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Curcumin mediates macrophage polarization to inhibit the formation of abdominal aortic aneurysms by inhibiting the expression of histone acetyltransferase EP300
⁎Corresponding authors at: School of Life and Pharmaceutical Sciences, Dalian University of Technology, Liaoning, No. 2 Dagong Road, Panjin, China(Y. Han), Department of Vascular Surgery, The First Hospital of China Medical University, Shenyang, China. No. 155 Nanjngbei Street, Shenyang, China(J. Zhang). jianzhang@cmu.edu.cn (Jian Zhang), yanshuohan@dlut.edu.cn (Yanshuo Han)
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Received: ,
Accepted: ,
This article was originally published by Elsevier and was migrated to Scientific Scholar after the change of Publisher.
Abstract
Background
The onset of abdominal aortic aneurysm (AAA) is caused by local dilatation of the infrarenal abdominal aorta. Curcumin can affect the polarization and function of macrophage subsets in the context of vascular diseases. Curcumin, a natural EP300 inhibitor, may have therapeutic effects on vascular diseases.
Objective
To explore the therapeutic pathway of curcumin in AAA.
Methods
We found that the hub regulatory factor EP300 is the key factor by which curcumin acts on AAA through bioinformatics network pharmacology and molecular docking. We verified the localization of histone acetyltransferase EP300 in AAA tissue by immunohistochemistry (IHC) and immunofluorescence (IF) staining. Then, we used Real-time polymerase chain reaction (RT-PCR) to explore the high expression level of EP300 in human AAA tissues and analysed its correlation with key genes in AAA diseases. In addition, we successfully induced M1 macrophages and EP300 knockout macrophages with LPS/IFN-γ in vitro to investigate the effect of EP300 on macrophage polarization.
Results
In our study, thirty important targets, including AKT1, STAT3, EGFR, EP300, GSK3B, APP, SERPINE1 and MMP14, were involved in the interaction between AAA and curcumin. Our molecular docking results showed that EP300 spontaneously binds to curcumin most easily. Therefore, we subsequently identified the histone acetyltransferase EP300 as the hub target of curcumin in AAA. IHC and IF staining of the outer membrane of AAA showed that EP300 was located in the mesa of AAA tissue, which was also the place where macrophages gathered. The mRNA expression of EP300 in human AAA tissue was upregulated, as shown by RT-PCR (P = 0.01). In in vitro RAW264.7 cells, we found that EP300 knockout in M0 macrophages significantly promoted the anti-inflammatory M2 polarization of macrophages and inhibited the proinflammatory M1 polarization of macrophages.
Conclusion
Our research showed that in the therapeutic mechanism by which curcumin treats human AAA, histone acetyltransferase EP300 affected the progression of AAA by promoting aortic inflammation, acting on the immune environment, modulating macrophage proinflammatory polarization, and influencing the expression of other AAA target genes.
Keywords
Curcumin
M1/M2 polarization
Abdominal aortic aneurysm
Histone acetyltransferase EP300
Macrophages
1 Introduction
The pathogenesis of AAA is characterized by continuous expansion and weakening of the local abdominal aorta (Sidloff et al., 2017; Jiang et al., 2015; Krishna et al., 2010). AAA is usually classified into three types, namely, the symptomatic, asymptomatic and ruptured types, accompanied by local permanent expansion and weakening (Helderman et al., 2008; Gurung et al., 2020). Recently, the UCC-SMART prospective cohort study showed that the prevalence of screen-detected AAA in men with vascular disease decreased between 1997 and 2017. According to ultrasound screening studies, AAA affects 1% to 2% of men aged 65 years and 0.5% of women aged 70 years (Carter et al., 2020; Thorbjørnsen et al., 2019; Cervin et al., 2020).
The mortality rate of AAA is above the average mortality rate, and the incidence rate is different in different regions and among different races (Begley et al., 2018). Over the past decade, AAA-related illnesses have been among the 12–15 leading causes of death among people 55 and older in the United States (Gratama and van Leeuwen, 2010), the United Kingdom and some European countries (Takei et al., 2012). Compared with the general population, the mortality rate of AAA patients is above the average regardless of whether they are being treated (van Lindert et al., 2009; Long et al., 2010; Hohneck et al., 2019). In addition, women with AAA have a lower survival rate than men because women have a higher risk of aneurysm rupture and a more complex aneurysm shape, which makes AAA surgery more difficult (Deery et al., 2017).
