Abstract Ageing is becoming an increasingly serious problem; therefore, there is an urgent need to find safe and effective anti-ageing drugs. Aims To investigate the effects of Bazi Bushen capsule (BZBS) on the senescence of mesenchymal stem cells (MSCs) and explore its mechanism of action. Methods Network pharmacology was used to predict the targets of BZBS in delaying senescence in MSCs. For in vitro studies, MSCs were treated with D-gal, BZBS, and NMN, and cell viability, cell senescence, stemness-related genes, and cell cycle were studied using cell counting kit-8 (CCK-8) assay, SA-β-galactosidase (SA-β-gal) staining, Quantitative Real-Time PCR (qPCR) and flow cytometry (FCM), respectively. Alkaline phosphatase (ALP), alizarin red, and oil red staining were used to determine the osteogenic and lipid differentiation abilities of MSCs. Finally, the expression of senescence-related genes and cyclin-related factors was detected by qPCR and western blotting. Results Network pharmacological analysis suggested that BZBS delayed cell senescence by interfering in the cell cycle. Our in vitro studies suggested that BZBS could significantly increase cell viability (P < 0.01), decrease the quantity of β-galactosidase^+ cells (P < 0.01), downregulate p16 and p21 (P < 0.05, P < 0.01), improve adipogenic and osteogenic differentiation, and upregulate Nanog, OCT4 and SOX2 genes (P < 0.05, P < 0.01) in senescent MSCs. Moreover, BZBS significantly reduced the proportion of senescent MSCs in the G[0]/G[1] phase (P < 0.01) and enhanced the expression of CDK4, Cyclin D1, and E2F1 (P < 0.05, P < 0.01, respectively). Upon treatment with HY-50767A, a CDK4 inhibitor, the upregulation of E2F1 was no longer observed in the BZBS group. Conclusions BZBS can protect MSCs against D-gal-induced senescence, which may be associated with cell cycle regulation via the Cyclin D1/CDK4/E2F1 signalling pathway. Keywords: Mesenchymal stem cells, Cell senescence, Bazi bushen capsule, Cell cycle, Network pharmacology 1. Introduction In recent years, with the increase in human life expectancy, the world's population has gradually aged, resulting in serious social, health, and economic problems [[45]1]. Ageing is a gradual process that is part of the life cycle of every organism [[46]2]. This is a natural, evolutionarily programmed phenomenon characterised by degenerative events such as tissue degeneration, telomere shortening, dementia, cognitive deficits, functional impairment, and chronic diseases [[47]3]. Experts have proposed 12 markers of ageing, including cellular senescence, stem cell exhaustion, and genomic instability [[48]4]. Senescence and exhaustion of stem cells are the core mechanisms of ageing [[49]5]. An increasing number of studies have shown that delaying the senescence of stem cells can help to effectively resist overall ageing and prolong life span [[50]6]. Therefore, delaying stem cell senescence may improve phenotypes associated with ageing. MSCs are primary pluripotent cells isolated from various tissues [[51]7]. It plays crucial roles in haematopoiesis, immune regulation, and tissue repair [[52]8]. The decreased ability of adult stem cell populations to proliferate and regenerate is one of the main causes of the human ageing process [[53]5]. Current anti-ageing drugs exhibit potent anti-ageing effects; however, some drawbacks remain regarding their safety and long-term use [[54][9], [55][10], [56][11]]. Therefore, it is necessary to find anti-ageing drugs that are not only safe and effective for longer usage periods. The basic theory of traditional Chinese medicine (TCM) believes that the deficiency of ‘kidney essence’ is the fundamental cause of ageing [[57]12]. BZBS, as a representative Chinese patent medicine, consists of 16 herbs [[58]13,[59]14]; it