incubated with primary antibodies purchased from abcam (Cambridge, UK) for anti-ALP (1:500, ALP), anti-OCN (1:1000, ab309521), anti-OPN (1:1000, ab214050), anti-Sp7/Osterix (1:1000, ab227820), anti-BMP2 (1:1000, ab214821), anti-SMAD2 (1:2000, ab40855), anti-SMAD3 (1:2000, ab40854), anti-p-SMAD2 (1:1000, ab280888), and anti-p-SMAD3 (1:2000, ab52903), and GADPH (1:1000, ab8245) overnight at 4℃. Then membranes were washed with TBST and incubated with secondary antibody (1:5000, ab6721). Protein bands were visualized using a gel imaging system (Bio-Rad, Hercules, USA).

Ovariectomized (OVX)-induced osteoporosis mouse model establishment

The sh-CCNA1 plasmids (5’-GCACGAGAATTGAGAATTAGA-3’) and negative control (sh-NC, 5’-GCCCAATTGTGCAGTGTGAAA-3’) were designed by GenePharma Company (Shanghai, China). Animal use was approved by the Ethics Committee of Bei**g Geriatric Hospital. Twelve-week-old C57BL/6 female mice were obtained from Animal Center of Academy of Military Medical Sciences. The animal experiments were conducted under the Guide for the Care and Use of Laboratory Animals and were carried out following the institutional ethical principles for animal experiments. Under pathogen-free conditions, mice were housed (4–5/cage) at 25℃ on a 12-h light/dark cycle, with adaptive feeding for 2 weeks. As previously reported, OVX-induced osteoporosis mouse model was established [15]. After intraperitoneal injection of ketamine (100 mg/kg) and xylazine (10 mg/kg), mice were performed with bilateral ovariectomy by dorsal approach. Mice in the sham group were subjected to incision and ovary exposure, but not to excision of the ovary. After four weeks of operation, 100 µL sh-CCNA1 or sh-NC was injected subcutaneously once a week for another four weeks. All mice were euthanized by intraperitoneal injection of pentobarbital sodium 160 mg/kg, and the femurs were removed after the last injection.

Micro-computed tomography

A Scanco vivaCT 40 (Scanco Medical AG, Bassersdorf, Switzerland) was employed for micro-computed tomography (µCT) as previously reported27. Using 6-µm pixel size, we set an X-ray source at 60 kV and scanned the excised left distal metaphysis of the femurs. We focused on a ~ 0.5 mm proximal region in the most distal part of the growth plate.

The femurs of mice were fixed with 4% paraformaldehyde for 24 h and then scanned by a Scanco vivaCT 40 (Scanco Medical AG, Bassersdorf, Switzerland). An X-ray source at 60 kV was set, the femurs were then scanned. Several bone-related parameters were analyzed, including the bone volume/total volume (BV/TV, %), trabecular thickness (Tb.Th, µm), trabecular number (Tb.N, mm− 1), trabecular separation (Tb.Sp, µm), and BMD (g/cm3).

Histology of bone tissues

Following Micro-computed tomography analysis, femurs were decalcified in 14% EDTA (Sigma-Aldrich, Sydney, NSW, Australia) at 37℃ for a week, and then embedded into paraffin for sectioning. Hematoxylin and eosin (H&E) staining was performed. Section images were acquired under a microscope Olympus FV1000 (Tokyo, Japan).

Statistical analysis

Statistical analyses were performed using the SPSS version 17.0 (SPSS Inc., Chicago, USA). All data were expressed as mean ± SD. Comparison between two groups was determined by student’s t-test. One-way ANOVA was used for comparison among different groups. p values less than 0.05 were considered to be significantly different.