AAA is a complex multifactorial disease that has genetic and environmental risk factors, and it usually is found in the late stage of disease (Pearce and Shively, 1085). Studies have shown differences in gut microbial diversity for patients with abdominal aortic aneurysm and atherosclerosis (Origuchi et al., 1996). The prevalence of AAA is much higher in high-risk groups, such as those with chronic obstructive pulmonary disease (COPD) (Taimour et al., 2019). In AAA therapy, surgical intervention and endovascular therapy are usually recommended for patients with severe symptoms of AAA to prevent rupture of the AAA (Shi et al., 2020), but drugs are usually required for patients with mild symptoms of AAA (Kessler et al., 2022). Unfortunately, there are no pharmacologic agents that are effective in reducing the expansion of AAAs (Liu et al., 2020). Recent studies on drugs for the treatment of AAA, particularly macrolides, tetracyclines, statins, angiotensin-converting enzyme inhibitors, angiotensin receptor blockers, corticosteroids, and antiplatelet agents, have shown that these drugs have many adverse effects. We desperately need drugs with few side effects to treat monoarticular arteriosclerosis (Yu et al., 2020).
In addition, infiltration of inflammatory immune cells in the aortic adventitia is an important feature of AAA (Potteaux and Tedgui, 2015). The formation and development of AAA is closely related to macrophages (Raffort et al., 2017). Macrophages play a role in vascular inflammation in AAA through their polarization. The AAA is transformed into a proinflammatory or anti-inflammatory type by macrophages (Cheng et al., 2018; Davis et al., 2021). When drugs can regulate the polarization of macrophages, they can further regulate heart metabolism and inflammation in CVD (cardiovascular disease) (Davis and Gallagher, 2019). Circular Cdyl RNA promotes AAA formation by polarizing M1 macrophages and promoting M1-type inflammation (Song et al., 2022). By weakening the expression of the hub gene EP300, curcumin promotes the polarization of macrophages, thereby hindering the AAA inflammatory microenvironment and thus playing a role in improving the condition of patients with AAA diseases.
Curcumin is a phenolic compound extracted from the rhizome of Curcuma longa. Curcumin not only has anti-inflammatory, antitumour, antithrombotic and other effects but also has shown cardiovascular protection effects in in vivo and in vitro experiments. Curcumin improves vascular function through anti-atherosclerosis mechanisms, inhibition of vascular smooth muscle migration and proliferation, regulation of blood lipids, and antiplatelet aggregation. It can also be effectively used as an adjuvant for several inflammatory and immune-mediated diseases, such as atherosclerotic plaque formation (Laurindo et al., 2023; Quispe et al., 2021). Acetyltransferase p300 regulates the ageing of atrial fibroblasts and age-related atrial fibrosis through the p53/Smad3 axis (Gao et al., 2023). However, few studies have systematically elucidated the target and molecular mechanism of curcumin against abdominal aortic aneurysm. Network pharmacology is an emerging topic based on systems biology theory, which uses the network analysis of biological systems for the molecular design of drugs that target multiple specific signalling nodes.
The purpose of this study was to build a network of “component targeting disease pathway” interactions through network pharmacological methods, predict the binding mode and affinity of ligand-receptor interactions through molecular docking technology, and investigate the target, pathway and presumable mechanism of action of curcumin in the healing of AAA. The experimental verification study established the expression of the hub target gene EP300 in human tissue, further explored the regulation of macrophage polarization by EP300 and provided a reference for subsequent research. The flow chart of this research project is shown in Fig. 1.
Network pharmacology and molecular docking experimental flow chart.
2 Materials and methods
2.1 Study on the AAA targets of curcumin
The verified and predicted targets of curcumin were obtained through the SuperPred (https://prediction. chart. de/) and the Swiss Target Prediction (https://www.swisstargetprediction.ch/) databases using DisGeNET (https://www.digenet. org/), NCBI (https://www.ncbi.nlm.nih. gov/) and GeneCards (https://www.genecards. org. Retrieve the above ginger/). The targets of curcumin action were mapped to the AAA targets to determine the presumable targets on which curcumin acts for AAA therapy.
