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INTRODUCTION
Diabetic kidney disease (DKD) is one of the most common microvascular complications of diabetes. According to the most recent global estimates, more than 451 million adults worldwide have been diagnosed with diabetes, and about one-third of these patients will eventually develop DKD [1]. Renal impairment from DKD is typically irreversible, and the disease may rapidly progress to end-stage renal disease (ESRD) without timely intervention. In China, there are approximately 1.1 million DKD patients, among whom 36.4% require dialysis treatment [2]. Renal interstitial fibrosis (RIF), a key pathological feature of ESRD, is a dynamic and evolving process [3]. The process is driven by multiple factors, such as injury, inflammation, oxidative stress, and immune responses [4-6]. These factors contribute to the disruption of renal structural and functional units, disrupting the balance between the synthesis and degradation of extracellular matrix (ECM), and resulting in abnormal deposition in the interstitial area [7,8]. Currently, for RIF caused by DKD, in addition to glycemic and lipid control and the use of ACEI/ARB drugs for supportive therapy [9], several new drugs with renal protective effects have been introduced into clinical practice [10]. These include sodium-glucose cotransporter 2 inhibitors glucagon-like peptide-1 receptor agonists, and non-steroidal mineralocorticoid receptor antagonists [11-13].
Despite the promise of emerging therapeutic approaches, challenges remain in addressing renal function decline and fibrosis progression in the mid-to-late stages of DKD. Traditional Chinese medicine (TCM) offers unique advantages in protecting renal function and delaying the progression of renal fibrosis due to its multi-component, multi-pathway, and multi-target mechanisms [14,15]. Therefore, leveraging these benefits is crucial for developing effective treatments for improving renal function and alleviating DKD-induced RIF. Xuefu Zhuyu decoction (XFZY) is one of the most renowned prescriptions with broad therapeutic applications, which is firstly recorded in Yilin Gaicuo by the doctor Qingren Wang in the Qing dynasty. XFZY has been demonstrated to have efficacy and safety in treating DKD [16,17]. However, the mechanisms underlying its renal protective effects against RIF require further investigation.
Network pharmacology and molecular docking are potent methodologies for identifying the bioactive components and elucidating the mechanisms of action of TCM formulations [18]. Network pharmacology screens and predicts drug and disease target proteins and genes, constructing multi-component, multi-target interaction networks using biomolecular networks [19,20]. Molecular docking simulates the interactions between bioactive compounds and protein receptors, predicts binding affinities, and explores molecular interactions between XFZY and its potential targets. In this study, the components of XFZY were first analyzed using ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS) and screened against public databases. Network pharmacology and molecular docking techniques were then employed to elucidate the potential mechanisms of XFZY in treating DKD-induced RIF. Finally, in vivo and in vitro experiments were conducted to validate the therapeutic mechanisms of XFZY.
METHODS
Composition and preparation of XFZY
Preparation method of XFZY: XFZY is created for the syndrome of Qi stagnation and blood stasis, and consists of Prunus persica (L.) Batsch, Carthamus tinctorius L., Angelica sinensis (Oliv.) Diels, Rehmannia glutinosa Libosch., Ligusticum chuanxiong Hort., Paeonia lactiflora Pall., Achyranthes bidentata Bl., Citrus aurantium L., Platycodon grandiflorum (Jacq.) A.DC., Bupleurum chinense DC. and Glycyrrhiza uralensis Fisch. All herbs were obtained from Dongzhimen Hospital, Beijing University of Chinese Medicine. The herbs were soaked in ten times their volume of water for one hour, boiled for forty minutes, and filtered. The filtrates were concentrated to produce a XFZY decoction at a concentration of 1.0 g/ml.
Mass spectrometry analysis
Preparation of test solution: A 0.2 g sample of the XFZY concentrate was mixed with 5 ml of 50% methanol aqueous solution and subjected to ultrasonic extraction at 40°C. After standing, the mixture was centrifuged at 13,000 r/min for 10 min. The supernatant was collected and filtered through a 0.22 μm microporous membrane to obtain the XFZY filtrate. A blank sample was prepared under identical conditions.
UPLC-Q-TOF-MS conditions: Chromatographic conditions were set using a Shimadzu LC-30A system. A Waters ACQUITY UPLC HSS T3 C18 column (2.1 × 100 mm, 1.7 μm) was employed. The mobile phase consisted of 0.1% formic acid in water (A) and acetonitrile (B) with a gradient elution profile: 0–4 min, 5% B; 4–15 min, 5%–30% B; 15–35 min, 30%–95% B; 35–37 min, 95% B. The column temperature was maintained at 45°C. The flow rate was 0.4 ml/min, and the injection volume was 4 μl.
