D. nobile was purchased from Sichuan Gentle Orchid Agricultural Science and Technology Co., LTD (Ziyang, China). The stems of D. nobile were dried in an oven at 60 °C. The dried stems were ground into powder by a pulveriser, which was then sieved through an 80-mesh sieve. The powdered substance was steeped in petroleum ether for 30 min with ultrasonic oscillation to defeat it. After the solid‒liquid mixture was filtered, the residues were extracted by 80%, 75%, and 70% ethyl alcohol (1:50 g/mL w/v) by ultrasonication for 30 min at 50 °C and filtered. After mixing all of the ethanol extracts and evaporation, the crude extract was produced (labelled EA). The crude EA extract was dissolved in deionized water and then extracted with solvents of increasing polarity, trichloromethane (labelled TCM), ethyl acetate (labelled EAC), and water-saturated n-butanol (labelled NBA). All the extracts were evaporated and stored at –20 °C in the dark.

As previously published, aluminum chloride colorimetry was employed to examine the total flavonoid concentration in the four D. nobile preparations, with minor modifications [20]. The D. nobile extract (324 $\mu$L) was mixed with 18 $\mu$L sodium nitrite solution (5%, w/v), and then the mixture was subsequently left at room temperature for 6 min. Then, the mixture was added to 18 $\mu$L aluminum nitrate and incubated for another 6 min. Then, 240 $\mu$L 1 mol/L sodium hydroxide was added to the mixture. The reaction was conducted at room temperature for 15 min. At 510 nm, the absorbance of the resulting mixture was measured. A rutin standard curve was used to determine the total flavonoid content, which was represented in milligrams of rutin equivalent per gram of D. nobile powder.

As previously stated, the Folin-Ciocalteu technique was used to determine the total polyphenol content in the four D. nobile extracts, with minor modifications [21]. The D. nobile extract (60 $\mu$L) was mixed with 18 $\mu$L Folin-Ciocalteu phenol reagent, followed by 90 $\mu$L sodium carbonate (20%, w/v) and 432 $\mu$L deionized. For 20 min, the reaction was conducted in the dark at room temperature. At 760 nm, the absorbance of the resulting mixture was measured. A gallic acid standard curve was used to determine the total polyphenol content, which was represented in milligrams of gallic acid equivalent per gram of D. nobilepowder.

Female Kunming mice, 8–10 weeks old and weighing 40–45 g, were procured from Chongqing Medical University’s experimental animal center (Reg. No. SCXK 2018-0003). The mice were kept in a polypropylene cage with an ambient temperature of 25 °C, relative humidity of 40–70%, and a 12-hour dark/12-hour light cycle. For a one-week acclimation period, all mice were given free access to common rodlike meals and water.

Except for the animals in the negative control group (NC), D-galactose was administered subcutaneously at a dose of 125 mg/kg b.w. for creating subacute ageing models. After 10 days, the D-galactose-treated mice were randomly separated into six groups using a completely random design. The NC group and the aging control group (AC) were orally administered solvent every day. The positive control group (PC) was orally administered resveratrol (200 mg/kg b.w.) every day. Mice in the EA, TCM, EAC and NBA groups were orally dosed daily with D. nobile extracts (200 mg/kg b.w) extracted using ethanol, chloroform, ethyl acetate and n-butanol, respectively. All the animals except for the NC group were injected subcutaneously with D-galactose (125 mg/kg b.w.) every day. All treatments lasted for 8 weeks. After collecting blood samples from the tail vein, the mice were euthanized by isoflurane overdose. Tissue samples were obtained for physiological index measurement and histopathological observation.

The wrinkle grade of the back skin of the mice was rated by three observers (single-blind) before and every two weeks after the initial treatment, and the scoring details were adjusted properly based on the literature [22]. Meanwhile, the mice were weighed, and we observed whether their hair was smooth, dry, yellow, or lacking luster and whether they showed flexible or slow behavior and quick or slow response.