Results

CCNA1 expression is significantly upregulated in osteoporosis

Firstly, microarray analysis of GSE100609 related to osteoporosis was conducted to identify genes which are aberrant expressed. As shown in Figs. 1A and 20 DEGs were identified in patients with osteoporosis, among which CCNA1 was markedly overexpressed. Additionally, the mRNA expression of CCNA1 was upregulated in the serum of patients with osteoporosis compared with the normal group (Fig. 1B). Moreover, the CCNA1 expression in DEX-treated MC3T3-E1 cells was significantly higher than that in untreated group (Fig. 1 C).

Fig. 1
figure 1

Dramatic upregulation of CCNA1 in osteoporosis. (A) Heat map of DEGs identified in patients with osteoporosis. (B) Detection of CCNA1 expression in patients with osteoporosis compared with that in healthy volunteers using qRT-PCR. (C) Detection of CCNA1 expression in MC3T3-E1 cells before and after DEX treatment using qRT-PCR. ***p < 0.001

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DEX-treated MC3T3-E1 cells were successfully established as osteoporosis model cells

Then osteogenesis of MC3T3-E1 cells of each group was evaluated to verify the success establishment of osteoporosis model cells. After treated with DEX, number of Alizarin Red stained cells and ALP stained cells were significantly decreased in MC3T3-E1 cells (Fig. 2A and B). Meanwhile, the expression of osteogenic-related proteins such as ALP, OCN, OPN, Osterix, and BMP2 were dramatically downregulated in DEX-treated MC3T3-E1 cells (Fig. 2C and D). These results suggested that DEX treatment inhibited osteogenesis of MC3T3-E1 cells, indicating that DEX-induced osteoporosis model cells were successfully established.

Fig. 2
figure 2

Successful establishment of DEX-treated MC3T3-E1 cells as osteoporosis model cells. (A) Image and quantification of Alizarin Red stained DEX-treated MC3T3-E1 cells. (B) Image and quantification of ALP stained DEX-treated MC3T3-E1 cells. C-D. Measurement of the expression levels of ALP, OCN, OPN, osterix, and BMP2 using qRT-PCR and western blotting. **p < 0.01, ***p < 0.001

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Knockdown CCNA1 promoted osteogenesis of MC3T3-E1 cells

Afterwards, the role of CCNA1 in modulating osteogenesis of MC3T3-E1 cells was studied. As indicated in Fig. 3A, CCNA1 expression was more remarkably downregulated after transfected with si-CCNA1 1# plasmid. After CCNA1 was suppressed, number of Alizarin Red stained cells and ALP stained cells were significantly increased (Fig. 3B C). Meanwhile, the expression of osteogenic-related proteins such as ALP, OCN, OPN, Osterix, and BMP2 were dramatically upregulated in MC3T3-E1 cells (Fig. 3D and E).

Fig. 3
figure 3

CCNA1 knockdown promotes osteogenesis of MC3T3-E1 cells. (A) Detection of CCNA1 expression levels by qRT-PCR after transfection. (B) Image and quantification of Alizarin Red stained MC3T3-E1 cells with inhibited CCNA1. (C) Image and quantification of ALP stained MC3T3-E1 cells with inhibited CCNA1. D-E. Expression levels of ALP, OCN, OPN, Osterix, and BMP2 measured by qRT-PCR and western blotting. **p < 0.01, ***p < 0.001

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CCNA1 expression was negatively related with TGF-beta signaling pathway

Next, pearson correlation analysis and KEGG analysis demonstrated that genes negatively related to CCNA1 were enriched in 10 pathways, including the glypican, IGF1, PI3K, mTOR, S1P1, ATM, ATR, BMP receptor, p53, and TGF-beta receptor signaling pathways (Fig. 4A and B). Interestingly, the expression of PARD6A and p-SMAD2, two genes enriched in the TGF-beta receptor signaling pathway, were significantly decreased in DEX-induced osteoporosis cells compared with that in control cells (Fig. 4C-4 F).