Mass spectrometry conditions: Electrospray ionization was utilized in both positive and negative ion modes with an ion scan range set to m/z 50–1,500. The declustering potential was 100 V, and collision energy was 35 eV (negative ion mode –35 eV). The capillary voltage was 5,500 V for positive mode and 4,500 V for negative mode. The ion source temperature was maintained at 500°C. Nitrogen served as the nebulizing gas at 50 PSI, auxiliary gas at 50 PSI, and curtain gas at 40 PSI. Data were acquired using information-dependent acquisition, dynamic background subtraction, and high sensitivity mode. The product ion scan range was set to m/z 50–1,000, consistent with TOF-MS scan mode parameters.
Data acquisition and processing: Data acquisition and processing were performed using SCIEX OS. Initially, data were matched against the compound database based on criteria such as mass accuracy (mass error < ±5 ppm), retention time, and isotopic distribution to identify highly matched compounds. The mass spectrometry data were then compared with the Natural Products HR-MS/MS Spectral Library 1.0. Preliminary screening of compounds was performed by integrating each chromatographic peak and further identified using MS1 and MS2 data. For compounds not included in the database, identification was based on MS/MS fragmentation patterns and relevant literature.
Network pharmacology analysis
Screening of bioactive compounds of XFZY and prediction of their potential targets: Bioactive compounds identified from the UPLC-Q-TOF-MS analysis of XFZY were screened using the TCMSP (https://tcmspw.com/tcmsp.php) and SymMap (http://www.symmap.org/). Screening criteria included oral bioavailability ≥ 30% and drug-likeness ≥ 0.18. The identified bioactive compounds were then input into the SwissTargetPrediction (http://swisstargetprediction.ch/) to predict potential drug targets. UniProt (https://www.uniprot.org/) was used to annotate the target proteins of XFZY.
Prediction of disease targets for DKD-induced RIF: The keywords "Diabetic kidney disease" and "Diabetic nephropathy" were used to search for DKD, and "Renal interstitial fibrosis" and "Renal fibrosis" were used for RIF in databases such as OMIM (https://www.omim.org/), DrugBank (https://go.drugbank.com/), GeneCards (https://www.genecards.org/), DisGeNET (https://www.disgenet.org/), and the Therapeutic Target Database (https://db.idrblab.net/ttd/). Disease targets retrieved were curated and deduplicated using UniProt. The intersection of DKD and RIF targets was then obtained to identify disease targets for DKD-induced RIF. A Venn diagram was generated using Bioinformatics (http://www.bioinformatics.com.cn/) to identify common targets between the potential drug targets of XFZY and the disease targets of DKD-induced RIF.
Construction of the "Formula-Bioactive Compound-Target" network and protein-protein interaction (PPI) network: The identified bioactive compounds of XFZY and their common targets were imported into Cytoscape (Version 3.8.0) to construct a "Formula-Bioactive Compound-Target" network. PPI analysis was then conducted using the STRING (https://cn.string-db.org/). The common targets of XFZY with DKD and RIF were imported into STRING with the parameters: species "Homo sapiens" and a medium confidence threshold of 0.4. Unconnected nodes were removed, and the data were imported into Cytoscape for topological analysis and visualization. The CytoHubba plugin identified hub genes in the PPI network, employing the Maximal Clique Centrality algorithm to select the top 10 core genes.
Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analysis: GO enrichment analysis, encompassing biological process (BP), cellular component (CC), and molecular function (MF), along with KEGG pathway enrichment analysis, was conducted using the Metascape (https://metascape.org/). Common targets were uploaded, with the species set to "Homo sapiens," and analyzed in "Custom Analysis" mode. The top 20 GO and KEGG enrichment results were visualized using a bioinformatics plotting tool, and a Sankey diagram was generated to illustrate the KEGG pathways and their associated targets.
Molecular docking: The two-dimensional structures of the bioactive compounds of XFZY were retrieved from PubChem (https://pubchem.ncbi.nlm.nih.gov/) in sdf format and converted to three-dimensional (3D) structures using OpenBabel. Hydrogen atoms were added and torsion angles set using AutoDockTools. The 3D structures of the target proteins were obtained from the PDB (https://www.rcsb.org/) and preprocessed with PyMOL and AutoDockTools. Ligands and receptors were then subjected to semi-flexible docking using AutoDockTools. Docking results were visualized as heat maps, and the lowest binding energy configurations were further visualized with PyMOL.
