Abstract

   Renal tubular epithelial cell injury is an important manifestation of
   chronic kidney disease (CKD). This study aims to explore the mechanism
   of astragaloside IV (AS-IV) in the treatment of UII-mediated renal
   tubular epithelial cell injury by integrating network pharmacology and
   experimental validation. BATMAN, SwissTarget-Prediction and ETCM data
   bases were used to screen the target proteins of AS-IV. DAVID software
   was then used to perform GO and KEGG enrichment analysis on these
   target genes, and STRING and cytoscape were used to construct a protein
   interaction network. Molecular docking analysis was performed on key
   genes. The CCK8 assay was applied to detect the cell viability. ELISA,
   laser confocal, RT-PCR, and Western blot methods were used to detect
   the expression of cell pathway indicators and inflammatory factors in
   each group. Network pharmacology analysis found that the cAMP signaling
   pathway is one of the most important pathways for AS-IV to treat CKD.
   Molecular docking results showed that the AS-IV can be well embedded in
   the active pockets of target proteins, such as ALB, VEGFA, AKT1, ROCK1,
   and DRD2. The cAMP content and expression of GPR-14, PKA, NF-κB, and
   TGF-β in the UII group and the UII+cAMP agonist group (Forskolin) were
   all higher than those in the control group (P<0.05). In the
   UII+SB-611812 group, UII+AS-IV group, UII+losartan group, and UII+cAMP
   inhibitor (H89) group, the cAMP content and the expressions of GPR-14,
   PKA, NF-κB and TGF-β were all decreased compared with those in the UII
   group (P<0.05). In conclusion, AS-IV may improve UII-mediated renal
   tubular epithelial cell damage by down-regulating the cAMP/PKA
   signaling pathway.

1. Introduction

   Chronic kidney disease (CKD) is a condition characterized by a gradual
   loss of kidney function over a period of months to years. The primary
   causes include diabetes and hypertension. Patients may experience
   symptoms such as acidosis, anemia, nerve damage, osteoporosis, and
   progression of atherosclerosis. Common symptoms include nocturia
   (increased urination at night), fatigue, nausea, itching, muscle cramps
   and spasms, loss of appetite, confusion, difficulty breathing, and
   edema, particularly in the legs. Diagnosis can be confirmed through
   blood and urine tests. Renal tubular epithelial cells possess high
   metabolic characteristics, and various injuries such as hypoxia, toxic
   compounds, proteinuria, and metabolic disorders can lead to damage to
   these cells. The damage can be categorized as lethal (leading to cell
   death) and sub-lethal (resulting in injured cells releasing
   pro-inflammatory or pro-fibrotic mediators or failing to perform their
   physiological functions), which can further lead to renal fibrosis
   [[32]1–[33]3].

   Our previous research found that in the UUO rat model, the
   concentration of UII was higher than in the normal group, and
   subsequent in vitro experiments confirmed that UII can cause pyroptosis
   of renal tubular epithelial cells [[34]4]. UII as a new vasoactive
   peptide, can promote the proliferation of various cells in heart and
   kidney tissues [[35]5–[36]8]. Its receptor is
   G-protein-coupled-receptor (GPR-14) [[37]6], which is mainly
   distributed in tissues and organs such as the heart, kidneys, and
   lungs. The expression of GPR-14 in the kidney is most abundant in the
   distal convoluted tubule, collecting duct epithelial cells and
   glomerular capillary endothelial cells [[38]9]. The influence of UII on
   the kidney may be due to the systemic and local hemodynamic changes it
   induces, or it may be a direct effect of UII receptor stimulation on
   glomerular filtration and/or renal tubular secretion and reabsorption
   [[39]10]. UⅡ can enhance the expression and secretion of TGF-β1 in
   renal tubular epithelial cells, induce the expression of α-SMA,
   fibroblast-specific protein 1 (FSP-1), fibronectin and type IV collagen
   in human renal tubular epithelial cells, and participate in Renal
   fibrosis process [[40]11–[41]13]. Studies have shown that in addition
   to regulating vascular tone, UII binding to GPR-14 can also promote
   cell proliferation and extracellular matrix accumulation in the kidney
   [[42]7, [43]12, [44]14]. Our previous studies found that UII can weaken
   the L-type calcium current in cardiomyocytes, promote cardiac
   fibroblast proliferation, and promote cardiomyocyte fibrosis through
   the cyclic adenosine monophosphate/protein kinase A (cAMP/PKA)
   signaling pathway [[45]15]. Our further research revealed that UII is
   also involved in the occurrence and development of renal fibrosis in
   rats [[46]16]. Our recent preliminary experimental research results
   show that UII can upregulate the expression of cAMP and NLRP3 in renal
   tubular epithelial cells. Currently, more and more studies have proven
   that the cAMP signaling pathway is related to kidney disease [[47]17].

