Extracts of Drynariae Rhizoma Promote Bone Formation in OVX Rats through Modulating the Gut Microbiota

Abstract

Drynariae Rhizoma has been commonly used as a preventive and therapeutic agent for bone diseases. However, its pharmacological mechanisms have not been fully elucidated. Here, we aimed to investigate the effects of Drynariae Rhizoma in a bilateral ovariectomized rat model and explore the correlation with gut microbiome. We established an ovariectomized rat model, which we treated with different doses of Drynariae Rhizoma (Drynariae Rhizoma-Low, 0.27 g/kg/day; Drynariae Rhizoma-Middle, 0.81 g/kg/day; Drynariae Rhizoma-High, 2.43 g/kg/day) through intragastric administration for 12 weeks. Results showed that Drynariae Rhizoma alleviated body weight, moderated bone microstructure, and promoted the expression of bone formation-related factors in ovariectomized rats, in which Drynariae Rhizoma-High showed the most significant effects among the three doses. Furthermore, the effects of Drynariae Rhizoma on promoting bone formation were correlated to the changes in microbial richness and the restorations of several genera, among which Ruminiclostridium and Ruminococcaceae_UCG_007 were positively correlated with the bone formation-related factors, and both were enriched in the Drynariae Rhizoma-High group as biomarkers. Moreover, CMP-legionaminate biosynthesis I might be a crucial pathway of Drynariae Rhizoma to regulate gut microbiota. The content of serum short-chain fatty acids in the ovariectomized rats were regulated by Drynariae Rhizoma. Our results demonstrate that Drynariae Rhizoma promotes bone formation in ovariectomized rats, and is related to the regulation of the gut microbiota structure.

Keywords

osteoporosis - Drynaria fortune - Polypodiaceae - extracts of Drynariae Rhizoma - ovariectomized rats - bone formation - gut microbiota

Introduction

Osteoporosis (OP) is a widespread systemic bone disease that is characterized by a reduction in bone mass, damage to the microarchitecture of bone tissue, increased fragility of bones, and frequent fractures. It is estimated that the global prevalence of OP and osteopenia is 19.7 and 40.4%, respectively [1], with one in two postmenopausal women likely to experience an osteoporotic fracture during their lifetime [2]. Abnormal bone metabolism is the underlying cause of OP, which closely correlates with insufficient bone formation. At present, antiresorptive agents are the most commonly used treatment, while bone formation-related drugs are limited. Traditional Chinese medicine (TCM), which has been used for thousands of years, has unique advantages in the treatment of OP according to growing evidence. TCM is reported to have dual efficacy in promoting bone formation and inhibiting bone resorption, with higher safety and lower toxicity [3], [4]. Thus, it is worthwhile to promote TCM as an alternative medicine for OP and to investigate the mechanisms underlying its promotion of bone formation.

Drynariae Rhizoma (DR) is obtained from the dried rhizome of Drynaria fortune (family Polypodiaceae). It is primarily composed of flavonoids and polyphenols, such as kaempferol, lignan, and naringenin [5], [6]. In TCM clinics, DR is commonly used in Chinese medicine prescriptions in the form of water extracts for the prevention and treatment of OP, as well as in dietary supplements like YIN-YANG-HUO-GU-SUI-BU capsules (National Healthy Food Index No.: G20140729, China) and so on. Studies have reported that the water extracts of DR could moderate the bone microstructure in an osteoporotic rat model, which was related to the regulation of metabolites or the AGE-RAGE signaling pathway [7], [8]. Additionally, DR extracts could promote the proliferation and osteogenic differentiation of osteoblasts [9], [10]. However, there are limited reports of DR on bone formation in ovariectomized (OVX) rat models, and its related mechanism requires further investigation.

The gut microbiota is a collective term used to describe the normal microorganisms present in the human intestine, including probiotic, neutrophilic, and pathogenic bacteria. The stability of the species structure is essential for maintaining normal physiological activities. Once disrupted, such as increasing harmful bacterial proportions, it may lead to various diseases, including OP [11], [12]. Studies have demonstrated that there are significant changes in the diversity and abundance of gut microbiota in patients with OP, and these changes are believed to affect bone metabolic balance via regulation of the immune system, endocrine system, and calcium plasma absorption [13]. Thus, the gut microbiota represents a crucial factor in the regulation of bone metabolic homeostasis.

In this study, we observed the bone microstructure changes in OVX rats after treatment with water extracts of DR, as well as some bone formation-related factors. Next, we explored the changes in the species and the abundance of gut microbiota by 16S rDNA high-throughput sequencing, expecting to provide a new perspective of DR in the treatment of OP.

Results

The chemical components of DR were analyzed by HPLC and the content of naringin was evaluated, which was found to be 3.99 mg/g ([Fig. 1 a, b]).