2.2 Construction of the protein interaction network and the screening of hub target genes
To obtain the protein interaction network diagram and TSV file, we imported the genes obtained above into the STRING database, selected the human species and set the confidence level to > 0.18.
2.3 Analysis of network topological features
To identify the hub target genes, the cytoHubba plugin of Cytoscape 3.7.1 software was used to analyse the above files using the maximum clique centrality (MCC) method. The six parameters of centrality (DC), intermediate centrality (BC), eigenvector centrality (EC), proximity centrality (CC), local mean connectivity (LAC) and network centrality (NC) were used to analyse the topological value of each node in the interactive network. These topological values were then analysed using CytoNCA, a plugin in Cytoscape software. These topological values indicated the topological importance of nodes in the hub protein interaction network.
2.4 Cluster analysis based on the PPI network
MCODE is an analysis tool based on the association and density of nodes in a network diagram. The scores of hub genes were analysed. The density of the node and its surrounding nodes was reflected by the hub value of the node. Then, the nodes were expanded into a seed node through the get-cluster hub algorithm, and an adjacent node satisfying the parameter condition was gradually added from the node with the largest hub. Finally, according to the parameter requirements for some follow-up processing, the final function module was generated.
2.5 GO and KEGG functional analysis
The Database for Annotation, Visualization, and Integrated Discovery (DAVID, https://david.ncifcrf.gov) was used for GO and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. The GO database included the following three categories: biological processes (BPs), cellular components (CCs), and molecular functions (MFs). KEGG included a collection of databases describing biological pathways, genomes, drugs, and diseases. Utilizing GO enrichment, the enrichment degree of the target in the disease path was analysed. Finally, the result file was output, and the enrichment graph was drawn by using R language.
2.6 Molecular docking
We downloaded the 2D structure of curcumin from the PubChem database. The 3D structures of the target proteins were downloaded from the Protein Data Bank (https://www.rcsb.org). Prior to docking computations, all proteins were cleaned and prepared. Chem3D and PYMOL software were used to remove water molecules from the protein and hydrogenate small molecules of the curcumin receptor. Search results for protein/protein lysine acetyltransferase (EP300), threonine protein kinase (AKT1) and matrix metalloproteinase 14 (MMP14) were processed into PDB format. Finally, the treated receptors were imported into Discovery Studio 2016 Client tool software and docked with drug molecules after dehydrogenation and dehydration. According to the bond energy, the binding of EP300 and curcumin was optimal.
2.7 Collection and pretreatment of experimental specimens
The human AAA tissues we studied were obtained from clinical cases of vascular surgery at the First Hospital of China Medical University. Clinical samples were selected for selective open surgery to repair aneurysms (He et al., 2021). The Aneurysm Biobank of China Medical University (CMU-aB) was used to select the AAA population and collect tissues (Tang et al., 2019). We excluded patients with vascular disease who had associated genetic abnormalities, drug history, cancer, infection, or any other immune-related disease that might negatively affect the study. Human AAA samples were collected under the guidelines of the Declaration of the World Medical Association in Helsinki. In patients diagnosed with AAA by computed tomography angiography (CTA) in CMU-aB, a subset of typical 2-–3 μm AAA tissue sections was selected for subsequent immunofluorescence (IF) and immunohistochemical (IHC) staining. The remaining tissues were used to extract and screen RNAs with a purity of A260/A280 > 1.79 and < 2.0. We selected 24 AAA patients and 8 normal controls to form the aneurysm biobank used in this study. All 32 tissue samples were stored in liquid nitrogen. TRIzol reagent (93289, Sigma Aldrich, USA) was then added to the high-quality RNA extracted above. We then used Prime ScriptTM RT Master Mix (RR036A, TaKaRa Bio, Shiga, Japan) to synthesize mRNA into cDNA for subsequent RT-PCR experiments.