contains Cuscuta chinensis Lam. (Tu-Si-Zi), Lycium harharum L. (Gou-Qi-Zi), Schisandra chinensis (Turcz.) Baill (Wu-Wei-Zi), Cnidium monnieri (L.). Cusson (She-Chuang-Zi), Rosa Laevigata Michx. (Jin-Ying-Zi), Rubus chingii Hu (Fu-Pen-Zi), Allium tuberosum Rottler ex Spreng. (Jiu-Cai-Zi), Toosendan fructus (Chuan-Lian-Zi), Epimedium brevicornu Maxim. (Yin-Yang-Huo), Morindae officinalis radix (Ba-Ji-Tian), Cistanche deserticola Ma (Rou-Cong-Rong), Rehmannia root (Di-Huang), Cyathula officinalis K. C. Kuan (Chuan-Niu-Xi), Panax ginseng C. A. Mey. (Ren-Shen), Cervus nippon Temminck (Lu-Rong), and Hippocampal Kelloggi (Hai-Ma). Prescription tonic of ‘kidney essence’ balances ‘Yin and Yang’ and enhances archaeus, making the body healthy and full of spirit. Previous studies have shown that BZBS has anti-ageing effects [[60][14], [61][15], [62][16], [63][17], [64][18], [65][19]], such as inhibiting premature senescence in mice, slowing methylation, and maintaining telomere length. Furthermore, it is believed that the ‘kidney essence’ is closely related to stem cells. However, the mechanism by which BZBS effectively alleviates senescence in MSCs remains unclear. Recently, network pharmacology has been widely accepted as an efficient research strategy to explore TCM from the perspective of biological network balance [[66]20,[67]21]. In recent years, great progress has been made in the application of network pharmacology methods to study the scientific connotation of TCM, such as the identification of new targets, biological processes, and signalling pathways, the discovery of potential active compounds, and elucidation of the mechanism of action [[68][22], [69][23], [70][24], [71][25], [72][26], [73][27]]. Furthermore, previous studies using network pharmacology predict that BZBS can alleviate the cognitive impairment caused by ageing [[74]14,[75]15]. Therefore, it is possible to discover the core mechanisms of approved Chinese medicines through network pharmacology. In this study, we hypothesised that BZBS exerts anti-ageing effects on MSCs. This study is the first to investigate the effects and mechanism of action of BZBS on MSCs senescence using network pharmacology and in vitro cytology ([76]Fig. 1). The abbreviations in this article can be found in [77]Table 1. Fig. 1. [78]Fig. 1 [79]Open in a new tab Graphical abstract of anti-ageing validation of BZBS based on network pharmacology and in vitro experiments (Created with [80]BioRender.com). Table 1. Abbreviation list. Full name Abbreviation Mesenchymal stem cells MSCs Bazi Bushen capsule BZBS Nicotinamide mononucleotide NMN d-galactose D-gal SA-β-galactosidase SA-β-gal Alkaline phosphatase ALP Traditional Chinese medicines TCM Disease Gene Network DisGeNET Comparative Toxicogenomics Database CTD Therapeutic Target Database TTD Universal Protein UniProt Protein-protein Interaction Network PPI network Kyoto Encyclopedia of Genes and Genomes KEGG Flow Cytometry FCM Quantitative Real-Time PCR qPCR Glyceraldehyde-3-Phosphate Dehydrogenase GAPDH Polyvinylidene fluoride PVDF Radio-Immunoprecipitation Assay RIPA Phosphate buffer saline PBS Analysis of variance ANOVA Cell Counting Kit-8 CCK-8 Least significant difference LSD Senescence-Associated Secretory Phenotype SASP Cyclin-dependent kinase inhibitor 1A p21 Cyclin-dependent kinase inhibitor 2A p16 Cyclin-dependent kinase 4 CDK4 E2F transcription factor 1 E2F1 [81]Open in a new tab 2. Materials and methods 2.1. Network pharmacology Using ‘cellular ageing’ or ‘cell senescence’ as search terms, ageing-related genes were retrieved from six sources: DisGeNET [[82]28], Open Target Platform [[83]29], MalaCards [[84]30], CTD [[85]31], GeneCards, and text mining [[86]32]. To ensure data reliability, only genes that appeared in more than three