Experimental validation
Antibody and regents: Atg5 (12994) was purchased from Cell Signaling Technology. AMPK (ab32047), p-AMPK (ab133448), p-mTOR (ab109268), LC3 (ab192890), and p62 (ab109012) were purchased from Abcam. Collagen Type III (COL-III) (22734-1-AP), mTOR (66888-1-Ig), ULK1 (20986-1-AP), p-ULK1 (80218-1-RR), Beclin1 (11306-1-AP), transforming growth factor-β (TGF-β) (21898-1-AP), α-smooth muscle actin (α-SMA) (14395-1-AP), neural cadherin (N-cadherin) (22018-1-AP) were purchased from Poteintech.
β2-microglobulin (β2-MG) (EL-M2411), kidney injury molecule-1 (KIM-1) (MSEL-M0009), neutrophil gelatinase-associated lipocalin (NGAL) (E-EL-M0828), liver-type fatty acid-binding protein (L-FABP) (E-EL-M3050) ELISA (enzyme-linked immunosorbent assay) kits were purchased from Elabscience.
Animal model establishment and therapeutic interventions: Forty male C57BL/6 mice (6 weeks old, weighing 20 ± 2 g) were purchased from Beijing Vital River Laboratory Animal Technology Co., Ltd. with certificate number SCXK (Jing) 2021-0011. The mice were housed in the SPF-grade Animal Experiment Center of Beijing University of Chinese Medicine under standard conditions (temperature: 24°C–26°C, humidity: 35%–45%, 12-h light/dark cycle, adequate ventilation) with free access to food and water. The study was approved by the Animal Ethics Committee of Beijing University of Chinese Medicine (No. BUCM-2023042003-2110) and conducted in accordance with the Guide for the Care and Use of Laboratory Animals.
After a 7-day acclimatization period, mice were randomly assigned to a control group (n = 10) and a high-fat diet (HFD) group (n = 30). The control group received a standard diet, whereas the HFD group was fed a HFD for 4 weeks. Subsequently, the mice were fasted for 12 h and injected intraperitoneally with 50 mg/kg streptozotocin (STZ) (Sigma-Aldrich, S0130) dissolved in citrate buffer (0.1 M, pH 4.5) for 5 consecutive days. Control mice received the same volume of citrate buffer. Blood glucose levels were measured from the tail vein after 7 days, and mice with glucose levels > 16.7 mmol/L were considered diabetic [21]. These mice were then randomly assigned to three groups (n = 10 per group): a model group (MOD), a semaglutide group (SEMA), and a XFZY group (XFZY). Three days after modeling, the XFZY group was administered 15.42 g/kg XFZY via gavage once daily (drug administration was adjusted for body weight). The control and model groups received an equal volume of saline via gavage. The SEMA group received 40 μg/kg of semaglutide (Novo Nordisk, SJ20210014) subcutaneously every third day. All groups were treated continuously for 12 weeks. The control group was maintained on a standard diet, while the other groups were kept on a HFD.
Determination of renal index: Prior to tissue collection, each mouse was weighed. The right kidney was excised, the renal capsule was removed, and the kidney was rinsed with saline. After blotting the kidney dry with filter paper, weighed, and the kidney-to-body weight ratio was calculated.
Blood glucose and urine protein quantification: Blood glucose was measured from the tail vein using a glucometer before treatment and at weeks 4, 8, and 12 post-treatment. Urine was collected over 24 h in metabolic cages, and total urine volume was recorded. Urine samples were centrifuged at 4°C for 5 min at 1,800 rpm, and the supernatant was collected and analyzed for protein levels using a urine protein assay kit (C035, Jiancheng Biotech Co., Ltd.).
Renal function testing: After the final administration, mice were fasted for 12 h and anesthetized with 1% sodium pentobarbital via intraperitoneal injection. Blood was collected via retro-orbital bleeding. The samples were centrifuged at 4°C and 3,000 rpm for 10 min to obtain serum. Serum creatinine (Scr) and blood urea nitrogen (BUN) levels were measured using assay kits (Cat# C013, C011, Jiancheng Biotech Co., Ltd.).
Renal histopathological examination: The kidneys were sectioned transversely and fixed in 4% paraformaldehyde for 48 h. Following dehydration with ethanol and clearing with xylene, tissues were embedded in paraffin and sectioned at 3 μm. Sections were stained with hematoxylin-eosin (HE), periodic acid-Schiff (PAS), periodic acid-silver methenamine (PASM) and Masson's trichrome according to the manufacturer's instructions. Tissue structures were examined and photographed under a light microscope.
ELISA assay: Urine samples were collected from each group of mice at baseline and after treatment. The levels of β2-MG, KIM-1, NGAL, L-FABP in the urine were measured using ELISA kits following the manufacturer's instructions.