2.8 IHC staining analysis of EP300 in human AAA tissues
To determine the role of EP300 in AAA organization, we performed an IHC analysis of AAA. The 2–3 µm paraffin-embedded AAA sections isolated above were treated overnight at 37 °C, dewaxed for 30 min at 60 °C, and then hydrated with xylene, isopropyl alcohol, anhydrous ethanol, 95% ethanol, and 75% ethanol. Finally, the sections were placed in antigen repair solution for antigen repair. Then, we washed with PBS 3 times for 10 min each time, incubated with 8% normal goat serum at room temperature for 10 min for closed sections, and added 40 µl to each tissue section without removing serum; 1: 1000 diluted rabbit anti-EP300 (ABS131229-50UG, Absin, Shanghai, China) working solution was added and the samples were incubated at 37 °C for 1.5 h. After using PBS for 10 min × 3 times, the secondary antibody working solution was used, and the working solution of Streptomyces ovalbumin labelled with alkaline phosphatase was added and the samples were incubated at 37 °C for 15 min; PBS was used for washing for 10 min × 3 times during the process. Then, DAB was used for colour development, and after 10 min × 3 rinsing with PBS, haematoxylin was used for staining for 30 s, and the sections were rinsed with running water for 5 min. Finally, we observed the sections with a microscope to obtain photos of different fields of view.
2.9 IF double staining analysis of CD68 and EP300 in human AAA tissue
Since we detected positive staining of EP300 in the medium membrane in AAA tissue by immunohistochemistry, to further study what kind of cells EP300 acts on in AAA tissue, we performed IF double staining analysis. We selected the macrophage marker CD68 and performed bidirectional staining with primary antibodies against CD68 and EP300 to determine cell localization in AAA tissue. Compared to IHC for the antigen repair steps mentioned above, the difference was that we blocked rabbit anti-EP300 overnight in a 4 °C light-resistant wet chamber. After washing with PBS three times, sections were incubated with goat anti-rabbit IgG Alexa Fluor 488 at room temperature sheltered from light for 2 h. Afterwards, the sections were rinsed with PBS three times and incubated with rabbit anti-CD68 overnight at 4 °C in light-resistant humidity. Cy3 (red)-conjugated goat anti-rabbit IgG was also added and samples were incubated for 2 h after three rinses with PBS, followed by three final rinses with PBS; DAPI was then added and the samples were incubated for 10 min protected from light. Finally, tissue sections were observed using fluorescence microscopy.
2.10 Macrophage cell culture and polarization induction
We used culture bottles and made foetal bovine serum with penicillin/streptomycin; then, we added DMEM to high-glucose medium to form our exclusive medium. RAW264.7 macrophages were selected for our in vitro experiment. We used lipopolysaccharide- and interferon-γ-induced macrophages, called M1 macrophages, to distinguish them from untreated macrophages called M0 macrophages, and then we cultured them at 37 °C and 5% CO2.
2.11 EP300 siRNA transfection and further induction of M1 polarization
The reagent siEP300 for knockdown of the EP300 gene in mice, the siRNA of control NC, and the transfection kit of riboFECTTMC were obtained from RiboBio. First, macrophages were inoculated into 6-well plates and transfected for 50 h after the cells were in good shape. M1 polarization was induced again 48 h after EP300 siRNA transfection (100 ng/mL LPS and 50 ng/mL IFN-γ in fresh medium and incubated for 24 h). Then, we extracted RNA and proteins for further analysis.
2.12 Quantitative real-time polymerase chain reaction (RT-qPCR)
The mRNA expression level of EP300 in tissues was determined by RT-qPCR. Reverse transcription into cDNA was performed on the tissues mentioned above. RT-qPCR was performed in the Applied Biosystems 7500 Real-Time PCR system (Thermo Fisher Scientific, USA) as follows. We selected the housekeeping gene glyceraldehyde-3-phosphate dehydrogenase (GAPDH) as a standardized internal control. The pre- and postprimer sequences were provided by Sangon Biotech (Shanghai, China) and are shown in Table 1 below. We set the initial denaturation at 80 °C for 30 s, followed by denaturation at 80 °C for 5 s, annealing at 50 °C for 30 s, and extension for 50 cycles. In each RT-qPCR experiment, the 2-ΔΔ CT method was used to calculate the relative mRNA expression level in the samples.