Fig. 1 The effects of DR on body weight and uterus status in OVX rats. a HPLC chromatogram of naringin. b HPLC chromatogram of water extracts of DR. c Change in body weight of rats (n = 6). The raw data represent replicate values. d Uterus morphology. e Uterus weight and index (n = 4). The raw data represent replicate values. ^Analyses were carried out twice and comparable results were obtained; *p < 0.05, **p < 0.01, ns: not significant.

Subsequently, the effects of DR in OVX rats were evaluated. The body weight of the OVX group increased significantly over time compared with the Sham group, while DR treatment could significantly alleviate this change ([Fig. 1 c]). Furthermore, the uterus weight and index were lower in the OVX group than in the Sham group, while DR treatment had no influence on the OVX rats ([Fig. 1 d, e]).

To further evaluate the effect of DR on the bone microstructure in OVX rats, micro- computed tomography (micro-CT) and hematoxylin and eosin (H&E) staining were performed. Results showed that the femur trabeculae of the OVX rats appeared irregular, porous, and fractured, with significantly lower bone mineral density (BMD), bone volume fraction (BV/TV), and trabecular number (Tb.N), and a higher trabecular separation (Tb.Sp) compared to the Sham group. DR treatment significantly increased the BMD (p < 0.05) in the OVX rats. Drynariae Rhizoma-High (DR-H) significantly increased the BV/TV, and significantly decreased the Tb.Sp compared to the OVX rats (p < 0.05). Besides, different doses of DR slightly increased Tb.N and Tb.Th in the OVX rats, but not significantly ([Fig. 2 a]). Moreover, H&E staining revealed that the OVX rats exhibited a higher degree of trabecular rarefaction and irregularity compared to the Sham rats. DR treatment ameliorated these changes, with DR-H presenting the most significant effect ([Fig. 2 b, c]).

Fig. 2 DR ameliorated the bone microstructure in OVX rats. a Micro-CT of the femur (n = 3). The raw data represents replicate values. b H&E staining of the femur; scale bar: 50 µm or 200 µm. C H&E staining of the lumbar vertebrae; scale bar: 50 µm or 200 µm. Analyses were carried out twice and comparable results were obtained; *p < 0.05, **p < 0.01, ns: not significant.

Subsequently, we also investigated the alternation of bone metabolism factors in rats. The results revealed that the content of estradiol (E2), osteocalcin (OCN), alkaline phosphatase (ALP), and calcium (Ca) ion in serum was significantly lower in the OVX group than the Sham group, and DR treatment could effectively reverse these trends (p < 0.05) ([Fig. 3 a, b]). However, the DR treatment did not have a significant effect on tartrate-resistant acid phosphatase (TRAP) in OVX rats ([Fig. 3 a]), as well as the content of phosphorus (P) ion ([Fig. 3 b]).

Fig. 3 The expression of bone formation-related factors in different groups. a Content of E2, OCN, ALP, and TRAP in serum (n = 4). b Content of Ca and P ion in serum (n = 4). c Cropped blots showed the protein expression of bone formation-related factors in different groups (n = 3). Full-length blots are available as Supporting Information. d mRNA expression of bone formation-related factors in different groups (n = 3). e, f IHC results of COL1A1and RUNX2 in the femur (n = 3); scale bar: 50 µm or 100 µm. Analyses were carried out twice and comparable results were obtained; *p < 0.05, **p < 0.01, ns: not significant.

To further explore the effect of DR on bone formation, changes in bone formation-related factors were detected. The protein expression of ALP, COL1A1, and RUNX2 was significantly lower in the OVX group than the Sham group, while the DR treatment group showed a significant increase in the expression of ALP, BMP-2, COL1A1, and RUNX2 in the OVX rats (p < 0.05) ([Fig. 3 c]). Additionally, we also evaluated mRNA expression. It demonstrated that Drynariae Rhizoma-Middle (DR-M) and DR-H significantly improved the mRNA expression of all these bone formation-related factors in OVX rats, while Drynariae Rhizoma-Low (DR-L) significantly increased the mRNA expression of bmp-2, col1a1, and runx2 in OVX rats (p < 0.05) ([Fig. 3 d]). Immunohistochemistry (IHC) staining revealed that COL1A1 and RUNX2 were sparsely distributed in OVX rats, while different doses of DR could effectively modulate them in the OVX rats ([Fig. 3 e, f]). These findings suggested that DR-H may provide more benefits in terms of bone formation.

We investigated the gut microbiota composition using 16S rDNA sequencing. After removing unqualified sequences, an average of 67 082 effective tags were obtained, and each sample obtained an average of 30 285 feature numbers for an average of 443 feature sequences. The Venn diagram of feature sequences from each group is shown in [Fig. 4 a].