databases were retained as the core gene set for ageing. A comprehensive target spectrum of BZBS is essential to study its substantive basis and mechanism of action in the treatment of ageing. We collected targets from DrugBank [[87]33], TTD [[88]34], ChEMBL [[89]35], the CTD database ([90]https://ctdbase.org/), and PubChem, and standardised their names using UniProt [[91][36], [92][37], [93][38]]. Gene sets related to ageing and potential targets of BZBS were analysed to identify the functional targets of BZBS for preventing and treating ageing. The target data were then submitted to STRING (version 12.0; [94]https://string-db.org/) for constructing the PPI network (confidence 0.7) [[95]39]. The PPI network was visualised using Cytoscape v3.9.0 [[96]40]. To explain the mechanisms of action of BZBS against ageing from a systematic perspective, we performed KEGG pathway enrichment analyses using Metascape ([97]https://metascape.org) and the ClueGO plugin in Cytoscape [[98]41]. 2.2. Preparation of BZBS and its compounds The BZBS stock solution was prepared in DMEM/F12 and diluted to the desired concentration with DMEM/F12 before the experiment. 2.3. Cell culture and treatment Human umbilical cord stem cells were purchased from Beijing Jing-Meng Cell Biotechnology Co. Ltd. (Cat # UC1139). MSCs were cultured in mesenchymal stem cell medium (Cat # MSC1201B, Cat # MSC1201S; Beijing Jing-Meng Cell Biotechnology Co., Ltd.) supplemented with 1‰ streptomycin, penicillin, and gentamicin, at 37 °C in a 5% carbon dioxide incubator. The media was changed every two days. The methods for isolation, cultivation, and characterisation of MSCs are described in detail by Fathi et al. [[99]42]. Cells in the logarithmic growth phase cells were seeded on plates at a density of 7 × 10^4–1 × 10^5/mL and cultured for 24 h before treatment. Three or more accessory wells were set up for each independent experiment for each group to ensure data reliability. D-Gal can significantly induce senescence in MSCs [[100]43]. The use of D-gal to accelerate animal ageing has gradually been recognised as an effective model for studying the mechanisms of ageing [[101]44]. Previous studies have demonstrated that D-gal can be used to model rapid cell senescence in vitro [[102][45], [103][46], [104][47]]. In this study, D-gal-induced MSCs were used to establish a rapid ageing model. MSCs were divided into Normal group (Control), Model group (d-galactose 20 mg/mL, 72h) (Model), Low dose Bazi Bushen capsule group (d-galactose 20 mg/mL + BZBS 10 μg/mL, 72h) (BZ-low), High dose Bazi Bushen capsule group (d-galactose 20 mg/mL + BZBS 20 μg/mL, 72h) (BZ-high), and NMN group (d-galactose 20 mg/mL+20 μM, 72h) (NMN). After adding CDK4 inhibitor (MCE, Cat #HY-50767A, USA), the group was divided into Normal group (Control), HY-50767A group (d-galactose 20 mg/mL + CDK4 inhibitors 1 μM, 72h), and BZ-high + HY-50767A group (d-galactose 20 mg/mL + BZBS 20 μg/mL + CDK4 inhibitors 1 μM, 72h). 2.4. Cell viability assay Cell viability was evaluated using CCK-8 (MCE, Cat # HY-K0301, USA) [[105]48]. 10 μL of CCK-8 solution was added to each well and incubated in a 37 °C incubator for 1–4 h. The absorbance was measured at 450 nm using a multifunctional microplate reader to calculate cell viability. 