Gene
Category
Primer sequences (5′to 3′)
GAPDH-Homo sapiens
internal reference
F: GTTGGAGGTCGGAGTCAACGGR:GAGGGATCTCGCTCCTGGAGGA
GAPDH-Mus musculus
internal reference
F: CAGCTACTCGCGGCTTTACR: TTCACACCGACCTTCACCATT
CD86-Mus musculus
M1macrophage marker
F: CAGCACGGACTTGAACAACCR: TGTGCCCAAATAGTGCTCGT
iNOS-Mus musculus
M1macrophage marker
F: TGCCAGGGTCACAACTTTACAR: CAGCTCAGTCCCTTCACCAA
TNFα-Mus musculus
M1macrophage marker
F: GATCGGTCCCCAAAGGGATGR: GTTTGCTACGACGTGGGCT
CD206-Mus musculus
M2macrophage marker
F: GCACTGGGTTGCATTGGTTTR: CCTGAGTGGCTTACGTGGTT
Arg1-Mus musculus
M2macrophage marker
F: GTGAAGAACCCACGGTCTGTR: AGAAAGGACACAGGTTGCCC
TGFβ-Mus musculus
M2macrophage marker
F: GATACGCCTGAGTGGCTGTCR: TTTGGGGCTGATCCCGTTG
EP300-Homo sapiens
internal reference
F: GCTTCAGACAAGTCTTGGCAT
R: ACTACCAGATCGCAGCAATTC
2.13 Protein level analysis using western blotting (WB) analysis
The expression of related genes at the protein level was analysed by WB. Protein samples (15 μg per strip) were separated on 5% spacer gels and 8% separation gels and then transferred to polyvinylidene fluoride (PVDF) membranes. The membranes were then sealed with a sealer solution (5% skim milk powder, 1 × TBS, 0.05% T20) for 3.5 h and then treated with 1:1000 diluted rabbit anti-EP300 (ABS131229-50UG, Absin, Shanghai, China) and 1:1000 rabbit anti-GAPDH (D110016, Shanghai) overnight at 4 °C. Goat anti-rabbit IgG imprinted with horseradish peroxidase (HRP) was then added and membranes were incubated at room temperature at a 1:1000 dilution for 1.5 h. The samples were washed with PBS containing Tween for 10 min each time. After four washes, the immune response bands were analysed.
3 Results
3.1 Presumable targets of curcumin for AAA treatment
We collected 2193 genes as disease targets for abdominal aortic aneurysms from the DisGeNET, NCBI, and GeneCards databases. The SuperPred Webserver and SwissTargetPrediction databases were used to retrieve 70 validated targets and 49 predicted targets of curcumin and a total of 66 curcumin targets. The proportion of curcumin targets associated with EP300 was the highest among all targets (Fig. 2A). Thirty-three common targets (Fig. 2B) were obtained after mapping with the targets of AAA; they were predicted to be feasible targets of curcumin for the treatment of AAA.
(A) Proportion of curcumin targets; (B) Venn diagram of targets of AAA and curcumin.
3.2 Construction, analysis and hub gene screening of the PPI network
The PPI network diagram we obtained (Fig. 3A) showed a degree of interaction between proteins. The top 10 genes, AKT1, STAT3, EGFR EP300, GSK3B, APP, SERPINE1, MMP14, RAF1 and NFE2L2, were found to be the hub target candidates through the cytoHubba plugin (Fig. 3B). The interaction between curcumin and these 10 proteins was close, which indicated that these 10 targets are the hub targets of curcumin in AAA therapy. Then, we utilized the MCODE algorithm. Three gene clusters were obtained, and specific information for each gene cluster was shown through the MCODE plug-in. Among them, the hub gene clusters included AKT1, STAT3, EGFR, and EP300. Therefore, we identified these 10 targets as hub targets for curcumin in AAA therapy (Fig. 3C).
(A): The PPI network of presumable targets of curcumin in AAA therapy; (B) the hub target interaction diagram; (C) MCODE analysis gene cluster.
3.3 Pathway enrichment analysis
We used R software for analysis. In Fig. 4, A, B and C, the right side is the enrichment pathway, and the left side is the gene listed from high to low enrichment. Genes were enriched in each pathway, and each enrichment pathway is represented by different colours and connected with each gene, as seen in Fig. 4. The functions involved mainly included chromatin binding, oxidative stress responses to binding transcription factors, extracellular stimulus responses, positive regulation of the first 10 pathways, and visual analysis (Fig. 4D). The involved tumour signalling pathways mainly included hypoxic cell stress signalling pathways, including the HIF-1 signalling pathway, Th17 cell differentiation, and measles. The hormone signalling pathways included the thyroid hormone signalling pathway and endocrine resistance. The key enrichment targets in these pathways were mainly AKT1, EGFR, STAT3, and EP300 (Fig. 4). These genes were candidates for our hub target genes.