   Our previous research found that AS-IV has a certain protective effect
   on the kidneys of rats with chronic overload stress by reducing the
   overexpression of UII and collagen I and III in the renal interstitium
   [[48]16]. AS-IV has various pharmacological effects such as
   immunomodulation, organ protection, and anti-inflammation [[49]18]. In
   the chronic pressure overload rat model, astragaloside IV (AS-IV) may
   delay renal interstitial fibrosis by reducing the overexpression of UII
   and collagens I and III in the renal interstitium [[50]16]. Studies
   also have shown [[51]19, [52]20] that AS-IV can delay the progression
   of renal fibrosis. The mechanism may be related to the fact that AS-IV
   participates in the regulation of TLR4/NF-кB, TGF-β/Smad3, and
   Wnt/β-catenin pathways and can reduce extracellular matrix accumulation
   and inflammatory cell infiltration in kidney tissue, but the exact
   mechanism requires further study.

   Traditional Chinese medicine or traditional Chinese medicine monomers
   have the characteristics of complex action targets and action networks.
   Network pharmacology can obtain complex interaction networks based on
   target molecules, biological functions, and bioactive compounds.
   Therefore, network pharmacology research methods are a powerful tool
   for studying the complex action mechanisms of traditional Chinese
   medicine, and can elucidate the action mechanism of traditional Chinese
   medicine formulas at the molecular level from a systematic perspective
   [[53]21]. This study first intends to construct a "drug
   ingredient-disease target-signaling pathway" network diagram by
   exploring the targets of AS-IV in treating CKD. At the same time, this
   study screened potential target proteins and differentially expressed
   genes of AS-IV, and further obtained CKD-related target genes by taking
   the intersection of the two. Then, molecular docking analysis was
   performed on related genes to elucidate the mechanism of AS-IV in
   treating CKD and further delaying renal fibrosis from many aspects.
   This study not only further clarifies the mechanism of action of AS-IV,
   but also provides a certain theoretical basis for in-depth research and
   clinical application of AS-IV.

2. Material and methods

2.1 Materials

   Rat renal tubular epithelial cells NRK-52E were purchased from the Cell
   Bank of the Chinese Academy of Sciences. DMEM high-glucose medium,
   penicillin-streptomycin solution, sterile PBS solution, trypsin
   digestion solution (containing EDTA but not phenol red), Certified
   Fetal Bovine Serum special grade fetal bovine serum, dimethyl sulfoxide
   DMSO (cell culture grade, CAS: 67-68-5), SB-611812 (urotensin receptor
   antagonist, CAS: 345892-71-9), astragaloside IV (CAS: 84687-43-4),
   losartan(CAS: [54]114798-26-4), H89(CAS: 127243-85-0), and Forskolin
   (CAS: [55]66575-29-9) were bought from MCE. UII was obtained from
   Cloud-Clone Crop. Rabbit anti-NF-κB antibody (ab19870), and rabbit
   anti-TGF-β antibody (ab215715) were purchased from Abcam. Rabbit
   anti-PKA antibody, rabbit anti-GPR-14 antibody, and Alexa Fluor® 647
   goat anti-rabbit IgG were purchased from Huaan Biotech. 4%
   paraformaldehyde fixative (CAS: 66455-31-0), RIPA lysis buffer
   (strong), PMSF were purchased from Beijing Seven Biotech. Horseradish
   peroxidase-conjugated goat anti-rabbit IgG was purchased from
   Proteintech. DAPI solution (CAS: 28718-90-3) was purchased from
   Solarbio. Rat cyclic adenosine monophosphate (cAMP) enzyme-linked
   immunosorbent assay kit were bought from Jianglaibio. Total RNA
   extraction kit, and the qPCR amplification kit were bought from
   Shanghai Promega Biotechnology Company. RNA reverse transcription kit
   was purchased from Promega. Bovine serum albumin BSA-V(CAS: 9048-46-8)
   was ordered from Solarbio. Tris-glycine-SDS electrophoresis buffer
   (10X), Tris-glycine-SDS transfer buffer (10X), TBS-T washing buffer
   (10X), and SDS-PAGE protein loading buffer (5X), PVDF membrane and
   filter paper were purchased from Boster Biological Technology.

2.2 Prediction and screening of AS-IV target proteins

   The BATMAN database [[56]22] was used to obtain potential target
   proteins existing in Drugbank, KEGG, and TTD databases, and the
   predicted target proteins were ranked in descending order. In this
   study, target proteins with scores greater than 5 were selected for
   further analysis. Set the species of the online tool
   SwissTargetPrediction [[57]23] to Homo sapiens, enter the simplified
   molecular formula (SMILES) of AS-IV, and finally select the protein
   with a Probability score greater than 0 as the target protein. Enter
   “Astragaloside IV” in the ETCM database [[58]24] to obtain its
   corresponding target protein. The target proteins predicted using the
   above three databases were combined as the target of AS-IV.

2.3 Experimental data and sources

   Four sets of CKD gene data sets numbered [59]GSE15072 [[60]25],
   [61]GSE62792 [[62]26], [63]GSE66494 [[64]27] and [65]GSE98603 [[66]28]
   were downloaded from the NCBI GEO [[67]29] database on February 23,
   2021.