2.5. SA-β-gal staining SA-β-gal staining [[106]49] was performed using the SA-β-gal staining kit (Beyotime, Cat #C0602, China). The cells were then washed with PBS and incubated in a fixative solution for 15 min at room temperature. Then, the cells were washed with PBS and incubated in SA-β-gal staining solution at 37 °C overnight without CO[2]. Images were captured using an inverted microscope (Axio Vert.A1, Carl Zeiss, Germany), and positive cells were quantified from four fields in each well. 2.6. Quantitative Real-Time PCR (qPCR) Total RNA was isolated from MSCs using the Eastep® Super Total RNA Extraction Kit (Promega, Cat # LS1040, China), and reverse transcription of the RNA sample to cDNA was carried out using Prime Script reagent Kit (Takara, Cat # RR047A, Japan). qPCR was performed using TB Green® Premix Ex Taq™ II (Tli RNaseH Plus) (Takara, Cat # RR820A, Japan). Primers for each target mRNA were designed and are listed in [107]Table 2. The 2^−ΔΔCt method was used to calculate the relative expression levels of target genes, and GAPDH was used as an internal control [[108]50]. Table 2. List of qPCR primer sequences. Primer names Primer sequences p16 F: GGGTCGGGTAGAGGAGGTG R: GCTGCCCATCATCATGACCT p21 F: GTCCTTGGGCTGCCTGTTTT R: GTGGGAAGGTAGAGCTTGGG OCT4 F: CCTTCGCAAGCCCTCATTTC R: TAGCCAGCTCCGAGGATCAA Nanog F: GAATGAAATCTAAGAGGTGGCA R: CCTGGTGGTAGGAAGAGTAAAGG SOX2 F: AGAACCCCAAGATGCACAAC R: GGGCAGCGTGTACTTATCCT CDK4 F: GAGGCGACTGGAGGCTTTT R: GGATGTGGCACAGACGTCC Cyclin D1 F: GGAGAACAAACAGATCATCC R: GAATGAAGCTTTCCCTTCTG E2F1 F: CGCCATCCAGGAAAAGGTGT R: GATGCCCTCAAGGACGTTGG GAPDH F: AGAAGGCTGGGGCTCATTTG R: AGGGGCCATCCACAGTCTTC [109]Open in a new tab 2.7. Adipogenic and osteogenic differentiation 2.7.1. Oil red O staining Oil Red O staining was performed to analyse adipogenesis [[110]51]. After 72 h of D-gal and BZBS treatment, the ADP1/ADP2 adipogenic induction medium (Pricella, Cat # PD-019, China) was exchanged for adipogenic culture (ADP1 for 3 days, ADP2 for 1 d) and Oil Red O staining was performed after 14 days. The cells were fixed with 4% neutral formaldehyde solution at room temperature for 30 min, stained at room temperature for 30 min, and washed with PBS to remove the floating colour. Oil red staining was visualised using an inverted microscope. 2.7.2. ALP staining and alizarin red staining Osteogenic differentiation culture was performed after 72 h of D-gal and BZBS intervention, and the cells were cultured in osteogenic induction differentiation medium (Pricella, Cat # PD-017, China) for 7 days. A BCIP/NBT Alkaline Phosphatase Colour Development Kit (Beyotime, Cat #C3206, China) was used for staining. The cells were incubated at room temperature for 5–30 min or longer (up to 24 h) and washed with PBS to terminate the colour reaction. Osteogenic differentiation was cultured for 21 days, and alizarin red was used for staining. The cells were fixed with a 4% neutral formaldehyde solution at room temperature for 30 min, stained at room temperature for 30 min, and washed with PBS to remove the floating colour. ALP and Alizarin Red staining were visualised using a microscope [[111]52]. 2.8. Cell cycle assay The cell cycle was measured using FCM [[112]53]. A Cell Cycle Staining Kit (MULTISCIENCES, Cat # CCS012, China) was used to analyse the cell cycle distribution. Cells were collected and fixed with 70% ethanol at 4 °C overnight. The cells were then washed with PBS and incubated in propidium iodide (PI)/RNase A staining solution at room temperature in the dark for 30 min. The cell cycle distribution was detected using a flow cytometer (BD FACS Aria III flow cytometer). 2.9. Western blot MSCs treated under different conditions were collected and lysed with RIPA buffer containing protease inhibitors. After centrifugation (13,000 rpm, 30 min) at 4 °C, total protein concentrations of the supernatant were quantified by BCA protein assay kit (SEVEN, Cat # SW101-02, China). A total of 50 or 100 μg of denatured protein samples were separated by 4–20% SDS-PAGE gel and then transferred onto a PVDF membrane. After being blocked with blocking buffer (LI-COR, Cat # 927–70001, USA), the PVDF membrane was incubated with appropriate primary antibodies [CyclinD1 (1:1000), CDK4 (1:1000)] overnight at 4 °C. The membranes were washed three times and incubated with appropriate secondary antibodies (1:5000) at 37 °C for 1 h. Finally, immuno-positive bands were visualised and quantified with Odyssey-imaging systems (Nebraska, USA) and normalised with the corresponding β-actin (1:5000) as the internal control. The primary antibodies used for MSCs were anti-CDK4 (Abcam, Cat # ab108357, Britain), anti-Cyclin D1 (Abcam, Cat # ab134175, Britain), and anti-β-actin (Abcam, Cat # ab8227, Britain). The operational method can also be found in detail elsewhere [[113]53]. 