Fig. 4 Venn diagram of feature sequences (a) and beta diversity analysis (b) of gut microbiota.

Alpha diversity analysis was conducted to describe the composition of the bacteria in different samples, including the low abundance feature coverage (Goods coverage), species richness (Chao and Observed species) as well as species diversity (Simpson and Shannon indices). As indicated in [Table 1], the Goods coverage value of gut microbiota was greater than or equal to 0.97 in each group, indicating that the abundance of features obtained by sequencing was credible, and the sequencing depth satisfied the subsequent bioinformatics analysis. Chao, Observed species, and Simpson analysis showed no significant difference among each group. Interestingly, the Shannon index was significantly improved in OVX rats compared to Sham rats, while DR-L and DR-H could significantly reverse it in OVX rats.

Table 1 Summary of the alpha diversity statistical analysis in different groups.

Group	Goods coverage index	Chao 1 index	Observed species index	Simpson index	Shannon index
*P < 0.05 vs. Sham, #p < 0.05 vs. OVX, ##p < 0.01 vs. OVX
Sham	1.00 ± 0	396.71 ± 185.3	388.67 ± 172.33	0.98 ± 0.01	7.01 ± 0.32
OVX	1.00 ± 0	537.12 ± 30.91	527.67 ± 25.33	0.99 ± 0	7.6 ± 0.08*
DR-L	1.00 ± 0	389.67 ± 110.00	384.67 ± 70.33	0.98 ± 0.01	7.15 ± 0.31#
DR-M	1.00 ± 0	498.10 ± 58.56	488.67 ± 52.33	0.99 ± 0	7.45 ± 0.20
DR-H	1.00 ± 0	397.86 ± 95.86	393.00 ± 91.00	0.98 ± 0.01	6.89 ± 0.17##

Furthermore, the beta diversity of UniFrac-based Principal Co-ordinates Analysis (PCoA) was used to evaluate a distinct clustering pattern of gut microbiota structure among each group, as depicted in [Fig. 4 b]. The results show a clear separation between the Sham and the other groups in the gut microbiota structure, while a clear separation was also observed between the OVX and DR-H groups.

At the phylum level, there were 16 phyla detected in all groups, among which Firmicutes, Bacteroidetes, and Proteobacteria were the dominant phyla. Compared with the Sham group, the abundance of Firmicutes was increased, while Bacteroidetes and Proteobacteria were decreased in the OVX group, resulting in an obvious increase in the ratio of Firmicutes/Bacteroidetes. Conversely, different doses of DR treatment decreased the abundance of Firmicutes and increased the abundance of Bacteroidetes, resulting in a decrease of the ratio of Firmicutes/Bacteroidetes in OVX rats. Furthermore, the DR-M and DR-H treatment increased the abundance of Proteobacteria in the OVX group ([Fig. 5 a]).

Fig. 5 Composition and abundance of gut microbiota in different groups of rats. a Composition of gut microbiota at the phylum levels. b Composition of gut microbiota at the genus levels. c Abundance of gut microbiota at the genus levels. d Spearmanʼs correlation of the abundant genus with bone metabolism factors. The data are expressed as means ± SD (n = 3 in each group); *p < 0.05, **p < 0.01.

At the genus level, there were 257 genera detected in all groups, among which Muribaculaceae_unclassified, Lactobacillus, Firmicutes_unclassified, Lachnospiraceae_NK4A136_group, and Ruminococcaceae_UCG-014 were the dominant genera. Compared with the Sham group, the abundance of Muribaculaceae_unclassified, Lactobacillus, and Lachnospiraceae_NK4A136_group was decreased, while the abundance of Firmicutes_unclassified and Ruminococcaceae_UCG-014 was increased in the OVX group. Conversely, different doses of DR treatment increased the abundance of Muribaculaceae_unclassified and Lactobacillus, and decreased the abundance of Lachnospiraceae_NK4A136_group in the OVX rats. Additionally, DR-H could decrease the abundance of Ruminococcaceae_UCG-014, and DR-L and DR-M decreased the abundance of Firmicutes_unclassified in OVX rats ([Fig. 5 b]).

The Kruskal-Wallis test was executed to detect genera among different groups. Results showed that the abundance of Ruminococcaceae_UCG-007 and Ruminiclostridium were significantly decreased in the OVX group, while the Prevotellaceae_Ga6A1_group was significantly increased compared with the Sham group. Meanwhile, different doses of DR treatment decreased the abundance of Peptococcaceae_unclassified in OVX rats. Furthermore, the abundance of Prevotellaceae_NK3B31_group, Ruminococcaceae_UCG-007, and Ruminiclostridium were increased in the DR-H group, as well as Ruminococcaceae_UCG-007 in the DR-M group, and Prevotellaceae_NK3B31_group, Prevotellaceae_Ga6A1_group, and Bacteroides in the DR-L group ([Fig. 5 c]). The flora distribution and different abundance (Kruskal-Wallis test, p < 0.05) of gut microbiota of rats at the class, order, family and species levels are shown in Fig. 1S, Supporting Information.