Fig. 4
figure 4

CCNA1 expression is negatively related to the TGF-beta signaling pathway. (A) Pearson correlation analysis between CCNA1 and its negatively related genes. (B) KEGG analysis of genes inversely associated with CCNA1 gene. C-F. Image and quantification of expression levels of PARD6A and IFNB1 enriched in TGF-beta signaling pathway accessed by western blotting. *p < 0.05, ***p < 0.001

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Suppressed CCNA1 promoted osteogenesis by activating TGF-beta signaling pathway

Then, expression levels of SMAD2/3 and phosphorylated SMAD2/3 were notably increased induced by silenced CCNA1 in DEX-induced osteoporosis cells (Fig. 5A). Furthermore, LY2109761, an inhibitor of the TGF-beta signaling pathway, suppressed the intensity of Alizarin Red and ALP intensity (Fig. 5B C). Meanwhile, the expression levels of ALP, OCN, OPN, osterix, and BMP2 increased by si-CCNA1 were also downregulated by LY2109761 (Fig. 5D and E).

Fig. 5
figure 5

Suppressed CCNA1 promoted osteogenesis by activating TGF-beta signaling pathway. (A) Protein expression of SMAD2/3 as well as phosphorylated SMAD2/3 measured by western blotting. (B) Image and quantification of Alizarin Red stained MC3T3-E1 cells after LY2109761 treatment. (C) Image and quantification of ALP stained cells MC3T3-E1 cells after LY2109761 treatment. D-E. Expression levels of ALP, OCN, OPN, Osterix, and BMP2 measured by qRT-PCR and western blotting after LY2109761 treatment. **p < 0.01, ***p < 0.001, compared with si-nc group. #p < 0.05, ##p < 0.01, ###p < 0.001, compared with si-CCNA1 group

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Suppressed CCNA1 relieved bone mass in vivo

Afterwards, CCNA1 was successfully downregulated in bone tissues of OVX mice injected with LV-sh-CCNA1 (Fig. 6A). The right tibials of mice were analyzed to perform the micro-computed tomography., and the results demonstrated that inhibition of CCNA1 prevented the extensive bone loss induced by the OVX procedure in mice femurs (Fig. 6B). Consistently, histological examination showed that the bone volume and bone surface were both well maintained in the CCNA1 inhibition group compared with the OVX mice (Fig. 6C). The quantitative analysis revealed that differences in BV/TV, Tb.Th, Tb.N, and Tb.Sp in trabecular bone were all significant between sham and OVX groups (Fig. 6D and G). Moreover, BMD was also dramatically suppressed by OVX surgery (Fig. 6H). These data revealed that OVX surgery prominentlyattenuated bone microstructure and bone mass; however, knockdown of CCNA1 dramatically reversed the effects of OVX treatment.

Fig. 6
figure 6

Suppressed CCNA1 relieves bone mass in vivo. (A) Detection of CCNA1 expression levels by qRT-PCR in bone tissues of all mice. (B) Representative µCT images were photoed to showthe bone loss. (C) Representative images of HE staining of decalcified bone sections. D-H. Quantification of micro-computed tomography data: BV/TV, Tb. Th, Tb. N, Tb.Sp. and BMD. **p < 0.01, ***p < 0.001, compared with Sham group. ##p < 0.01, compared with OVX + LV-sh-NC group

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Discussion

Osteoporosis is the result of the disruption of the dynamic balance between bone formation and bone resorption [16, 17]. During this process, osteoblasts play a key role in bone formation and are responsible for osteogenesis and bone regeneration [18]. In addition, inhibition of osteogenic differentiation can cause bone defects after trauma and seriously affect the quality of life [19]. Therefore, studying of the mechanism of osteogenic differentiation is of great significance for the treatment of diseases, such as heterotopic mineralization and osteoporosis.