GO and KEGG functional enrichment. (A) BP functional enrichment; (B) CC functional enrichment; (C) MF functional enrichment; (D) KEGG functional enrichment.
3.4 Molecular docking
In summary, 10 key protein target genes were used as large molecules and curcumin was used as a small molecule for molecular docking. The docking is shown in Fig. 5, and the binding energy of the target gene to curcumin is shown in Table 2. The lower the binding energy, the more stable the conformation, the easier the spontaneous binding and the more important the target gene. The binding energies of SKT3, EGFR, GSK3B, RAF11 and EP300 with curcumin were small, the binding energy of the EP300 target with curcumin was −6.836, and the EP300 target had the strongest binding activity with curcumin. Based on the above conclusions, EP300 was selected for in vitro studies (Table 3).
Docking of hub proteins with curcumin.
Gene
Subgragh
Degree
Eigenvector
Information
LAC
Betweenness
Closeness
Network
AKT1
2446.8140
23
0.421837
4.405257
5.6
299.82
0.318681
21.02
STAT3
1932.8240
18
0.374889
4.215221
5. 9
100.09
0.298969
16.08
EGFR
1454.1330
15
0.325057
4.057686
5.1
49.22
0.284314
11.30
EP300
844.0494
10
0.247121
3.663526
5.2
10.26
0.268519
8.31
GSK3B
752.4486
10
0.233137
3.663526
4.4
12.93
0.268519
7.16
APP
692.2298
8
0.223995
3.426813
5.0
5.52
0.266055
6.37
SERPINE1
548.2217
8
0.198763
3.426813
4.2
13.13
0.271028
5.74
MMP14
545.7513
8
0.198375
3.426813
4.2
32.68
0.271028
6.04
RAF1
458.1516
7
0.181985
3.281064
3.4
5.79
0.261261
5.00
NFE2L2
457.6431
6
0.182052
3.110943
3.7
1.96
0.258929
4.50
ADAM17
447.7871
6
0.179907
3.110943
4.3
1.15
0.261261
5.20
IKBKG
447.7377
6
0.180006
3.110943
3.7
2.06
0.258929
4.67
MMP8
413.4152
6
0.17273
3.110943
4.0
1.40
0.258929
4.95
RPS6KB1
342.6825
5
0.157186
2.909784
4.0
0.00
0.256637
5.00
CXCR2
303.0739
5
0.147856
2.909784
3.2
1.17
0.256637
4.17
NOX4
262.2947
5
0.137348
2.909784
2.8
1.57
0.256637
3.50
MMP13
248.9945
7
0.132942
3.281064
2
99.15
0.271028
3.17
AGTR1
245.0689
5
0.132596
2.909784
2.8
1.57
0.256637
3.50
AURKA
228.9830
4
0.128389
2.668237
2.5
0.22
0.254386
3.33
BCL2
228.5319
4
0.128381
2.668237
2.5
0.40
0.254386
3.33
BRAF
205.8481
4
0.121635
2.668237
2.5
0.22
0.254386
3.33
TLR9
193.2925
4
0.117870
2.668237
2.5
0.50
0.254386
3.33
ALOX5
46.54573
4
0.054049
2.668237
2.0
28.93
0.258929
3.00
PTGS1
46.54573
4
0.054049
2.668237
2.0
28.93
0.258929
3.00
BMP1
19.65789
2
0.034907
2.003110
1.0
0.00
0.224806
2.00
PTGES
16.74233
4
0.026955
2.668237
1.5
13.33
0.228346
2.33
ALOX5AP
8.432649
3
0.014237
2.372784
2.0
0.00
0.218045
3.00
ALPL
4.463660
1
0.014031
1.527232
0.0
0.00
0.218045
0.00
CA2
1.543081
1
0
1.527232
0.0
0.00
0.034483
0.00
CA1
1.543081
1
0
1.527232
0.0
0.00
0.034483
0.00
Target Protein
Energy (kcal/mol)
AKT1
−0.006
STAT3
−5.367
EGFR
−60242
EP300
−6.836
GSK3B
−5.464
APP
−0.006
SERPINE1
198,015
MMP14
−0.005
RAF1
−6.246
NFE2L2
2,400,132
3.5 Location and expression of EP300 in AAA organization
We stained AAA tissue sections with EP300 antibody. We found significant positive staining of EP300 in AAA tissues located in the medium (Fig. 6). Then, we performed RT-qPCR (Fig. 7A and 7B). We found that compared with the normal control group, EP300 in AAA tissues had significantly higher expression. Subsequently, we consulted relevant data to identify some genes that had been confirmed to be significantly different in AAA diseases, such as macrophage markers, and conducted RT-qPCR experiments on these genes and measured EP300 in AAA tissues at the same time. Subsequently, we conducted Pearson analysis on these genes and EP300 and found that these genes were strongly correlated with the expression of EP300 in AAA; the correlation was 0.75 for CD45 and 0.54 for MSR-1. Due to the large number of immune cells, such as macrophages, in the middle membrane of AAA tissues, to further verify the relationship between EP300 and macrophages, we used IF double staining analysis to examine the co-staining of EP300 in the wall of AAA tissues and the label CD68 on the surface of macrophages; the results showed that EP300 was closely related to macrophages (Fig. 7C).