Spearmanʼs correlation analysis was carried out to investigate the association between the different genera and bone metabolism factors in serum. The results showed that Peptococcaceae_unclassified was negatively correlated with OCN, ALP, and Ca ion. Ruminococcaceae_UCG-007 was positively correlated with OCN but negatively correlated with P ion. Ruminiclostridium and Prevotellaceae_NK3B31_group were positively correlated with ALP and Ca ion ([Fig. 5 d]). Therefore, we speculated that Ruminococcaceae_UCG-007, Ruminiclostridium, and Prevotellaceae_NK3B31_group may be the potential targets of DR to promote bone formation.

Combining the previous results, DR-H presented the most significant effects on bone formation. To get further insight into the underlying mechanisms of DR-H, linear discriminant analysis effect size (LEfSe) and phylogenetic investigation of communities by reconstruction of unobserved states (PICRUSt2) analyses were conducted among the Sham, OVX, and DR-H groups. LEfSe analysis was utilized to explore the potential biomarker that was significantly enriched in the bacterial community, while PICRUSt2 was used to analyze the KEGG pathways and assess the function of variational gut microbiota.

The results of the LEfSe analysis indicated that the genus and species levels exhibited significant differences among different groups (linear discriminant analysis score > 2.5). Specifically, at the genus level, Quinella was enriched in the Sham group, while Ruminiclostridium, Coriobacteriales_unclassified, and Ruminococcaceae_UCG_007 were enriched in the DR-H group. At the species level, Quinella_unclassified was enriched in the Sham group, Negativibacillus_unclassified was enriched in the OVX group, while Ruminiclostridium_unclassified, Coriobacteriales_unclassified, and Ruminococcaceae_UCG_007_unclassified were enriched in the DR-H group ([Fig. 6 a]).

Fig. 6 Advanced analysis of LEfSe (a) and function prediction (b) of gut microbiota.

The PICRUSt2 analysis revealed that 16 metabolic pathways were disordered in the OVX group compared with the Sham group. Notably, the relative abundance of CMP-legionaminate biosynthesis I was significantly increased in the OVX group, while this trend could be reversed by DR-H treatment. Therefore, we inferred that CMP-legionaminate biosynthesis I might be a crucial pathway of DR to regulate gut microbiota ([Fig. 6 b]).

We also investigated the serum short-chain fatty acid (SCFA) levels in OVX rats treated with DR ([Fig. 7]). The results indicated a significant reduction in serum SCFA concentrations in the OVX rats (p < 0.05), which was notably ameliorated by DR intervention (p < 0.01). Notably, both acetic acid and butyric acid levels were significantly diminished (p < 0.05) in the serum of the OVX rats. However, treatment with both DR-H and DR-M significantly enhanced the serum acetic acid levels (p < 0.05). Furthermore, DR-H was also effective in elevating the serum butyric acid levels in OVX rats (p < 0.01).

Fig. 7 Concentrations of SCFA in the serum of rats.

Discussion

OP is a significant public health concern affecting the elderly population, and its prevention and treatment remain worldwide challenges. Current drugs used for OP have remarkable efficacy [14], but some limitations exist, including poor tolerability and significant adverse effects [15], [16]. Consequently, there is a need to develop new drugs with fewer adverse effects. DR has been used as a kidney-nourishing herb to treat bone diseases and as a primary component of many healthcare products. DR and its active ingredients have been shown to exhibit skeletal protective effects in glucocorticoid and OVX-induced models [7], [17], [18]. However, the specific mechanism underlying its promotion of bone formation remains poorly understood.

Our results indicate that DR treatment significantly decreased body weight and increased estradiol levels in serum in OVX rats, showing the estrogen-like effect in OVX rats. The estrogenic effects of phytoestrogen-containing drugs or selective estrogen receptor modulators are always a concern due to their potential to stimulate the growth of reproductive tissues, such as the breast and uterus [19], [20]. Our results proved that DR did not exhibit any stimulatory effects on the uterus of OVX rats, which corresponds to a previous study that DR only exerted estrogenic effects in a tissue-selective manner, such as bone [21]. Next, micro-CT and H&E staining results indicated that DR significantly moderates bone mass and the bone microstructure. Furthermore, the content of OCN, ALP, and Ca ion was significantly upregulated in the DR treatment group, while TRAP showed no significant difference. In addition, the DR treatment group showed an increase in the expression of bone formation-related factors, as shown by IHC staining, Western blot, and RT-PCR. Our results suggest that extracts of DR significantly stimulated bone formation in a dose-dependent manner, with the highest efficacy observed at the DR-H dosage. These findings indicate that DR has obvious effects on bone formation in OVX rats.