2.4 Screening of significantly differentially expressed genes

   For the above four sets of data sets, we first downloaded the
   preprocessed and standardized probe expression profile files, and
   downloaded the corresponding probe annotation files to annotate the
   probes. The probes are then converted into gene symbols, and when
   different probes map to the same gene symbol, the average value is
   taken as the expression value of the gene. Finally, the limma package
   Version 3.34.7 [[68]30] in the R3.6.1 language was used to screen genes
   (differentially expressed genes, DEGs) that were significantly
   differentially expressed between CKD and normal groups. In addition, BH
   is used to correct the pvalue to obtain p.adjust value. The set
   thresholds are as follows: |log2FC|>0.585 and p.value<0.05.

2.5 GO functional analysis and pathway analysis of DEGs

   The AS-IV target protein and CKD-related genes obtained through the
   above steps are intersected to obtain target genes related to AS-IV
   treatment of CKD. These target genes were then analyzed using DAVID
   version 6.8 [[69]31, [70]32] to analyze their enriched GO (Gene
   Ontology) biological processes and KEGG (Kyoto Encyclopedia of Genes
   and Genomes) signaling pathways. p <0.05 and the number of enriched
   genes count ≥2 are used as the threshold for screening significant
   enrichment.

2.6 Target protein interaction analysis

   Based on the obtained related target genes of AS-IV acting on CKD, the
   STRING database [[71]33] was used to search for the interaction
   relationship between the corresponding proteins. Cytoscape Version
   3.6.1 [[72]34] was used to construct a visual network for the
   above-mentioned protein to protein interaction (PPI). The threshold for
   interaction screening is combined score = 0.4. Then the CytoNCA plug-in
   [[73]35] was used to perform node degree analysis on the
   above-mentioned PPI network, and the parameters were set to without
   weight. Screen key proteins based on the ranking of node degrees in the
   network. At the same time, we also used the MCODE plug-in [[74]36] to
   identify module genes in the network, with parameters set to default
   values and a threshold of score ≥5.

2.7 Network pharmacology and molecular docking analysis

   Based on the components of AS-IV-target protein-pathway, cytoscape was
   used to construct a pharmacological network to demonstrate the pathway
   regulation mechanism of target proteins related to the treatment of CKD
   by AS-IV. In this study, the top 10 pathways (according to p value) in
   the pathway enrichment analysis were selected to construct the network.

   The top 3 key proteins in the PPI network and the genes of the cAMP
   signaling pathway were selected as key targets. Download the structure
   file of the complex formed by the above target protein and other small
   molecules in the PDB database for subsequent research. Download the SDF
   format file of the molecular structure of AS-IV through the PubChem
   Compound database [[75]37]. Convert it to PDB format using pymol for
   subsequent molecular docking analysis. Finally, Autodock (version
   4.2.6) software [[76]38] was used to perform molecular docking between
   key small molecules and targets.

2.8 NRK-52E proliferation detection

   The CCK8 cell proliferation experiment was used to observe the
   proliferation of cells in each group after NRK-52E intervention with
   different UII concentrations for 24 hours. Group according to different
   UII concentrations: 0mol/L UII, 10^-10mol/L UII, 10^-9mol/L UII,
   10^-8mol/L UII, 10^-7mol/L UII, 10^-6mol/L UII. NRK-52E was cultured in
   complete culture medium (89% DMEM high-glucose medium, 10% fetal bovine
   serum, 1% penicillin-streptomycin double antibody), 37°C, 5% CO2 and
   100% humidity cell culture incubator. Cells were passaged when
   confluence reached about 95%. When the cells reached the third passage
   and the confluence reached about 90%, the cells were planted in a
   96-well plate and then cultured in a cell culture incubator for 24
   hours. After observing that the cells are in an adherent state, 100 μL
   of UII of different concentrations were added to each well according to
   the experimental group and placed in a cell culture incubator for 24
   hours. Add 10 μL of cell proliferation detection reagent to each well,
   and then place the 96-well plate in a cell culture incubator and
   incubate for 1–4 hours. After incubation, microplate reader was used to
   detect the OD value at 450nm in each well.

2.9 Determination of cAMP content by ELISA

   The cell culture method is the same as above. Experimental groups were
   set as follow: control group, UII group (10^−8 mol/L UII), UII + FSK
   group (10^−8 mol/L UII+ Forskolin (cAMP agonist, 10 μmol/L)), UII +
   SB-611812 group (10^−8 mol/L UII + SB-611812 (UIl receptor antagonist,
   1 μmol/L)), UII + AS-IV group (10^−8 mol/L UII + 40μmol/L AS-IV
   [[77]39]), UII + H89 group (10^−8 mol/L UII + H89 (cAMP inhibitor, 20
   μmol/L)), UII + losartan group (10^−8 mol/L UII + 10^-5mol/L losartan).
   All cells were collected and lysed using RIPA lysis buffer after
   treatment. The lysed cells were centrifuged at 1000 r/min at 4°C for 20
   min, the supernatant was collected, and the cAMP content was detected
   according to the instructions of the cAMP ELISA kit.