The running test was measured by a level treadmill (FT-200, Chengdu Taimeng Software Co. Ltd., Chengdu, China). Running training was given twice on nonconsecutive days (Days 1 and 3), with a fixed speed run of 20 m/min for 20 min. On Day 5, there were two stages to the treadmill exam. The first stage consisted of a five-minute run at a speed of 10 m/min. After 5 min of running, the speed is increased to 20 m/min until exhaustion is reached. The same treadmill level was used for all of the training and testing. Any mouse that resisted probing for 10 seconds and remained on the platform was declared fatigued, and the time was recorded.

After blood collection from the tail vein of mice, they were separated by centrifugation at 3000 r/min for 10 min. After euthanasia of the mice, the skin, liver and brain were quickly removed and homogenized in ice-cold 0.9% NaCl solution, followed by centrifugation at 3000 $\times$ g for 15 min at 4 °C. MDA, SOD, CAT and GSH-Px levels were measured in blood and three tissue supernatants using immuno kits according to the manufacturer’s instructions.

Tissues taken from the euthanized mice were washed with ice-cold normal saline before being immobilized for 24 hours in a 4% paraformaldehyde solution. The tissues were then fixed in molten paraffin and cut into 3 $\mu$m thick tissue slices. After deparaffinization and hematoxylin-eosin (HE) staining, tissue sections were examined under a light microscope for histological investigation.

Total RNA was extracted from the brain samples by the TRIzol (Invitrogen, Carlsbad, CA, USA) method, and genomic DNA was removed using DNase I (Takara, Tokyo, Japan). The quality of the RNA samples was determined by a 2100 Bioanalyzer (Agilent Technologies, Inc., Santa Clara, CA, USA) and ND-2000 (Nanodrop Technologies, Wilmington, DE, USA). A TruSeqTM RNA Sample Preparation Kit (Illumina, San Diego, CA, USA) was used to establish the RNA library. After quantification using the TBS380 microfluorometer (Yuanpinghao Biotechnology Co., Beijing, China) with Picogreen (Invitrogen, Carlsbad, CA, USA), high-throughput sequencing was performed on an Illumina HiSeq XTEN/NovaSeq 6000 sequencing platform (Illumina, San Diego, CA, USA), and the sequencing length was PE150. The raw sequencing reads were deposited into the NCBI Sequence Read Archive (SRA) database (Accession Number: PRJNA867020). Bioinformatic analysis of the transcriptome data was carried out using the online Majorbio Cloud Platform (https://www.majorbio.com) [23].

Total microbial genomic DNA was extracted from mouse colon content samples using the E.Z.N.A.® soil DNA Kit (Omega Bio-Tek, Norcross, GA, USA) according to the manufacturer’s instructions. The quality and concentration of DNA were determined by 1.0% agarose gel electrophoresis and a NanoDrop® ND-2000 spectrophotometer (Thermo Fisher Scientific Inc., Wilmington, DE, USA) and kept at –80 ℃ before further use. The hypervariable region V3-V4 of the bacterial 16S rRNA gene was amplified with the primer pairs 338F (5′-ACTCCTACGGGAGGCAGCAG-3′) and 806R (5′-GGACTACHVGGGTWTCTAAT-3′) [24] by an ABI GeneAmp® 9700 PCR thermocycler (ABI, Foster City, CA, USA). Purified amplicons were pooled in equimolar amounts and paired-end sequenced on an Illumina NovaSeq 6000 platform (Illumina, San Diego, CA, USA) according to the standard protocols by Majorbio Bio-Pharm Technology Co. Ltd. (Shanghai, China). The raw sequencing reads were deposited into the NCBI Sequence Read Archive (SRA) database (Accession Number: PRJNA863054).

Bioinformatic analysis of the gut microbiota was carried out using the online Majorbio Cloud Platform (https://www.majorbio.com) [23]. Based on the ASV information, rarefaction curves and alpha diversity indexes, including observed ASVs, Chao1 richness, Shannon index, and Good’s coverage, were calculated with Mothur v1.30.1 (https://www.mothur.org/wiki/Download_mothur). The similarity among the microbial communities in different samples was determined by principal coordinate analysis (PCoA) based on the unweighted UniFrac dissimilarity using R package vegan v2.5-3 (http://www.cran.r-project.org/package=vegan).