Immunohistochemical photos of human AAA sections stained with EP300. (A) Overview image 1000 μm; (B) original magnification × 20; (C) overview image 1000 μm; (D) original magnification × 20.
Location and expression of EP300 in AAA organization. (A) Expression levels of EP300 in AAA and normal tissues. (B) Correlation analysis of EP300 and AAA-related gene expression. (C) Immunofluorescence photographs.
3.6 Relationship between EP300 expression and macrophage polarization
Due to the previous colocalization experiment and RT-qPCR experiment, we found that EP300 was closely related to macrophages in the middle membrane of AAA tissues, as shown in Fig. 8A and 8B. We successfully induced the polarization of M1 macrophages, and the two markers of M1 showed significant differences. Western blot analysis was performed using these cells. As shown in Fig. 8C and 8D, the relative expression of EP300 was determined in M1 macrophages. The expression level of EP300 was higher than that in M0 macrophages.
The M1 model was successfully constructed in vitro, and the expression level of EP300 was analysed. (A) The expression levels of markers in the M1 model were tested. (B) The expression level of M1 markers was tested; (C) Western blotting of EP300 and GAPDH in M0 and M1; (D) quantification of relative expression by Western blotting.
3.7 The pathway by which EP300 is involved in macrophage polarization
To explore how EP300 affects the polarization of macrophages, we silenced the expression of EP300 in macrophages. Subsequently, we conducted detection based on the results of these cells, and we found that the expression level of the M1 marker was decreased and that M2 was detected. The results showed that the lower the expression of EP300 in macrophages, the more easily macrophages were polarized towards M2. The higher the expression of EP300 in macrophages, the more prone the macrophages are to M1 polarization. (Fig. 9A and 9B).
Knockdown of EP300 significantly reversed the polarization of M0-M1 macrophages. (A) Relative expression of macrophage M1 and macrophage M0 phenotypic markers; (B) relative expression of macrophage M2 and macrophage M0 phenotypic markers; (C) the expression of the M1 marker iNOS relative to GAPDH in M1 macrophages, M0 macrophages and M1-polarized macrophages after knockdown; (D) quantification of Western blotting images.
3.8 Knockdown of EP300 significantly reverses the polarization of M0-M1 macrophages
In the EP300 knockout group, we then induced M1 polarization. Compared with M0, M1 and three levels of M1 polarization after knockout, we detected the protein content of M1 markers and found that EP300 knockout could significantly reverse the M0-M1 polarization of macrophages (Fig. 9C and 9D).
4 Discussion
Our study showed the therapeutic mechanism of curcumin in human AAA. Curcumin impacts the process of AAA by altering its target genes. Amidst them, histone acetyltransferase EP300 may be important in the balance of macrophage polarization and the promotion of aortic inflammation. Curcumin may act on AAA by inhibiting the expression of EP300. In this study, 2193 disease-related targets and 66 curcumin action targets were retrieved by network pharmacological methods, and 30 presumable targets of curcumin in AAA therapy were discovered. We built a PPI network and obtained the top 10 hub targets of AKT1, STAT3, EGFR EP300, GSK3B, APP, SERPINE1, MMP14, RAF1 and NFE2L2 according to the MCC and MCODE calculation methods. STAT3, EGFR, EP300, GSK3B and RAF1 were lower than −5 kJ·mol-1. In this 3D range, the above targets showed stronger framework activity against curcumin, and EP300 showed the strongest binding to curcumin. In the supplementary information, we detail the EP300 distribution levels in AAA tissues and select those to be used in the normal group in human tissue experiments. Knockout of EP300 in M0 macrophages inhibited the M1 polarization of macrophages but promoted the M2 polarization of macrophages. In our in vitro experiment, we found that EP300 may promote aortic inflammation by participating in the regulation of macrophage polarization.