2.10 Cell immunofluorescence

   After washing the slides with sterile PBS solution, fix the cells on
   the slides with 4% paraformaldehyde for 25 minutes at room temperature.
   The cells were then punched with 0.5% Triton for 10 minutes and blocked
   with 3% BSA for 30 minutes at room temperature. Place the cell sample
   on a slide on which primary antibodies (rabbit anti-GPR-14 antibody,
   rabbit anti-PKA antibody, rabbit anti-NF-κB antibody, rabbit anti-TGF-β
   antibody) have been dropped. Place the cell samples in a humidified box
   and incubate overnight in a 4°C refrigerator. The next day, the cell
   slides were washed with sterile PBS solution and placed in a darkroom
   for further processing. Place the cells onto a glass slide on which
   Alexa Fluor® 647 goat anti-rabbit IgG has been dropped, and incubate
   for 2 hours at room temperature in the dark. Add DAPI to counterstain
   the cells for 10 minutes and then add anti-fluorescence attenuation
   mounting medium dropwise to mount the slide. Place the cell sample
   under an oil lens and take pictures. Image-J was used to quantitatively
   calculate the fluorescence intensity of each indicator in each group.

2.11 Quantitative RT-PCR

   Primers were designed in Pubmed and synthesized by Invitrogen Co., Ltd.
   The primer pair sequences (rat) are as follows:
   Gene Name         Gene Sequence (5’→3’)
   GPR-14    Forward GACTTCCTGACAATGCACGC
             Reverse TTACGGTAACCCTTGGAGCG
   NF-κB     Forward GATCCTTTCGGAACTGGGCA
             Reverse GGTATGGGCCATCTGCTGTT
   TGF-β     Forward ATGCCAACTTCTGTCTGGGG
             Reverse CCCGGGTTGTGTTGGTTGTA
   PKA       Forward AAGAAAGGCAGCGAAGTGGAG
             Reverse ATTACTCGGGGGAGGGTTCT
   Actb      Forward TGTCACCAACTGGGACGATA
             Reverse GGGGTGTTGAAGGTCTCAAA
   [78]Open in a new tab

   A total RNA extraction kit was used to extract RNA from each group, and
   the total RNA concentration was measured. Reverse transcription was
   performed using a reverse transcription kit to synthesize cDNA. Using
   cDNA as a template, use a qPCR amplification kit to amplify the cDNA,
   and quantitatively detect the fluorescence of the amplified product.
   The results are calculated using relative quantification 2-ΔΔCT to
   obtain the expression level of the target gene mRNA.

2.12 Western blotting

   The protein of cells was collected, and the protein content was
   determined by BCA protein quantification method. Proteins were
   separated by 8% SDS-PAGE electrophoresis. Use a Bio-Rad electroporation
   instrument to transfer the proteins in the gel to a PVDF membrane.
   Then, wash the membrane three times with TBS-T for 5 minutes each time.
   The above PVDF membrane was blocked with 5% skimmed milk powder at room
   temperature for 1 hour. The membrane was incubated with primary
   antibodies (rabbit anti-GPR-14 antibody, rabbit anti-PKA antibody,
   rabbit anti-NF-κB antibody, rabbit anti-TGF-β antibody) overnight at
   4°C. The next day, wash the membrane 3 times with TBS-T, 5 minutes each
   time. The membrane was incubated with horseradish peroxidase-labeled
   secondary antibody for 1 hour at room temperature. After washing the
   membrane with TBS-T, perform subsequent processing in a darkroom. Mix
   the ECL chem-iluminescence reagent and cover it on the membrane. The
   film was exposed in a dark box. Use Alpha-view software to scan and
   analyze the results.

2.13 Data analysis and statistics

   Statistical analysis was performed using GraphPad Prism 9.5.1 software
   and IBM SPSS Statistics26. Measurement data are expressed in mean ± SD.
   Comparisons between multiple groups were performed using one-way
   analysis of variance. Pairwise comparisons between groups were
   performed using the LSD-t test. The difference was considered
   statistically significant when P<0.05.

3 Results

3.1 Prediction results of AS-IV target protein

   By using BATMAN, SwissTargetPrediction, and ETCM databases for
   prediction, 58, 44, and 4 target proteins for AS-IV to exert
   pharmacological effects were predicted, respectively. Finally, a total
   of 101 target proteins were obtained by combining the above results
   ([79]S1 Fig).

3.2 Screening of CKD-related genes

   After screening four data sets ([80]GSE15072, [81]GSE62792,
   [82]GSE66494, and [83]GSE98603), 685 (319 up-regulated, 366
   down-regulated), 157 (148 up-regulated, 9 down-regulated), 8403 (6730
   up-regulated, 1673 down-regulated), and 237 (93 up-regulated, 144
   down-regulated) DEGs were obtained respectively ([84]Fig 1).