Immunohistochemical staining: Paraffin sections were baked at 60°C and deparaffinized in xylene. Antigen retrieval was performed using EDTA antigen retrieval buffer (pH 9.0) in a 95°C water bath. Sections were then treated with peroxidase blocking reagent to reduce background staining, followed by incubation with primary TGF-β, α-SMA, N-cadherin antibody overnight. The next day, sections were incubated with secondary antibody, developed with DAB, counterstained with hematoxylin, differentiated with acid alcohol, and rinsed. Sections were dehydrated through a graded ethanol series and cleared in xylene. Slides were mounted with neutral resin, and images were captured. Positive expression of markers was quantified using ImageJ software (National Institutes of Health).
Immunofluorescence staining: Kidney tissues were embedded in OCT compound and cryosectioned at 20 μm thickness. After sections were equilibrated to room temperature, they were fixed in cold acetone and washed with PBS. Sections were blocked with goat serum and incubated overnight at 4°C with primary antibody against p62. The following day, sections were incubated with fluorescent secondary antibody in the dark, counterstained with DAPI, and mounted with anti-fade reagent. Fluorescence images were captured using a fluorescence microscope, and the average fluorescence intensity was analyzed using ImageJ software.
Preparation of drug-treated serum: Twenty Sprague-Dawley rats were acclimated for one week and then randomly divided into two groups. The experimental group (n = 10) received the drug-containing serum via gavage according to an equivalent dose conversion coefficient, while the control group (n = 10) received an equal volume of saline via gavage. Both groups were treated daily for 7 days. One hour after the final gavage, the rats were anesthetized, and blood samples were collected from the abdominal aorta under sterile conditions. Blood samples were allowed to clot and then centrifuged at 3,000 rpm for 10 min at 4°C. The serum was collected, inactivated at 56°C for 30 min to inactivate complement, filtered through a 0.22 μm microporous membrane to remove bacteria, aliquoted, and stored at –80°C.
Cell culture: HK-2 cells (a gift from Professor Baoli Liu, Beijing Traditional Chinese Medicine Hospital) were cultured in DMEM/F12 (1:1) supplemented with 10% fetal bovine serum, 100 U/ml penicillin, 100 μg/ml streptomycin, and 0.25 μg/ml amphotericin B at 37°C in a humidified atmosphere with 5% CO2. The culture medium was refreshed every 48 h, and cells were passaged at 80% confluence to maintain optimal growth conditions for subsequent experiments.
Cell viability assay: HK-2 cells were seeded into 96-well plates at a density of 1 × 104 cells per well. After adherence, the cells were treated with advanced glycation end-products bovine serum albumin (AGE-BSA) at concentrations of 50, 100, 200, or 300 μg/ml for 24 and 48 h. After treatment, 10% CCK-8 solution was added to each well in the dark and incubated for an additional 3 h. Absorbance at 450 nm was measured using a microplate reader to determine cell viability. This data was used to identify the optimal concentration and incubation time of AGE-BSA. After determining the optimal model conditions, cells were seeded in 96-well plates under the same conditions and treated with media containing 5%, 10%, 15%, 20% and 25% XFZY-containing serum for 24 and 48 h. Cell viability was assessed using the CCK-8 assay to determine the optimal concentration and intervention time of XFZY for treating the DKD cell model. Following the experimental findings, cells were allocated into four groups: control, AGEs, AGEs + 10% XFZY, and AGEs + 15% XFZY.
Western blot analysis: Kidney tissue samples from each group were homogenized, and cells were collected. Both tissues and cells were lysed in RIPA buffer containing protease and phosphatase inhibitors, followed by centrifugation to extract total protein. Protein concentration was measured using a BCA assay kit (Applygen, P1511), and the proteins were denatured by heating. Protein samples (10 μl per well) were separated by SDS-PAGE and transferred to nitrocellulose membranes. The membrane was blocked with 5% non-fat milk, and incubated overnight at 4°C with primary antibodies against COL-III, AMPK, p-AMPK, mTOR, p-mTO, ULK1, p-ULK1, Atg5, Beclin1, LC3, and p62. The membrane was then incubated with HRP-conjugated secondary antibodies and washed with TBST. Bands were visualized using an ECL detection reagent and captured with a chemiluminescence imaging system. Image analysis was performed using ImageJ software.
Data analysis
Statistical analyses were performed using SPSS 26.0 software (IBM). Data are presented as means ± SD. Normality tests were conducted before analysis. For comparisons between two groups, independent samples t-tests were applied for normally distributed data, while the Mann–Whitney U-test was used for non-normally distributed data. For comparisons among multiple groups, one-way analysis of variance (ANOVA) was used for normally distributed data, followed by Tukey’s or Bonferroni post-hoc tests when significant differences were observed. For non-normally distributed data, the Kruskal–Wallis test was employed, followed by pairwise comparisons with Bonferroni correction if significant differences were detected. A p-value < 0.05 was considered statistically significant.