Statistical analyses were performed using GraphPad Prism 6 (GraphPad Software, San Diego, CA, USA). For multiple datasets, data were subjected to one-way ANOVA followed by Dunnett’s multiple comparisons test when comparing every mean to a control means. All p values 0.05 were considered statistically significant.

The total polyphenol content (TPC) and total flavonoid content (TFC) were determined using the photocolorimetric method with gallic acid and rutin as standards (Fig. 1). As shown in Fig. 1B, the TPC of the EA crude extracts was twice as high as the TFC. After secondary extraction with different polar solvents, the TPC and TFC were highest in TCM, followed by EAC. They were lowest in NBA, and the TFC was much lower than the TPC.

Fig. 1.

Total flavonoid and phenolic contents of various polarity extracts from D. nobile. (A) Gallic acid and rutin standard curves. A rutin standard curve was used to determine the total flavonoid content (TFC) at 510 nm. At 760 nm, a gallic acid standard curve was used to determine the total polyphenol content (TPC). (B) The content of TFC and TPC in the extracts of each group. NC, negative control; AC, aging control; PC, positive control; EA, ethanol extract; TCM, chloroform extract; EAC, ethyl acetate extract; NBA, n-butanol extract; OD, optical density.

We used a treadmill to test the endurance of each group of mice. The running time of mice in the AC group was significantly shorter than that of mice in the NC group. The running time of mice in the PC, EA and EAC groups was significantly increased compared to that of mice in the AC group and was similar to that of the NC group (Fig. 2A). Mice in the AC group had significantly higher body weights than mice in the NC group. The body weight of mice in the PC, EA and EAC groups was significantly lower than that of mice in the AC group and similar to that of the NC group. The body weight of mice in the TCM and NBA groups was significantly lower than that of mice in the AC group and much lower than that of mice in the NC group (Fig. 2B). Compared with mice in the AC group, the spleen coefficient of mice in the NBA group was basically the same as that in the AC group, while the spleen coefficient of mice in the NC, PC, EA and TCM groups was slightly higher than that in the AC group and that of mice in the EAC group was significantly higher than that in the AC group (Fig. 2C). Compared with the mice in the AC group, the thymus coefficient of the mice in the TCM and NBA groups was basically the same as that in the AC group, the thymus coefficient of the mice in the PC group was slightly higher than that in the AC group, and the thymus coefficient of the mice in the NC, EA and EAC groups was significantly higher than that in the AC group (Fig. 2D).

Fig. 2.

Endurance, weight gain and organ coefficient of aging mice following D. nobile extract treatment. (A) Running time during the endurance test. All groups ran on a treadmill at 10 m per minute for the first 5 min and 20 m per minute thereafter until exhaustion. (B) Effects of different compounds on body weight gains of D-galactose-induced ageing mice after oral administration for 8 weeks. Bodyweight gain (%) = [(bodyweight of 8 weeks – bodyweight of 1 week)/bodyweight of 1 week] $\times$ 100. Spleens (C) and thymuses (D) were weighed immediately after extraction from euthanized mice for organ coefficient according to (organ weight/mice weight) $\times$1000. Each value is expressed as the mean $\pm$ SE (n = 6). *p 0.05, **p 0.01, compared with the AC group. NC, negative control; AC, aging control; PC, positive control; EA, ethanol extract; TCM, chloroform extract; EAC, ethyl acetate extract; NBA, n-butanol extract.

As shown in Fig. 3, after 8 weeks of treatment, the MDA content in the skin of the AC group was significantly higher than that of the NC group, while the MDA content in the liver of the EA and EAC groups was significantly lower than that of the AC group (Fig. 3A,C). The EA extracts significantly upregulated SOD, CAT and GSH-Px activities in the skin compared to the AC group. In addition, EAC extracts significantly upregulated skin CAT and GSH-Px activities (Fig. 3A). In blood, EA extracts significantly upregulated SOD and CAT activities, while EAC extracts significantly upregulated SOD, CAT and GSH-Px activities (Fig. 3B). In the liver, SOD, CAT and GSH-Px activities were significantly upregulated in the EA group, while CAT levels were upregulated in the EAC group, and GSH-Px activities were upregulated in the NBA group (Fig. 3C). In brain tissue, SOD and GSH-Px activities were significantly upregulated in the EA group, while GSH-Px activities were upregulated in the EAC group (Fig. 3D). In summary, all D. nobile extracts were effective in increasing the activity of antioxidant factors in skin, serum, liver and brain, with the effects on skin and liver being more pronounced. In addition, the antioxidant activity was stronger in the EA and EAC groups.