2.10. Statistics All statistical analyses were performed using IBM SPSS 26.0. Data were tested for normal distribution (Shapiro-Wilk test) and homogeneity of variance (Levene's test for equality of variance). One-way analysis of variance (ANOVA) was used, and the least significant difference (LSD) method was used for pairwise comparisons between groups. The Kruskal-Wallis test was used for non-normally distributed data analysis. P < 0.05 was considered statistically significant. All graphs were generated using GraphPad Prism (V.8.01). Experimental data were expressed as mean ± standard deviation ( [MATH: X‾±S :MATH] ). 3. Results 3.1. Network pharmacology analysis Based on the pathogenic genes reported in the ageing literature and the therapeutic targets of approved drugs, a PPI molecular network of ageing-specific pathogenesis was constructed, and the underlying mechanism was explored. Notably, cellular senescence, cell cycle, p53 signalling pathway, and Senescence-Associated Secretory Phenotype (SASP) are potential key signalling pathways regulated by BZBS that exert ageing effects ([114]Fig. 2A, [115]Table 3, and [116]Table S1). A total of 207 targets were regulated by BZBS, and 54 key targets were selected through network parameters, including CCND1(Cyclin D1), CDKN1A(p21), CDKN2A(p16), E2F1, and CDK4 ([117]Fig. 2B–[118]Table 4). Fig. 2. [119]Fig. 2 [120]Open in a new tab The network mechanism of anti-ageing effects exerted by BZBS. (A) Enrichment analysis of KEGG pathway for targets regulated by BZBS exerting anti-ageing effects. (B) Key targets for the anti-ageing effects of BZBS. Table 3. KEGG pathway enrichment analysis of targets involved in the anti-ageing effects exerted by BZBS (Top 10). ID Term Term PValue KEGG:04218 Cellular senescence 2.40743E-42 KEGG:04110 Cell cycle 6.37723E-39 R-HSA:1640170 Cell Cycle 2.71294E-33 R-HSA:2559583 Cellular Senescence 1.16843E-31 KEGG:05200 Pathways in cancer 6.67365E-31 R-HSA:2262752 Cellular responses to stress 7.70814E-30 R-HSA:8953897 Cellular responses to stimuli 1.42276E-29 KEGG:05166 Human T-cell leukaemia virus 1 infection 7.0644E-27 KEGG:05220 Chronic myeloid leukaemia 9.11453E-26 R-HSA:69,278 Cell Cycle, Mitotic 1.13862E-25 [121]Open in a new tab Table 4. Key targets for the anti-ageing effects of BZBS. Name Degree Betweenness Centrality Closeness Centrality TP53 45 0.148473494 0.894736842 MYC 40 0.082818149 0.822580645 CCND1 31 0.037333763 0.718309859 BRCA1 30 0.056091746 0.708333333 AKT1 29 0.057198656 0.698630137 CDKN1A 29 0.041174705 0.698630137 MDM2 26 0.020931669 0.671052632 EP300 26 0.018948606 0.671052632 CDKN2A 26 0.013542006 0.671052632 CCNA2 26 0.012443273 0.662337662 CDK2 26 0.010284623 0.662337662 CCNB1 25 0.01224249 0.662337662 ATM 25 0.020584459 0.653846154 CDK1 25 0.016958246 0.653846154 E2F1 24 0.006594027 0.653846154 HDAC1 23 0.0138728 0.64556962 CDK4 23 0.008746474 0.6375 CDKN1B 20 0.006003036 0.614457831 RELA 20 0.034427293 0.62195122 H2AX 20 0.011413751 0.607142857 CCNE1 20 0.00599456 0.614457831 RB1 20 0.012287583 0.614457831 SIRT1 19 0.022322659 0.614457831 CHEK1 17 0.004297014 0.593023256 CUL1 16 0.005339689 0.573033708 RAD51 16 0.00432618 0.579545455 PLK1 15 0.001621685 0.573033708 SKP1 14 0.003773555 0.554347826 IL6 13 0.013450835 