RESULTS
Network pharmacology analysis of XFZY
The Swiss Target Prediction was employed to predict potential targets for the seven bioactive compounds of XFZY, resulting in 123 targets post deduplication. By merging disease-associated targets from GeneCards, DisGeNET, and OMIM, and eliminating redundancies, 792 DKD targets and 1,490 RIF targets were identified. The intersection of predicted drug targets with disease-associated targets resulted in 61 common targets (Fig. 2A), and constructed a " Formula-Bioactive Compound-Target" network (Fig. 2B). The PPI network was constructed via STRING, consisting of 62 nodes and 671 edges, and visualized using Cytoscape (Fig. 2C). Further analysis of the PPI network using the CytoHubba plugin identified 10 hub genes, including AKT1, EGFR, SRC, MTOR, ESR1, CCND1, TNF, ERBB2, MMP9, and ULK1 (Fig. 2D), providing critical targets for pathway and molecular docking analyses (Fig. 2D).
GO and KEGG enrichment analyses of the 61 common targets were conducted using the Metascape. The GO analysis identified 447 BP, including negative regulation of apoptotic process, protein autophosphorylation, inflammatory response, and positive regulation of phosphorylation. It also identified 41 CC, including plasma membrane, receptor complex, endoplasmic reticulum, and lysosome. Additionally, 98 MF were identified, including identical protein binding, protein homodimerization activity, oxidoreductase activity, and insulin receptor substrate binding. The top 20 results in each category are presented (Fig. 3A-C). KEGG analysis identified 138 pathways, including the PI3K/AKT signaling pathway, AMPK signaling pathway, EGFR tyrosine kinase inhibitor resistance, endocrine resistance, and AGE-RAGE signaling pathway in diabetic complications. The top 20 pathways are presented (Fig. 3D). Subsequently, 10 relevant pathways and their targets from the KEGG results were visualized (Fig. 3E) to elucidate the potential mechanisms of XFZY in treating DKD-induced RIF.
Integrating mass spectrometry data with network pharmacology, we conducted molecular docking to evaluate the interactions between principal AMPK pathway targets (AMPK, mTOR, ULK1) and XFZY bioactive compounds (Baicalin, Linarin, Ellagic acid, Quercetin, Luteolin, Isoimperatorin, Formononetin). The results indicated that the selected bioactive compounds exhibited high binding affinities to the primary targets, as visualized in the heatmap (Fig. 4A). The top three docking targets with binding energies below –5 KJ/mol with the primary targets were visualized for detailed analysis (Fig. 4B, Table 2).
Renal protective effects of XFZY on DKD model mice
By employing a HFD combined with intraperitoneal injection of STZ, we established the disease model. There were no significant differences in blood glucose, renal function, or urine protein excretion between the groups at baseline. Following the modeling procedure, significant increases in blood glucose levels and 24-h urine protein were observed in the model group, SEMA group, and XFZY group, validating the effectiveness of the model. After treatment, the levels of creatinine, BUN, renal index, and urine protein in the SEMA and XFZY groups were significantly reduced compared to the model group (Fig. 5), indicating that XFZY could improve renal function. Among them, a significant reduction in proteinuria was observed after 8 weeks of treatment with XFZY, compared to the untreated group. Despite the administration of XFZY, no significant effect on blood glucose levels was recorded compared to the model group.
XFZY alleviates renal pathological damage in DKD mice
To investigate the renal protective effects, we performed histopathological analysis on kidney tissues from mice treated with different interventions (Fig. 6A). HE staining revealed that the kidney tissues in the control group exhibited regular morphology with intact and neatly arranged glomeruli and renal tubules. In contrast, the model group displayed significant pathological changes, including glomerular hypertrophy, capillary loop proliferation, Bowman’s capsule dilatation, tubular lumen expansion. PAS and PASM staining revealed no thickening of the basement membranes and no mesangial proliferation in the control group, the mesangial region in the model group was significantly widened, the mesangial matrix was proliferated and the Glomerular basement membrane was thickened. However, the model group exhibited glomerular capsular adhesions, homogenous thickening of glomerular basement membranes, and proliferation of mesangial cells and matrix. Masson's Trichrome staining indicated collagen fiber proliferation in the renal interstitium, reduced and absent brush borders of tubular epithelial cells, focal glomerulosclerosis in the model group, while no significant collagen deposition was observed in the control group. Following intervention with XFZY and SEMA, the renal pathological damage in DKD mice improved compared to the model group (Fig. 6B). Additionally, following treatment with XFZY and SEMA, renal COL-III expression levels were significantly lower in the intervention groups compared to the control group (Fig. 6C, D).