Fig 1. Volcano plot of differentially expressed genes.

   [85]Fig 1
   [86]Open in a new tab

   Upper left, [87]GSE15072; upper right, [88]GSE62792; lower left,
   [89]GSE66494; lower right, [90]GSE98603.

3.3 Function and pathway enrichment analysis

   The 101 target proteins of AS-IV obtained above and the DEGs screened
   from the four data sets ([91]GSE15072, [92]GSE62792, [93]GSE66494,
   [94]GSE98603) were intersected, and 7, 0, 49, and 1 DEGs were obtained
   respectively. The results obtained from these several data sets were
   then combined to obtain 54 target genes ([95]S2 Fig)

   Functional and pathway enrichment analysis was performed on the 54
   target genes obtained above, and a total of 105 significantly enriched
   GO biological functions and 21 KEGG signaling pathways were obtained.
   The biological functions enriched by GO analysis mainly include ion
   transmembrane transport, γ-aminobutyric acid signaling pathway,
   positive regulation of heterotypic intercellular adhesion, positive
   regulation of ERK1 and ERK2 cascades, etc ([96]S3 Fig). Significantly
   enriched KEGG pathways include neuroactive ligand-receptor interaction,
   cAMP signaling pathway, proximal tubule bicarbonate recycling, cGMP-PKG
   signaling pathway, etc. ([97]Fig 2). According to p value, we presents
   the top 10 functions and pathways ([98]S1 Table).

Fig 2. KEGG pathway of AS-IV acting on 54 disease-related genes.

   [99]Fig 2
   [100]Open in a new tab

   The length of the bar in the figure indicates the number of enriched
   genes, and the color from blue to red indicates the significance. The
   smaller the p.value, the more significant.

3.4 Protein interaction analysis

   In this study, a total of 47 interacting proteins were screened
   ([101]S2 Table), including 129 relationship pairs (see [102]S3 Table
   for details of the connectivity ranking). The top three connected
   proteins are ALB, VEGFA, and AKT1. Then the PPI network is identified
   and two sub-modules are obtained based on threshold screening.

3.5 Pharmacological network construction and molecular docking

   The constructed AS-IV component-target protein-pathway network diagram
   contains 37 nodes and 82 relationships ([103]Fig 3). These include 1
   chemical component node, 25 target protein nodes and 10 pathway nodes
   ([104]S4 Table).

Fig 3. Network diagram of network pharmacology analysis.

   [105]Fig 3
   [106]Open in a new tab

   The blue hexagon is the component of AS-IV. The orange circle
   represents the target gene, the light blue square represents the
   signaling pathway; the green line represents the gene participating in
   a certain pathway, and the light purple dotted line represents the
   targeting effect of the component and the target gene protein.

   Molecular docking analysis was conducted using the top 3 key proteins
   in the PPI network (ALB, VEGFA, AKT1) and cAMP signaling pathway
   proteins (ROCK1, DRD2), as well as AS-IV. Download the crystal
   structure of the complex of ALB, VEGFA, AKT1, ROCK1, DRD2 and other
   ligands from the PDB database. Their PDB IDs are 6YG9, 1MKK, 3O96,
   3V8S, and 6CM4, respectively. Water molecules and small molecules were
   removed from these structures and the protein 3D structure was
   isolated. Then, based on the principle that the smaller the Binding
   Energy, the higher the possibility of binding, the model with the
   smallest Binding Energy was selected as the best model and a visual
   simulation was performed ([107]Fig 4). Among them, the minimum binding
   energy of AS-IV with ALB, VEGFA, AKT1, ROCK1, and DRD2 are: -8.91,
   -12.87, -9.24, -5.68, and -8.77 respectively.

Fig 4. Schematic diagram of molecular docking.

   [108]Fig 4
   [109]Open in a new tab

   A, B, C, D, and E represent the molecular docking results of AKT1, ALB,
   ROCK1, VEGFA, and DRD2, respectively. The left column shows the global
   diagram of simulated docking, in which the green sphere represents the
   ligand small molecule AS-IV; The middle column indicates the results
   for each receptor, in which yellow indicates the ligand small molecule
   AS-IV; The column on the right is a partial three-dimensional diagram
   of simulated docking, in which yellow represents the ligand small
   molecule AS-IV, and green represents the bound protein amino acid
   residues. The surrounding text indicates amino acid residues, and the
   red dashed lines indicate interacting hydrogen bonds.

3.6 Effects of different concentrations of UII on NRK-52E proliferation

   The results showed that there was no linear correlation between UⅡ
   concentration and cell viability. Compared with the control group (0
   mol/L UII), the cell viability of the 10^-10mol/L, 10^-9mol/L,
   10^-8mol/L, 10^-7mol/L, and 10^-6mol/L UⅡ groups all decreased (P<0.05,
   [110]Fig 5A). It indicated that UII treatment will inhibit cell
   viability of NRK-52E. And the treatment of 10^−8 mol/L UII showed less
   effect on cell viability, which indicates 10^−8 mol/L of UII is a
   relative safe concentration for UII-mediated renal tubular epithelial
   cell injury study. Therefore, 10^−8 mol/L of UII was used in subsequent
   experiments.