0.566666667 MAPK1 12 0.003361689 0.554347826 SOX2 12 0.002753501 0.542553191 BMI1 12 0.003771435 0.554347826 SP1 12 0.003009748 0.548387097 PCNA 12 0.000603861 0.542553191 TERT 11 0.006928212 0.542553191 RBX1 11 0.00404508 0.536842105 MAPK3 10 0.006610808 0.536842105 MTOR 10 0.003519078 0.548387097 CDKN2B 10 0.000630685 0.53125 TGFB1 9 0.00732846 0.53125 PML 9 0.000174711 0.536842105 CXCL8 8 0.004435775 0.53125 SQSTM1 8 0.002383251 0.536842105 POU5F1 7 0.000259145 0.51 NANOG 7 0.00020915 0.504950495 UBE2D1 6 0.001201368 0.485714286 IL1A 6 0.001068499 0.414634146 LMNB1 5 0.001314857 0.490384615 SERPINE1 5 0.001374833 0.451327434 TERF2 4 0.000255213 0.447368421 LMNA 4 0.000479303 0.451327434 BAX 3 0 0.495145631 [122]Open in a new tab 3.2. Effects of BZBS on cell viability, p21 and p16 expression, and SA-β-gal staining in D-gal-induced senescent MSCs The experimental results are shown in [123]Fig. 3. Compared to the control group, the cell viability in the model group was significantly decreased (p < 0.01) ([124]Fig. 3A), p21 and p16 mRNA ([125]Fig. 3B and C) and SA-β-gal-positive ratio ([126]Fig. 3D and E) were markedly increased (P < 0.05, P < 0.01). Compared to the model group, the cell viability of the BZBS groups was significantly increased (p < 0.01), and p21 and p16 mRNA and SA-β-gal-positive ratio were decreased (P < 0.05, P < 0.01); p16 mRNA and SA-β-gal-positive ratio of NMN group were also reduced (p < 0.01). These results suggest that BZBS improves the viability of senescent MSCs, downregulates p21 and p16 expression, and reduces the number of senescent MSCs. Fig. 3. [127]Fig. 3 [128]Open in a new tab Effects of BZBS on cell viability, p21 and p16 expression, and SA-β-gal staining in D-gal-induced senescent MSCs. (A) MSCs samples with no less than 1 × 10^6 cells/well were collected from each group. Cell viability was measured using the CCK-8 kit, as described in the Methods section. Effects of BZBS on cell viability of D-gal-induced MSCs (n = 6); (B) and (C) MSCs samples with no less than 1 × 10^6 cells/well were collected from each group. Total RNA was collected, and qPCR was performed according to the method described in the Methods section. Effect of BZBS on the expressions of p21 and p16 in senescent MSCs (n = 3, n = 6); (D) and (E) According to the method described in the Methods section, the MSCs were fixed at room temperature, then stained with SA-β-gal, and finally recorded using an inverted microscope. Effect of BZBS on SA-β-gal-positive ratio in senescent MSCs and quantitative analysis of SA-β-gal-positive cells. (n = 4; Magnification: 200x). The results represent the mean ± SD. vs Control, *p < 0.05, **p < 0.01; vs Model, ^#p < 0.05, ^##p < 0.01. 3.3. Effect of BZBS on the differentiation potential of senescent MSCs The effect of BZBS on the adipogenic potential of senescent MSCs is shown in [129]Fig. 4A. Compared to the control group, the number of lipid droplets formed by the adipogenic differentiation of MSCs in the model group decreased significantly, and the staining became lighter. Compared to the model group, the number of lipid droplets formed in the BZBS and NMN groups increased significantly, and the staining became darker ([130]Fig. 4A). Fig. 4. [131]Fig. 4 [132]Open in a new tab Effect of BZBS on the differentiation potential of senescent MSCs. Each group of MSCs was fixed at room temperature and stained according to the method described in the Methods section. (A) Effect of BZBS on adipogenic potential in senescent MSCs. (Oil red O staining, Magnification: 200x). (B), (C), and (D) Effect of BZBS on osteogenic potential in senescent MSCs. (ALP staining, Magnification: 100×; Alizarin red staining, Magnification: 50x and 100x). (For interpretation of the references to colour in this figure legend, the