Protective role of XFZY in alleviating DKD-induced RIF
Tubulointerstitial damage is a critical driver of RIF and plays a pivotal role in the progression of chronic kidney disease [22,23]. Damage to tubular epithelial cells impairs the reabsorption of small molecular proteins such as β2-MG, resulting in increased urinary excretion. The expression of tubulointerstitial damage markers, such as KIM-1, NGAL, and L-FABP, significantly increases when renal tubules are subjected to damaging stimuli, serving as sensitive indicators of renal injury. ELISA results demonstrated a significant decrease in the levels of tubular injury markers in the SEMA and XFZY treatment groups compared to the DKD model group (Fig. 7A-D). Additionally, biomarkers at different stages of the RIF process were examined, including the RIF inducer TGF-β, the epithelial-mesenchymal transition (EMT) marker N-cadherin, the myofibroblast marker α-SMA. The expressions of TGF-β, α-SMA, and N-cadherin were significantly increased in the model group compared to the control group. However, following SE and XFZY intervention, the trend of RIF was reversed (Fig. 7E-H).
Construction of the cell model and drug intervention conditions
CCK-8 assay was performed to determine the AGEs modeling concentration and SXZY treatment concentration of HK-2 cells. Under the same intervention time (24 h or 48 h), 5%, 10%, 15% and 20% XFZY had no significant effect on the survival rate of HK-2 cells. However, a further increase in concentration led to a decrease in HK-2 cell activity, and its toxicity became obvious (Fig. 8A). Compared with the control group, the cell viability of all AGEs treatment groups was significantly reduced, and the effect of 200 μg/ml AGEs treatment for 48 h was the most obvious (Fig. 8B). Therefore, the optimal construction condition of DKD cell model in this study was that HK-2 cells were treated with 200 μg/ml AGEs for 48 h. Compared with AGEs treatment group, 10% and 15% XFZY significantly increased the survival rate of HK-2 cells, while 20% XFZY intervention significantly decreased the survival rate of HK-2 cells (Fig. 8C). Therefore, we used 10% and 15% XFZY as effective concentrations for subsequent cell experiments.
Modulation of the AMPK/mTOR/ULK1 pathway by XFZY
Based on the core pathways and targets predicted by network pharmacology, we propose that the therapeutic effects of XFZY on DKD-induced RIF are exerted through modulation of the AMPK/mTOR/ULK1 signaling pathway. To validate this hypothesis, we conducted in vivo (Fig. 9A–D) and in vitro (Fig. 9E–H) experiments using Western blotting to detect the expression levels of AMPK, p-AMPK, mTOR, p-mTOR, ULK1, and p-ULK1 proteins. Compared to the control group, the model group exhibited increased p-mTOR expression and decreased p-AMPK and p-ULK1 expressions. Following intervention with XFZY and SEMA, compared to the model group, p-mTOR expression was decreased, while p-AMPK and p-ULK1 expressions were increased.
Regulation of downstream mechanisms of the AMPK/mTOR/ULK1 pathway by XFZY
The AMPK signaling pathway, a crucial mechanism for cellular homeostasis, triggers autophagy through a dual mechanism by directly activating ULK1 and inhibiting mTOR's suppressive effect on ULK1. To confirm the aforementioned mechanism of XFZY, we utilized Western blotting to detect the expression levels of Atg5, Beclin1, LC3, and p62 in vivo (Fig. 10A–E) and in vitro (Fig. 10F–J). Compared to the control group, the model group showed no significant difference in Atg5 and Beclin1 expression, while LC3 and p62 expression levels were significantly increased. After intervention with SEMA and XFZY, LC3 and p62 expression levels decreased. Furthermore, immunofluorescence was used to verify the expression of LC3 and p62 in renal tissues across groups (Fig. 10K), and the results were consistent with those obtained from Western blotting (Fig. 10L).