Gut microbiota is the primary member of intestinal microecology, which interacts with organs and systems of the body, mainly through SCFA and inorganic salts [12]. Studies have shown that the structural changes of gut microbiota are closely related to the development of OP [22], [23]. In both OP patients and animal models, an increase of the ratio of Firmicutes/Bacteroidetes was found. Conversely, several probiotics have been shown to have a protective effect, indicating that the gut microbiota is an important target for the treatment of OP [24], [25]. Until now, increasing evidence suggested that the anti-OP effect of TCM was closely related to the gut microbiota. For instance, Eucommia ulmoides leaf extract could alter the composition of gut microbiota and increase the ratio of Firmicutes/Bacteroidetes to ameliorate OP [26]. Xian-Ling-Gu-Bao capsules regulate gut microbiota to further control lipid and bile acid metabolism, stimulating the increase of bone mass in OVX rats [27].

Our results revealed that the water extracts of DR led to a significant improvement in the ratio of Firmicutes/Bacteroidetes and the abundance of Muribaculaceae_unclassified and Lactobacillus in OVX rats. Prior research has demonstrated that Muribaculaceae_unclassified is associated with the regulation of lipid metabolism and inflammation, with its abundance being reduced in animal models related to adiposity [28], ulcerative colitis [29], and diabetic kidney disease [30]. Interestingly, Muribaculaceae_unclassified was positively correlated with the increase of butyrate production, while butyrate could stimulate bone formation via T regulatory cell-mediated regulation of WNT10B expression [31]. Our previous study revealed that ovariectomy could lead to abnormal fat metabolism and weight gain [32], whereas DR showed a significant reduction in body weight, promoted bone formation, and increased the abundance of Muribaculaceae_unclassified in this study. Therefore, we speculated that Muribaculaceae_unclassified might be one of the mechanisms of DR regulating bone formation. Of course, further exploration is required to validate this hypothesis. As for the Lactobacillus, several strains, including Lactobacillus brevis AR281 [33], Lactobacillus rhamnosus GG [34], and Lactobacillus casei [35], have been demonstrated to promote osteogenesis or attenuate osteoclastogenesis in OVX rats. Moreover, Ruminococcaceae_UCG-007 was decreased in the DR-H and DR-M groups when contrasted to the OVX rats, which was similar with the Chinese medicine preparation You-gui pills in the treatment of OP rats [36]. In addition, Peptococcaceae_unclassified was significantly decreased in the DR groups. It was reported that an abundance of the family Peptococcaceae was decreased in high-fat and cholesterol diet-induced hypercholesterolemia mice [37]. It is worth noting that the abundance changes of differential genera such as Ruminococcaceae_UCG-007 and Ruminiclostridium did not show a typical dose-effect relationship with drug doses of DR, and there are several reasons for this. For one thing, different dosages of a drug may affect gut microbiota differently. A low dose may only affect specific bacteria, while a high dose may have a broader effect on the flora [38]. In addition, the gut microbiota is composed of thousands of different bacteria, and the complex interactions among them may tend to maintain the structural and functional stability of the intestinal microenvironment, resisting the changes in flora abundance brought about by different doses of drugs [39].

We also performed Spearmanʼs correlation analysis between the different gut microbiota community at the genus level and bone metabolism factors in serum. We concluded that Ruminococcaceae_UCG-007, Ruminiclostridium and Prevotellaceae_NK3B31_group were positively correlated with the bone formation-related factors, while Peptococcaceae_unclassified was negatively correlated. Our results are accordance with a recent study that Ruminiclostridium had a positive correlation with Ca ion in OVX rats [40]. Furthermore, LEfSe analysis also demonstrated that Ruminiclostridium and Ruminococcaceae_UCG_007 were enriched in the DR-H group. There results suggest that the anti-OP effect of DR may correlate with the improvement of Lactobacillus in gut microbiota, and Ruminococcaceae_UCG-007, Peptococcaceae_unclassified, and Ruminiclostridium may be the other potential targets.

In addition, PICRUSt2 analysis showed that CMP-legionaminate biosynthesis I might be an important pathway where DR regulated bone formation through affecting gut microbiota in OVX rats. Research indicates that this pathway is involved in the biosynthesis of sialic acids, which have been found to play a critical role in the virulence of pathogenic organisms by enabling them to evade host immune responses and invade cells [41]. In particular, the metabolite sialic acid-like 5,7-diacetamido-3,5,7,9-tetradeoxy-nonulosonate, which is a product of CMP-legionaminate biosynthesis I, could be incorporated into the glycoconjugates of virulence-associated cell surface, such as lipopolysaccharides (LPS), capsular polysaccharides, pili, and flagella [42]. LPS, in turn, has been implicated in bone destruction caused by inflammation [43], [44], above all suggesting a potential link between the CMP-legionaminate biosynthesis I pathway and bone metabolic balance.