Fig. 3.

Analysis of antioxidant indicators including SOD, CAT, and GSH-Px activity and MDA content in the skin (A), blood (B), liver (C), and brain (D). Values represent the mean $\pm$ S.E. M (n = 6). *p 0.05, **p 0.01, ***p 0.001, compared with the AC group. NC, negative control; AC, aging control; PC, positive control; EA, ethanol extract; TCM, chloroform extract; EAC, ethyl acetate extract; NBA, n-butanol extract.

According to the histological analysis of H&E staining, mice in the NC group had a thick skin dermis with a clear and orderly structure, while mice in the AC group had a much thinner skin dermis with many adipocytes. Mice in the PC, EA and EAC groups had skin similar to that of the NC group, while mice in the TCM and NBA groups had skin similar to, but better than, that of the AC group (Fig. 4). Hepatocytes in the AC group were increased in size and had some edema, with a large amount of hepatocyte necrosis and steatosis. On the other hand, liver tissue from mice in the NC, PC, EA and EAC groups showed normal hepatocytes with no necrosis around the central vein. Pathological changes were also present in the TCM and NBA groups, but the symptoms were not as severe as those in the AC group (Fig. 4). In the NC group, the hippocampal CA1 region had tightly arranged pyramidal cells with normal cell morphology. The AC group had sparsely scattered pyramidal cells with more necrotic neuronal cells. The PC, EA and EAC groups had more tightly arranged pyramidal cells than the AC group, with less degeneration and necrosis of neurons, especially in the EA group (Fig. 4). Spleen pathology in the AC group showed blurred boundaries between the white and red marrow, severe loss of white marrow and a marked decrease in the white marrow/red marrow ratio. In addition, the spleen in the AC group had interstitial fibrous tissue hyperplasia and vascular growth. The severity of spleen lesions was greatly reduced in the EA and EAC groups compared to the AC group (Fig. 4). Follicle cells in the ovaries of the NC group were well developed with abundant corpus luteum tissue. Pathological lesions such as ovarian atrophy, follicular cell disintegration, corpus luteum and fibrous tissue hyperplasia were significantly higher in the AC group. Follicles in the EA and EAC groups grew well, and the number of follicular cells was appreciable compared to that in the AC group (Fig. 4). Thus, D. nobile extracts showed significant improvement in the pathological changes of the tissues.

Fig. 4.

Histopathological results of HE staining in mouse tissues. NC, negative control; AC, aging control; PC, positive control; EA, ethanol extract; TCM, chloroform extract; EAC, ethyl acetate extract; NBA, n-butanol extract.

A large number of studies have reported that aging can lead to the degeneration of brain function, which is the basis of neurodegeneration and dementia [25, 26]. In previous work, we found that EA and EAC reduced cellular senescence and oxidative stress in aging mice, so we wondered whether EA and EAC could regulate aging-related gene expression levels in the brain. We performed transcriptome sequencing analysis of brain tissue from D-galactose-induced aging mice in the EA and EAC groups. We found that 643 genes were upregulated and 707 genes were downregulated in aging mice of the AC group compared with normal mice of the NC group (Fig. 5A,B). EA and EAC reversed the same 235 upregulated and 72 downregulated genes associated with aging. In addition, EA alone reversed the upregulation of 134 genes and the downregulation of 68 genes. EAC alone reversed the upregulation of 25 genes and downregulation of 25 genes (Fig. 5A,B). KEGG analysis of these differentially regulated genes regulated by EA and EAC showed that most of the regulation at the gene level in aging mice was clustered in signaling molecule interaction pathways and signal transduction pathways (Fig. 5C,D). In addition, EAC regulates many genes in the endocrine system pathway (Fig. 5C). Cluster analysis of differentially expressed genes in these pathways revealed that important genes related to aging, such as Il1a, Il1b, Il1rn, Ccl3, Ccl4, Fos and Gck, were restored to low expression levels (Fig. 5E–G and Supplementary Fig. 1). In conclusion, EA and EAC have a significant downregulation effect on aging-related genes, indicating that EA and EAC have antiaging effects at the gene expression level.