Fig 5. Effects of AS-IV on cAMP content in NRK-52E.

   [111]Fig 5
   [112]Open in a new tab

   A, Viability of NRK-52E cells treated with different concentrations of
   U II. *P<0.05, compared with control group; #P<0.05, compared with
   10^−10 mol/L, 10^−9 mol/L, 10^−7 mol/L and 10^−6 mol/L UⅡ group,
   respectively, n ≥3. B, The changes in intracellular cAMP concentration
   after NRK-52E cells are treated with UII and UII in combination with
   various signal transduction pathway regulators. *P<0.05, compared with
   the N group, #P<0.05, compared with the UII group, n ≥3.

3.7 Effects of AS-IV on cAMP content in NRK-52E

   Compared with the control group, the cAMP levels in NRK-52E cells in
   the UII group and the UII + FSK group were significantly increased
   (P<0.05). However, compared with the UII group, the cAMP levels in the
   UII + SB-611812 group, UII + AS-IV group, UII + H89 group and UII +
   losartan group were decreased significantly (P<0.05). The results
   showed that under the treatment of SB-611812, AS-IV, H89 and losartan,
   the upregulation of cAMP in NRK-52E cells by UII can be inhibited
   ([113]Fig 5B).

3.8 Cellular immunofluorescence detection of the impact of AS-IV on key genes

   The results showed that GPR-14 ([114]Fig 6A and 6B), PKA ([115]Fig 6C
   and 6D), NF-κB ([116]Fig 6E and 6F), and TGF-β ([117]Fig 6G and 6H)
   were expressed in scattered spots in the cytoplasm and nucleus of
   NRK-52E. Relatively lower GPR-14, PKA, NF-κB, and TGF-β expression were
   found in NRK-52E in the control group. After treatment with UII,
   intracellular GPR-14, PKA, NF-κB, and TGF-β were significantly
   increased (P<0.05). After cells were treated with UII + SB-611812, UII
   + AS-IV, UII + H89 and UII + losartan, respectively, compared with the
   UII group, the expressions of GPR-14, PKA, NF-κB and TGF-β were
   significantly decreased (P<0.05). Combined with the ELISA results, it
   is suggested that the cAMP/PKA signaling pathway may be involved in
   UII-induced renal tubular epithelial cell injury. AS-IV and losartan
   may downregulate the cAMP/PKA signaling pathway to protect renal
   tubular epithelial cells.

Fig 6. The expression of key genes after AS-IV treatment, detected by
immunofluorescence.

   [118]Fig 6
   [119]Open in a new tab

   A, C, E, G, Laser confocal images of NRK-52E cells in each group (10×63
   times, eyepiece 10 times, oil lens 63 times. B, D, F, H, Quantitative
   immunofluorescence analysis of NRK-52E cells in each group. *P<0.05
   compared with N group, ^#P<0.05 compared with UII group, n ≥3.

3.9 Quantitative RT-PCR to verify the impact of AS-IV on key genes

   Experimental results showed that NRK-52E in the control group had
   relatively lower GPR-14, PKA, NF-κB, and TGF-β mRNA expression. After
   stimulation with UII, the expression levels of intracellular GPR-14,
   PKA, NF-κB, and TGF-β mRNA were significantly increased (P<0.05). After
   treatment with UII + SB-611812, UII + AS-IV, UII + H89 and UII +
   losartan, respectively, compared with the UII group, the expression of
   GPR-14, PKA, NF-κB, TGF-β mRNA were decreased significantly (P<0.05).
   Combined with the ELISA results, it is suggested that the cAMP/PKA
   signaling pathway may be involved in UII-induced renal tubular
   epithelial cell injury. AS-IV and losartan may downregulate the
   cAMP/PKA signaling pathway to protect renal tubular epithelial cells
   ([120]Fig 7A).

Fig 7. The expression of key genes after AS-IV treatment, detected by Q-PCR
and Western blot.

   [121]Fig 7
   [122]Open in a new tab

   A, The mRNA expression levels of PKA, GPR-14, NF-κB, and TGF-β in each
   group after NRK-52E intervention. B, The protein expression of PKA,
   GPR-14, NF-κB, and TGF-β in each group after NRK-52E intervention. *P <
   0.05 compared with the N group, ^#P<0.05, compared with the UII group.

3.10 Western blot to verify the impact of AS-IV on key genes

   The results showed that the control group NRK-52E had relatively lower
   GPR-14, PKA, NF-κB, and TGF-β protein expression. After treatment with
   UII, the expression levels of intracellular GPR-14, PKA, NF-κB, and
   TGF-β proteins were significantly increased (P<0.05). After cells were
   treated with UII + SB-611812, UII + AS-IV, UII + H89 and UII +
   losartan, respectively, compared with the UII group, the protein
   expression levels of GPR-14, PKA, NF -κB and TGF-β were significantly
   decreased (P<0.05). Combined with the ELISA results, it is suggested
   that the cAMP/PKA signaling pathway may be involved in UII-induced
   renal tubular epithelial cell injury. AS-IV and losartan may
   downregulate the cAMP/PKA signaling pathway to protect renal tubular
   epithelial cells ([123]Fig 7B).