DISSCUSSION
DKD has emerged as the leading cause of ESRD globally. DKD affects all types of intrinsic kidney cells, leading to glomerular mesangial cell proliferation, ECM deposition, glomerulosclerosis, tubular injury, and RIF [24]. Tubulointerstitial damage in DKD shows a stronger correlation with renal insufficiency compared to glomerular damage, with tubular lesions preceding glomerular injury during the initial phases of the disease [25,26]. Progressive renal fibrosis, characterized by compensatory tubular hypertrophy, tubular atrophy, and ECM deposition, is a critical determinant driving chronic renal failure and ESRD [27]. Therefore, developing therapeutic interventions to slow the progression of RIF is imperative for the effective management of DKD. Components of XFZY, including Astragalus [28,29], Hirudo [30], Curcuma [31], and Achyranthes [32], exhibit nephroprotective effects by modulating metabolic pathways, protecting intrinsic kidney cells, regulating autophagy, inhibiting inflammation and oxidative stress, and maintaining hemodynamic stability. Consequently, we administered a HFD combined with STZ injections to establish the disease model [33], aiming to investigate the therapeutic effects of XFZY on DKD-induced RIF and to validate its potential therapeutic mechanisms.
A meta-analysis [17] indicates that XFZY significantly reduces proteinuria in patients with DKD, improves renal function, enhances glucose and lipid metabolism, and is associated with a low incidence of adverse events. In the present study, the significant increase in proteinuria and renal dysfunction in the model mice confirmed the successful establishment of the renal disease model. Consistent with previous reports, treatment with SEMA and XFZY significantly reduced Scr and BUN levels in the model mice, indicating improved renal function. Furthermore, in vitro experiments demonstrated that the treatment did not induce cytotoxicity in HK-2 cells, suggesting a favorable safety profile. Histopathological analysis revealed that treatments with SEMA and XFZY ameliorated pathological changes, including RIF, tubular injury, basement membrane thickening, and glomerular hypertrophy. Blood glucose monitoring revealed that XFZY could mitigate the progression of DKD without altering blood glucose levels. Monitoring 24-h urine protein levels revealed that both the SE and XFZY groups exhibited reduced proteinuria, while the effect in the XFZY group became significant only after the 8th week. Thus, XFZY may provide nephroprotective effects through the tubulointerstitial pathway.
The tubular interstitium constitutes more than 90% of the kidney volume, serving a crucial role in reabsorption and secretion. β2-MG is freely filtered by the glomerulus and almost entirely reabsorbed and catabolized by proximal tubules [34]. Urinary β2-MG levels significantly increase with tubular injury, serving as a reliable biomarker for detecting tubular reabsorption impairment. KIM-1, expressed by tubular epithelial cells, rises significantly in injured tubules and serves as a specific urinary biomarker for renal injury and fibrosis [35]. NGAL is a sensitive marker for early DKD-induced renal injury, reflecting decreased reabsorption and increased secretion due to tubular epithelial cell damage [36,37]. L-FABP, involved in fatty acid transport and metabolism, is expressed in proximal tubular cells and increases in urine upon tubulointerstitial injury, serving as an independent risk factor for DKD progression [38,39]. Our findings demonstrated that the interventions effectively reduced urinary β2-MG, KIM-1, NGAL, and L-FABP levels, indicating the nephroprotective potential of XFZY against DKD-induced renal injury.
TGF-β1 drives renal fibrosis through the SMAD signaling pathway [40], facilitating myofibroblast activation and excessive ECM production [41]. Pro-inflammatory and pro-fibrotic cytokines stimulate tubular epithelial cells, exacerbating fibroblast activation and EMT. EMT involves decreased expression of cell adhesion molecules, characterized by the 'cadherin switch,' which refers to the downregulation of E-cadherin and upregulation of N-cadherin [42]. These processes induce an imbalance between ECM synthesis and degradation, resulting in excessive ECM accumulation and driving RIF. EMT contributes to the activation of fibroblasts into myofibroblasts, characterized by α-SMA expression. Fibronectin, synthesized and secreted by myofibroblasts, forms an ECM scaffold and promotes collagen fiber deposition [43,44]. This research demonstrates that the XFZY significantly reduces the expression of TGF-β, N-cadherin, α-SMA, and COL-III. The reduction of pro-fibrotic factors, inhibition of EMT, and attenuation of collagen levels and ECM accumulation contribute to its anti-fibrotic effects. However, the underlying mechanisms of XFZY remain unclear. This research employs a network pharmacology approach, integrating mass spectrometry and experimental validation to elucidate the mechanisms and identify targets of XFZY for treating DKD-induced RIF. By integrating public database resources with mass spectrometry, we identified seven key bioactive components in XFZY, including Betulinic acid, Baicalin, Isoimperatorin, and Formononetin. Baicalin has been reported to ameliorate DKD-induced fibrosis by reducing oxidative stress and inflammation and enhancing autophagic flux, with its mechanisms involving the AMPK/mTOR and PI3K/Akt pathways. Ellagic acid exerts anti-fibrotic effects by reducing the accumulation of AGEs, suppressing inflammation and ECM deposition, and alleviating EMT, potentially through the PI3K/Akt/mTOR pathway. Quercetin promotes mitophagy via the AMPK signaling pathway, restores lysosomal function, inhibits the TGF-β signaling pathway, and mitigates tubular sclerosis. Luteolin enhances autophagic activity by activating AMPK and inhibits the TGF-β/SMAD pathway to improve EMT and renal fibrosis. Benzoic acid reduces oxidative stress, improves insulin resistance, and enhances autophagosome-lysosome fusion, likely acting through the AMPK/mTOR/ULK1 pathway. Network pharmacology analysis also indicates that XFZY may exert therapeutic effects through the AMPK signaling pathway, involving the critical proteins AMPK, mTOR, and ULK1. Molecular docking indicated that several bioactive components generally exhibit strong binding affinity towards AMPK, mTOR, and ULK1. Experimental results demonstrated that XFZY intervention significantly increased p-AMPK and p-ULK1 levels while decreasing p-mTOR levels, indicating its potential to delay DKD-induced RIF through the AMPK/mTOR/ULK1 pathway.