Fig. 5.

Transcriptome sequencing analysis of mouse brain tissue. (A,B) Venn plots indicate the number of genes that are regulated by EA and EAC in D-galactose-induced ageing mouse brains, and “up” and “down” represent the changes in gene expression levels of the former compared with the latter, p 0.001. (C,D) Differential genes with significant changes in expression after EA and EAC interventions were analysed for the KEGG pathway. (E–G) The three most enriched pathway genes in the KEGG analysis of the EAC group were analysed by heatmap clustering. In the figure, red represents a high expression level of the gene in the sample, while blue represents a low expression level. The number label is under the color bar on the upper left for the specific change trend of the expression level. NC, negative control; AC, aging control; PC, positive control; EA, ethanol extract; TCM, chloroform extract; EAC, ethyl acetate extract; NBA, n-butanol extract; vs, versus.

The antiaging effect was better in the EA and EAC groups. We selected the EA, EAC, NC, and AC groups of mouse colon contents for 16S rRNA sequencing to obtain ASV data for each sample. The ASVs of each group were analysed by Pan and Core species analysis and rarefaction curve analysis, and it was found that all gut microbiota samples were representative and stable (Fig. 6A–C). Combining the rarefaction curves and Venn diagrams of each group revealed that D-galactose injection significantly reduced the gut microbiota diversity of mice. The gut microbiota diversity of mice in the EA and EAC groups increased significantly after the intervention, although the number of gut microbiota in the EAC group remained low (Fig. 6C,D). Genus-based PCoA showed that the gut microbiota of the NC, EA, and EAC groups was clustered, while that of the NA group was disorganized and discrete (Fig. 6E). We analysed gut microbiota taxonomy at the phylum level and found that the EA and EAC groups significantly reversed the decrease in abundance of the dominant mouse flora bacteroidota and the increase in abundance of actinobacteria caused by aging. The EA group also reversed the increase in Firmicutes abundance, but the two treatment groups did not show a reversal effect on the increase in Proteobacteria abundance (Fig. 6F). A genus-level-based heatmap revealed that the EAC and EA groups reversed 11 and 18 D-galactose-induced changes in the abundance of the Firmicutes subtype, 5 and 11 changes in the abundance of the Bacteroidetes subtype, and 3 and 4 changes in the abundance of the Actinobacteria subtype in the gut microbiota, respectively (Fig. 6G). These results indicated that both ethyl acetate and ethanol extracts of D. nobile could improve the gut microbiota dysbiosis of aging mice to varying degrees, with the ethanol extract being the most effective.

Fig. 6.

Active ingredients of D. nobile regulate gut microbiota dysbiosis in aging mice. The colonic contents of mice in the EA, EAC, NC, and AC groups were selected for 16S rRNA sequencing to obtain ASVs for each sample, and the ASV data from each sample were drawn flat and processed. (A,B) The ASV data of the gut microbiota were based on Pan and Core species analysis at the genus level. (C) The ASV data of the gut microbiota were based on rarefaction curve analysis at the ASV level. (D) Venn diagram analysis of ASV data of gut microbiota based on ASV levels. (E) Unweighted UniFrac PCoA based on the genus level of gut microbiota ASV data. (F) Community Barplot analysis based on gut microbiota ASV data at the phylum level. (G) Community heatmap analysis of gut microbiota ASV data based on the genus level. NC, negative control; AC, aging control; PC, positive control; EA, ethanol extract; TCM, chloroform extract; EAC, ethyl acetate extract; NBA, n-butanol extract.