Studies have shown that osteogenic differentiation can be evaluated using various bone metabolism markers [20, 21]. For instance, the intensity of ALP and ARS is generally used to detect early and late mineralization states, which indicate bone formation by osteoblasts [22]. Additionally, OPN (regulates biomineralization in bone tissue and aids in growth reduction and accumulation of calcium crystals in epithelial tissue), osterix (bone formation-related genes), and BMP2 (stimulates bone mineralization and osteoblast differentiation) have been reported to be related to bone metabolism regulators [23,24,25]. Moreover, elevated expression of bone turnover markers including ALP and OCN has also been reported to be related to the remission of osteoporosis [26]. In this study, we evaluated osteogenesis by detecting mineralization levels, ALP, OCN, OPN, osterix, and BMP2 expression in osteoblasts.

Genetic association research is an effective method to explore the molecular genetic mechanisms of many complex diseases including osteoporosis in recent years [27, 28]. Recent genome-wide association studies meta-analyses and large sample association studies have shown that many genes are associated with osteoporosis and fracture risk [29,30,31]. An increasing number of abnormally expressed genes have been identified as the key regulators of osteoblast differentiation [32, 33]. The abnormal expression of genes involved in the differentiation of stem cells into osteoblasts and the potential role of stem cells in osteogenesis have been reported [34, 35]; however, their relative functional significance is not fully understood. SOST gene is a candidate gene for osteoporosis [36]. Inhibition of SOST and its products induces osteoblastic activation and promotes bone formation [37]. Likewise, the knockdown of genes involved in bone metabolism, such as RANKL, RANK, and DKK-1, provides promising therapies based on genetic engineering [38,39,40]. Hence, there is an urgent need to improve the gene network related to bone metabolism for osteoporosis treatment. Our data suggested that CCNA1 screened from the bioinformatics analysis was dramatically overexpressed in the serum of patients with osteoporosis, indicating that CCNA1 may be a potential gene related to bone metabolism. Therefore, the mechanisms of action of CCNA1 were investigated in this study.

Dexamethasone (DEX) is an artificial compound of long-acting glucocorticoid. Glucocorticoid induced osteoporosis (GIOP) is a kind of thin-bone hormone caused by DEX, and its incidence is secondary to primary osteoporosis [41]. Long-term high-dose injection of DEX leads to osteoblast apoptosis [42]. In this study, compared with untreated MC3T3-E1 cells, DEX-treated MC3T3-E1 cells inhibited osteogenesis, suggesting the successful establishment of DEX-induced osteoporosis cells. CCNA1 was upregulated in DEX-induced osteoporosis cells.

Moreover, the knockdown of CCNA1 significantly promoted osteogenesis in DEX-induced osteoporosis cells. Next, KEGG analysis suggested that CCNA1 may suppress osteoblast differentiation via several signaling pathway including TGF-beta signaling pathway which plays an important role in maintaining bone homeostasis [43, 44]. Interestingly, BMP2, one of the evaluation marker of osteoblast differentiation, was reported to be a cytokine of TGF-beta family [23]. Subsequently, expression of two genes enriched in TGF-beta family was downregulated in DEX-induced osteoporosis cells. These results indicated that CCNA1 may suppress TGF-beta signaling pathway in osteoporosis. Furthermore, the TGF-beta signaling pathway inhibitor LY2109761 significantly suppressed osteogenesis promoted by silenced CCNA1 in DEX-induced osteoporosis cells, suggesting that CCNA1 suppressed osteoblast differentiation by inactivating TGF-beta signaling pathway in osteoporosis.

The following limitations of this paper need to be further explored in the future. TGF-bata signaling pathway has been found to participate in CCNA1 modulating osteoblast differentiation process in vitro, the role of TGF-beta pathway should also be studied in vivo experiments in the future. Moreover, whether CCNA1 regulate the process of osteoporosis in a DEX-induced mouse model should also be studied.

Conclusion

Taken together, CCNA1 inhibited osteoblast differentiation of osteoblasts via suppressing TGF-beta signaling pathway. Knockdown of CCNA1 may be an potential therapy for osteoporosis.