4 Discussion

   The prevalence of CKD among adults worldwide is as high as 10–15%
   [[124]40]. And its incidence rate is increasing year by year in both
   developed and developing countries [[125]41], but there is still a lack
   of effective intervention methods. Our previous research found that
   AS-IV has a certain protective effect on renal tubular epithelial cell
   damage in diabetic nephropathy [[126]42].

   This study used network pharmacology research methods to explore the
   molecular mechanism of AS-IV in delaying the progression of kidney
   disease. Through differential analysis, we screened a total of 54 genes
   related to AS-IV treatment of CKD. These genes are enriched in 21
   pathways, including cAMP signaling pathway, neuroactive ligand-receptor
   interaction, cGMP-PKG signaling pathway, and so on. Among them, the
   cAMP signaling pathway is the key pathway for AS-IV to treat CKD.
   Subsequently, we conducted molecular docking analysis of the top three
   key proteins in the PPI network (ALB, VEGFA, AKT1) and key proteins in
   cAMP pathway (ROCK1, DRD2) with AS-IV, respectively. We found that
   AS-IV molecules can be well embedded in the active pockets of the above
   five key gene proteins (ALB, VEGFA, AKT1, ROCK1, and DRD2).

   Studies have shown [[127]43] that the cAMP/PKA signaling pathway is
   involved in regulating the process of tissue and organ fibrosis.
   Activating the cAMP/PKA signaling pathway can induce the expression of
   downstream TGF-β and other factors, thereby promoting the progression
   of renal fibrosis [[128]44]. The cAMP/PKA signaling pathway can
   regulate nuclear transcription factor-κB (NF-κB) and activate the NLRP3
   inflammasome at the transcriptional level. Studies have shown that
   Intermedin (IMD, a small peptide belonging to the
   calcitonin/calcitonin-generating peptide family) can inhibit the
   production of reactive oxygen species (ROS) by down-regulating the
   cAMP-PKA signaling pathway, thereby reducing renal fibrosis caused by
   unilateral ureteral obstruction (UUO) [[129]45]. Renal fibrosis is
   primarily driven by inflammatory cytokines, including transforming
   growth factor-β (TGF-β) [[130]46, [131]47]. At the same time, NF-κB is
   a major regulator of many pro-inflammatory and pro-fibrotic molecules
   [[132]48]. Therefore, we used TGF-β and NF-κB as indicators of cellular
   fibrosis. The results of this study show that UII can induce the
   proliferation of renal tubular epithelial cells by upregulating the
   cAMP/PKA signaling pathway, leading to an increase in the inflammatory
   injury factors NF-κB and TGF-β, and promoting renal tubular epithelial
   cell damage. It is suggested that the cAMP/PKA signaling pathway plays
   an important role in the progression of kidney disease.

   As a new vasoactive peptide, UII plays an important role in a variety
   of pathophysiological processes. Studies have proven [[133]14, [134]49]
   that the combination of UII and GPR14 can not only regulate vascular
   tone, but also promote cell proliferation, epithelial
   cell-to-mesenchymal transition, and extracellular matrix accumulation
   in the kidney. And it also promotes extracellular calcium influx in the
   renal tubular epithelium and the release of calcium ions in the
   sarcoplasmic reticulum, which in turn leads to an increase in
   intracellular calcium and activates calcineurin. Eventually, the
   transcription factor NFAT3 is dephosphorylated and transferred into the
   nucleus, regulating gene expression and producing a pro-proliferative
   effect. In addition, UII can also promote the proliferation of renal
   interstitial fibroblasts in a dose-dependent manner and affect the cell
   cycle. And promotes renal fibrosis by regulating inflammatory signaling
   pathways such as JAK2/STAT3. Recent studies have shown that UII can
   induce pyroptosis by regulating the NLRP3-Caspase1 pathway [[135]50].
   And it can enhance the expression and secretion of TGF-β in renal
   tubular epithelial cells, and induce the up-regulation of alpha-smooth
   muscle actin (α-SMA), fibroblast specific protein 1 (FSP1), fibronectin
   (FN) and collagen IV (Col Ⅳ) in human renal tubular epithelial cells,
   thereby promoting the occurrence and development of fibrosis
   [[136]11–[137]13]. Combined with the results of this study, it is
   suggested that UII and TGF-β have similar pathological effects. UII can
   induce the expression of NF-κB and TGF-β in NRK-52E cells by
   upregulating the cAMP/PKA signaling pathway, thereby inducing
   inflammatory damage of renal tubular epithelial cells and promoting the
   occurrence and development of fibrosis.