Previous research has established that SCFA may enhance calcium absorption through several mechanisms, such as the regulation of pH values and the expression of Calbindin D9k, TRPV6, and VDR [45]. Our results showed that DR increased acetic acid and butyric acid, and the resulting increase in SCFA may be an important mechanism for promoting bone formation.

All in all, the purpose of this study was to examine the bone formation effect of DR and its relationship with the gut microbiota in OVX rats. Specifically, we found that DR alleviated body weight, moderated the bone microstructure, and promoted the expression of bone formation-related factors in the femur, in which DR-H showed the most significant effects among the three doses. The effect of DR was correlated with the changes in microbial abundance and the restoration of several genera, among which Ruminiclostridium and Ruminococcaceae_UCG_007 were positively correlated with the bone formation-related factors, and both enriched the DR-H group as biomarkers. Furthermore, the CMP-legionaminate biosynthesis I pathway and SCFA production might be involved in the process of DR-H regulating bone formation.

Conclusions

The present study demonstrated that extracts of DR promoted bone formation in OVX rats, the mechanism of which might be related to regulate the composition and function of the gut microbiota. These findings offer valuable insights into the underlying mechanisms of DR in the treatment of OP and provide a new theoretical foundation for its clinical application.

Materials and Methods

Preparation of water extracts of Drynariae Rhizoma

Four kilograms of DR were obtained from the Bei Jing Shen Gang Company (batch number 1 905 036), and meet the quality standard of the pharmacopoeia of the Peopleʼs Republic of China (2020 edition) [46]. The DR extraction process involved reflux extracting twice with 32 or 28 kilograms of distilled water each time at 100 °C [46]. The resulting extracts were combined and concentrated using rotary evaporation at 60 °C to achieve a final concentration of 1 gram of DR extract per milliliter. The concentrated extract was then cooled to room temperature and stored at − 80 °C for further use.

High-performance liquid chromatography detection of water extracts of Drynariae Rhizoma

The whole process followed the pharmacopoeia of the Peopleʼs Republic of China (2020 edition), and naringin standards (batch number B21594, purity greater than 98%) obtained from Shanghai Yuanye Bio-Technology Co., Ltd. Initially, 10.0 mL of water extracts of DR were freeze-dried using an ALPHA 2 – 4 LD Plus freeze-dryer, yielding 1.40 grams of powder. Subsequently, 0.025 grams of the powder was dissolved in 10 mL of methanol, and ultrasonic-assisted extraction was carried out at 300 watts for 30 min at 40 °C, with the missing solution replenished. An Agilent/1260 Infinity II HPLC-diode array detector (HPLC-DAD) system (Agilent) was employed to detect the content of the water extracts of DR. Lichrospher-C₁₈ columns (250 mm × 4.6 mm, 5 µm; Jiangsu Hanbang Science & Technology Co., Ltd.) were used. The mobile phase consisted of water, methanol, and acetic acid, with a proportion of 65, 35, and 4 for 20 min, and the column temperature was maintained at 30 °C. The DAD detector was set at 283 nm to monitor elutes. Additionally, a standard curve of naringin with different concentrations (36, 72, 108, 144, and 180 mg/L) was established with the same detecting condition. The presence of naringin was confirmed by comparing retention times and ultraviolet spectra with reference standards, and its quantification was calculated upon the corresponding standard curve based on the peak areas of the samples.

Animal treatments

Thirty-three-month-old female Sprague Dawley rats were obtained from Guangdong Provincial Laboratory Animal Public Service Center [SCXK(Yue)2018 – 0034] and raised at Boji Medical & Technological Co. Ltd. [SYXK(Yue)2017 – 0134] under specific pathogen-free facilities with controlled temperature (23 ± 1 °C), humidity (50 ± 10%), a 12-hour light/dark cycle, and free access to food and water. After a 1-week adaptation phase, the rats were divided into five groups: a sham-operated (Sham, n = 6) group, an ovariectomized (OVX, n = 6) group, DR treatment groups with a high dose (DR-H; 2.43 g/kg/day, n = 6), middle dose (DR-M; 0.81 g/kg/day, n = 6), and low dose (DR-L; 0.27 g/kg/day, n = 6). Bilateral ovariectomy surgery was performed to stimulate bone mass loss following the protocol described in previous studies [32]. Briefly, rats were anesthetized by 2% sodium pentobarbital through intraperitoneal injection with a dosage of 0.2 mL per 100 g. Then, laparotomy was carried out after the rats were unconscious, followed by bilateral oophorectomy on the rats in OVX and DR treatment groups, while an equivalent volume of fat near the ovary was removed in the Sham group. According to the pharmacopoeia of the Peopleʼs Republic of China (2020 edition) [46], the recommended dosage of a DR decoction piece for human consumption is 9 grams, which was used as the middle dose in this study. Based on the body surface area conversion of clinical doses, the dose of intragastric administration of DR for each group was one-third and three times the dose of DR-M, respectively [47], [48]. Our protocol abided by the guidelines established by the National Institutes of Health and Boji Medical & Technological Co. Ltd. Animal Care Committee (approval number: IACUC-N2040-PD, November 23, 2020). After 12 weeks of treatment, all rats were anesthetized by 2% sodium pentobarbital. After the rats were unconscious, blood from the abdominal aorta was collected, stored at room temperature for 2 h, and centrifuged at 1500 rpm for 15 min. Then, the supernatant was extracted. Also, the bone tissues such as femurs and lumbar vertebrae were obtained for further analysis.