The AMPK/mTOR/ULK1 signaling pathway is crucial for regulating cellular metabolism and maintaining energy homeostasis, serving as a critical mechanism for autophagy regulation [45]. GO enrichment analysis further underscored the connection by highlighting key components and processes related to autophagy regulation. CC analysis identified lysosomes, mitochondria, and the endoplasmic reticulum as critical organelles involved in autophagy. BP analysis emphasized events such as protein phosphorylation and apoptosis regulation. MF analysis revealed the crucial role of ATP binding and kinase activity in the energy-dependent processes of autophagy. These findings underscore the essential contribution of the AMPK/mTOR/ULK1 pathway and its associated autophagic phenotypes in elucidating how XFZY modulates autophagy to exert its therapeutic effects. AMPK, an evolutionarily conserved serine/threonine protein kinase, activates ULK1 through phosphorylation at Ser555 and Ser777, promoting autophagy, while mTOR inhibits autophagy by phosphorylating ULK1 at Ser757 [46,47]. Additionally, inhibition of mTORC1 by AMPK through multiple mechanisms regulates autophagy [48,49]. The ULK1 complex, composed of ULK1, FIP200, and ATG13, is vital for inducing autophagosome formation [50] and regulating substrate recognition, autophagosome-lysosome fusion, and lysosomal degradation through phosphorylation and ubiquitination [51-53]. Autophagy acts as a protective mechanism in renal tubular cells by removing dysfunctional organelles and proteins, reducing injury and maintaining cellular homeostasis [54-56]. Renal tubular cells rely on autophagy to clear damaged mitochondria and lysosomes, eliminating reactive oxygen species-induced oxidative stress and inflammation [54,57,58], thereby mitigating RIF. In DKD, impaired autophagy in renal proximal tubules promotes collagen deposition and ECM accumulation [55]. In this research, Western blotting was performed to measure key markers at various stages of the autophagy process, including Beclin1, ATG5, LC3, and p62. Compared to the control group, the model group showed no significant reduction in Beclin1 and ATG5 expression, whereas LC3 and p62 expression were significantly upregulated. These negative trends were reversed following intervention with SEMA and XFZY, demonstrating the efficacy of these treatments in modulating autophagic processes. LC3 is a marker for the fusion of autophagosomes and lysosomes [59]. p62 links the autophagy pathway and the ubiquitin-proteasome system [60,61], facilitating the degradation of damaged organelles and proteins [62]. The concurrent increase in LC3-II and p62 levels indicates an autophagic flux blockade, resulting in the impaired degradation of autophagosomes [63,64]. Defective autophagy leads to the accumulation of p62-positive aggregates, contributing to fibrotic progression in renal tissues [65-67]. Autophagic degradation of p62 and ubiquitinated proteins mitigates renal fibrosis, highlighting the antifibrotic effects of effective autophagic clearance through the regulation of autophagic flux [68,69]. Immunofluorescence staining demonstrated that the intervention reduced p62 expression and enhanced autophagic degradation of substrates. Overall, our findings suggest that XFZY can alleviate DKD-induced RIF by modulating the AMPK signaling pathway to regulate autophagic processes. However, our study has some limitations. The therapeutic effects of XFZY on DKD-induced RIF involve multiple bioactive compounds and targets, necessitating further investigation to explore the underlying mechanisms.
This research employed network pharmacology predictions and experimental validation to investigate the therapeutic potential of XFZY. Our results indicate that XFZY could regulate multiple signaling pathways, including the AMPK/mTOR/ULK1 pathway, to alleviate DKD-induced RIF by modulating autophagy. These findings provide insights into its potential as a therapeutic agent and strategy.
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