   Studies have found that by down-regulating the AKT/GSK-3β signaling
   pathway, AS-IV can reduce the expression of α-SMA, type I collagen and
   fibronectin induced by TGF-β1 and inhibits the
   epithelial-to-mesenchymal transition of rat renal tubular epithelial
   cells and delays renal fibrosis [[138]51]. At the same time, AS-IV can
   reduce the urinary protein excretion rate of rat models of diabetic
   nephropathy and inhibit the proliferation of glomerular mesangial cells
   in rats, thereby delaying renal fibrosis. In the UUO model of rats with
   obstructive nephropathy, AS-IV can inhibit the infiltration of
   inflammatory cells and improve the survival rate of renal tubular cells
   by regulating the TLR4/NF-кB, TGF-β/Smad3, and Wnt/β-catenin signaling
   pathways and prevent cell apoptosis, thereby delaying the progression
   of renal fibrosis [[139]19, [140]52–[141]54]. Our preliminary research
   has found that AS-IV has a certain role in inhibiting inflammatory
   mediators and improving renal fibrosis in a rat model of diabetic
   nephropathy. In this study, it was found that AS-IV can down-regulate
   the cAMP/PKA signaling pathway and inhibit the expression of
   inflammatory factors in renal tubular epithelial cells, thus exerting
   its renal protective effect. This result provides a more powerful
   experimental basis for exploring the treatment of AS-IV in kidney
   disease, and provides certain evidence for the clinical promotion of
   AS-IV.

   This study preliminarily analyzed the mechanism of AS-IV in improving
   renal fibrosis based on network pharmacology methods and molecular
   docking technology, and selected key pathways for in vitro experimental
   verification. The results show that AS-IV can exert a renal protective
   effect through different signaling pathways, reflecting the
   characteristics of the combined effects of AS-IV on multiple pathways.
   This study provides a scientific basis for the clinical application of
   AS-IV in the treatment of renal fibrosis, and also provides a new
   direction for exploring the potential mechanism of action of AS-IV. The
   experimental verification of this study found that UII can induce
   damage to renal tubular epithelial cells to a certain extent, and AS-IV
   can improve this damage. However, the relationship between other
   discovered signaling pathways and other downstream target genes such as
   ROCK1, DRD2, etc. still needs further experimental verification. In the
   future, we will continue to conduct experimental verification of target
   genes downstream of this pathway. In summary, through this network
   pharmacology analysis, we have obtained more new targets for AS-IV in
   the treatment of renal fibrosis, and also demonstrated that network
   pharmacology is one of the powerful tools for exploring the mechanism
   of drug action.

5. Conclusions

   AS-IV may improve UII-mediated renal tubular epithelial cell damage by
   down-regulating the cAMP/PKA signaling pathway. Further animal
   experiments will need to validate the results and conclusions obtained
   from network pharmacology and cell biology, with the aim of
   corroborating these findings at the animal level. This may provide a
   new direction for the study and treatment of renal tubular epithelial
   cell damage.

Supporting information

   S1 Raw images

   (PDF)
   [142]pone.0310210.s001.pdf^ (162.2KB, pdf)
   S1 Table. The enrichment results of 54 target genes.

   (XLSX)
   [143]pone.0310210.s002.xlsx^ (23.6KB, xlsx)
   S2 Table. PPI network relationships.

   (XLSX)
   [144]pone.0310210.s003.xlsx^ (19.9KB, xlsx)
   S3 Table. PPI network protein connectivity.

   (XLSX)
   [145]pone.0310210.s004.xlsx^ (10KB, xlsx)
   S4 Table. Astragaloside-target protein-pathway network.

   (XLSX)
   [146]pone.0310210.s005.xlsx^ (9.5KB, xlsx)
   S1 Fig. Target prediction results of astragaloside IV.

   Red diamond, predicted tool or database; green circle, target gene
   name.

   (PDF)
   [147]pone.0310210.s006.pdf^ (115.1KB, pdf)
   S2 Fig. Venn diagram of the intersection of astragaloside IV target
   protein and differential genes in each data set.

   (PDF)
   [148]pone.0310210.s007.pdf^ (78.4KB, pdf)
   S3 Fig. The astragaloside IV component acts on GO BPs that are
   significantly enriched in 54 disease-related genes.

   Red dots, enriched up-regulated genes; Blue origin, enriched
   down-regulated genes; The middle strip, the pathway z-score, reflects
   the up- and down-regulation of the pathway to a certain extent; Red
   strip, z-score is greater than 0, indicating that the pathway is
   activated; Blue strip, z-score less than 0, indicates that the pathway
   is inhibited.

   (PDF)
   [149]pone.0310210.s008.pdf^ (69.7KB, pdf)

Data Availability

   All relevant data are within the manuscript and its [150]Supporting
   Information files.

Funding Statement

   This study was funded by the scientific research project of Shanxi
   Provincial Administration of Traditional Chinese Medicine
   (2023ZYYB030). The funders had no role in study design, data collection
   and analysis, decision to publish, or preparation of the manuscript.

References