Micro-computed tomography images of femurs

The femurs were collected and fixed in 4% paraformaldehyde, then subjected to scanning using a Hiscan XM Micro-CT (Suzhou Hiscan Information Technology Co., Ltd.). The parameters were established at 60 kV and 133 µA, with images captured at a resolution of 50 µm and an 0.5° rotation step through a 360° angular range, with 50 ms exposure per step. The reconstructed images were analyzed using Hiscan Reconstruct software and Hiscan Analyzer software (Version 3.0, Suzhou Hiscan Information Technology Co., Ltd.) to analyze the data of BMD, BV/TV, Tb.Th, Tb.N, and Tb.Sp.

Hematoxylin and eosin and immunohistochemical analysis

The femurs and lumbar vertebrae were collected and subsequently fixed with a 4% paraformaldehyde solution and then decalcified with a 10% ethylenediaminetetraacetic acid solution at room temperature for 1 month. After that, the dehydrated samples were embedded in paraffin and sectioned at about 5 µm. Next, they were subsequently dehydrated with an alcohol gradient and embedded in paraffin. A portion of the sections were stained with H&E, while others were reserved for IHC analysis, as described in a previous study [47]. Briefly, the sections were prepared, stained, counterstained, dehydrated, hyalinized, and mounted, following which the antibody against collagen type I alpha 1 (COL1A1, 72 026; Cell Signaling Technology) and runt-related transcription factor 2 (RUNX2, ab76956; Abcam) were diluted at a ratio of 1 : 100. All images were captured by a microscope (Zeiss, AXIO; Carl Zeiss Microscopy GmbH).

Enzyme-linked immunosorbent assay assay

The content of E2 (Enzyme-linked Biotechnology), OCN (Enzyme-linked Biotechnology), TRAP (Enzyme-linked Biotechnology), and SCFA (Bioroyee Biotech) in serum was analyzed using an ELISA kit following the manufacturerʼs instructions.

Inorganic ion assay

The content of Ca and P ions in serum was analyzed by using the Ca and P assay kit (GM1125 and GM1127; Servicebio) according to the manufacturerʼs instructions and the quantitatively analysis based on a biochemical analyzer (Chemray-800; Rayto).

Alkaline phosphatase assay

The content of ALP in serum was evaluated using an ALP analysis kit (A059 – 2; Nanjing Jiancheng Biological Engineering Research Institute). Briefly, serum samples were prepared and related reagents were added. Detection was performed at 520 nm with a microplate reader (Biotek, Epoch) according to the instructions provided by the manufacturer.

Western blot

Total protein was extracted by RIPA lysis buffer (P0013B; Beyotime) and separated by 10% SDS-PAGE electrophoresis, followed by transferring the protein onto PVDF membranes. Next, it was incubated with primary antibodies, including anti-ALP (GTX42809; GeneTex, anti-bone morphogenetic protein-2 (BMP-2, ab225898; Abcam), anti-COL1A1 (72 026; Cell Signaling Technology), anti-RUNX2 (ab192256; Abcam), and anti-glyceraldehyde-3-phosphate dehydrogenase (GAPDH, 5147S; Cell Signaling Technology), all at a dilution of 1 : 1000 and at 4 °C overnight. The next day, the membranes were incubated with HRP-conjugated secondary antibodies at a dilution of 1 : 2500 (7074P2; Cell Signaling Technology) for 1 h at room temperature. The signals were visualized using a Bio-Rad apparatus, and band intensities were determined using Image J software and normalized to GAPDH.

Real-time quantitative polymerase chain reaction

Total RNA was extracted by Trizol reagent (15 596 – 026; Takara), and the quality and quantity of the extracted RNA were evaluated by nanodrop 2000. Next, 1.5 micrograms of total RNA were reverse transcribed into cDNA using a cDNA synthesis kit (638 313; Takara). SYBR Green mix (A304-01; Genestar) was used to amplify, and the data were calculated using the formula of 2^–ΔΔct with GAPDH as an internal control. The prime sequences are listed in [Table 2].

Table 2 The primer sequences.

Gene name		5′-3′ sequence
Alpl	Forward:	GACAAGAAGCCCTTCACAGC
	Reverse:	ACTGGGCCTGGTAGTTGTTG
Bmp-2	Forward:	GCCATCGAGGAACTTTCAGA
	Reverse:	TGTTCCCGAAAAATCTGGAG
Col1a1	Forward:	ACGTCCTGGTGAAGTTGGTC
	Reverse:	TCCAGCAATACCCTGAGGTC
Runx2	Forward:	AACAGCAGCAGCAGCAGCAG
	Reverse:	GCACGGAGCACAGGAAGTTGG
Gapdh	Forward:	GACATGCCGCCTGGAGAAAC
	Reverse:	AGCCCAGGATGCCCTTTAGT

16S rDNA sequencing

The DNA from various fecal samples was extracted using the CTAB extraction method in accordance with the manufacturerʼs instructions (L-AX0699; Ansiang). The complete 16S rDNA gene was amplified using the primers 27F: 5′-AGRGTTYGATYMTGGCTCAG-3′ and 1492R: 5′- RGYTACCTTGTTACGACTT-3′, each tagged with a specific barcode corresponding to the respective sample. PCR amplification was carried out, and the resultant products were verified using 2% agarose gel electrophoresis. The purified products were obtained using the AxyPrep DNA Gel Extraction Kit (Axygen Biosciences) in accordance with the manufacturerʼs instructions. The amplicon pools were quantified using a TM-ST kit (Promega), and libraries were prepared for sequencing. The libraries were prepared with the Pacific Biosciences TM Template Prep kit 1.0 (PacBio) and sequenced on a Sequel II platform (LC-Bio Technology Co., Ltd.).

Gas chromatography detection

Gas chromatography analysis was performed on a trace 1310 gas chromatograph (Thermo Fisher Scientific). The GC was fitted with a capillary column Agilent HP-INNOWAX (30 m × 0.25 mm ID × 0.25 µm) and helium was used as the carrier gas at 1 mL/min. Injection was made in split mode at 10 : 1, with an injection volume of 1 µL and an injector temperature of 250℃. The temperature of the ion source and MS transfer line were 300 and 250℃, respectively. The column temperature was programmed to increase from an initial temperature of 90℃, followed by an increase to 120℃ at 10℃/min, and to 150℃ at 5℃/min, and finally to 250℃ at 25℃/min, which was maintained for 2 min.

Statistical analysis

The data in this study are presented either in replicated values or as the mean ± standard deviation. The normality of the data was assessed using Graphpad Prism 8.0 (GraphPad Software), and differences between groups were evaluated by one-way analysis of variance (ANOVA). A p value less than 0.05 was considered to indicate a significant difference.

The 16S rDNA sequencing data were analyzed using the following methods: circular consensus sequence (CCS) reads were generated from raw subreads using SMRT Link (v6.0) with the parameters set to minPasses = 3 and minPredictedAccuracy = 0.99. Lima (v1.7.1) was employed to differentiate CCS reads from different samples, while Cutadapt (v1.9) was used to identify primers. CCS reads ranging from 1200 bp to 1650 bp in length were retained after length filtration. After dereplication and filtering of chimeric sequences using DADA2, feature table and feature sequence were obtained. Normalized alpha diversity and beta diversity were calculated by randomly matching the same sequences. The alpha diversity was used to analyze the complexity of species diversity in a sample via six indices, including Chao1, Observed_features, Goods coverage, Shannon, Simpson, and Pielou_e. All these indices were calculated using QIIME2. Beta diversity was also calculated using QIIME2. The annotated Amplicon Sequence Variants were aligned with the SILVA database (release 138). Other diagrams were generated using R packages.

Contributorsʼ Statement

Data collection: Q. Lin, X. C. Ouyang, Q. Pan; design of the study: X. Y. Li, R. H. Zhang; statistical analysis: J. J. Huang, Z. F. Zhang, Y. M. Yang; analysis and interpretation of the data: H. Y. Wang, L. Yang; drafting the manuscript: Q. Lin, X. Y. Li; critical revision of the manuscript: X. F. Zhu, R. H. Zhang.

Conflict of Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgements

The authors would like to express their gratitude to the MCMIA and Vincent & Lily Woo Foundation for the Vincent & Lily Woo Fellowship, and the Analytical and Testing Center of Jinan University for research equipment and technical support in this research.

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Publication History

Received: 07 May 2024

Accepted after revision: 04 November 2024

Accepted Manuscript online:
05 November 2024

Article published online:
17 January 2025