Curcumin is an important bioactive component of turmeric. Many studies have shown that curcumin has a cardiovascular protective effect against cardiovascular disease. Curcumin has strong activity in various signalling pathways related to cell growth, cell proliferation, cell survival, inflammatory response and oxidative stress (Cox et al., 2022; Hedayati-Moghadam et al., 2021). Preclinical studies on cardiovascular diseases such as atherosclerosis, stroke and cardiovascular complications of diabetes showed that curcumin plays a certain role in the treatment of cardiovascular diseases (Li et al., 2020). Some studies have shown that the c-Jun N-terminal kinase pathway and cell apoptosis are inhibited by curcumin, thus reducing the formation of aortic aneurysms in rats. The diameter of the thoracic aorta dilation induced by CaCl2 was significantly inhibited, the medial elastic fibre was inhibited and not preserved, and cell apoptosis in thoracic aortic aneurysm tissues was reduced (Fan et al., 2012). The inflammation of ApoE -/- mice was inhibited by curcumin, thus hindering the formation of AAA. Some studies have shown that the PI3K/AKT signalling pathway mediates the PVT1/miR-26a/KLF4 axis and inhibits VSMC scorching and that the inflammatory response is regulated by curcumin nicotinic acid (curcumin derivatives derived from curcumin and nicotinic acid). The Ang II-induced expression of 3a-related proteins and inflammatory factors was reduced by curcumin nicotinic acid, thus reducing VSMC scorching. Curcumin nicotinate may be regarded as a therapeutic target for AAA (Xiong et al., 2021). The number of neutrophils in the body and the ratio of neutrophils to lymphocytes were associated with mortality in AAA patients with or without vascular repair or vessel rupture (Garagoli et al., 2022; Klopf et al., 2021; Yan et al., 2016; Plana et al., 2020; Nishibe et al., 2022). It has been found that curcumin plays a role in AAA therapy by influencing biological processes such as transcription factors, the oxidative stress response, and the extracellular stimulation response. Oxidative stress is a stress response caused by an imbalance in cellular redox to produce excess reactive oxygen species (ROS) and an imbalance between antioxidant systems (Sánchez-Infantes et al., 2021; Krishna et al., 2021). Nrf2 is the main regulator of redox homeostasis, but there have been few studies on the mechanism by which curcumin affects AAA by regulating oxidative stress, and this study provides a basis for further study (Méndez-García et al., 2019).
The dynamic modification of histone H3 is associated with the formation of AAA, so histone modification is the focus of attention in the study of AAA pathology (Greenway et al., 2020). Regulatory T-cell DNA methylation and histone modification rates were significantly altered in AAA patients (Xia et al., 2019). Some studies have shown that the KAT family/p300 of CBP can stimulate multiple functions of specific transcriptional regulatory proteins (Wei et al., 2020). Histone acetylation has been proven to be associated with increased gene transcription, which may lead to overexpression of AAA-related genes. Acetylated histones enhanced the accessibility of DNA templates to the transcription of AAA-related gene expression. These modifications usually occur in the promoter region and determine genotype traits. High levels of acetylation increases the expression of various inflammatory cytokines and proteolytic enzymes, which results in the accumulation of inflammatory cells and remodelling of vascular walls in AAA. Changes in EP300 may cause AAAs to break (Han et al., 2016). In our study, curcumin treatment and EP300 reduced M1 polarization in macrophages. This proved that EP300 can contribute to the polarization of M1 macrophages and thus affect the development of AAAs.
Curcumin is an effective inhibitor of EP300. The expression of p300 and NF-κB is regulated by curcumin, which influences diabetic renal abnormalities (Chiu et al., 2009). The p300/miR-142-3p/PSMB5 axis was inhibited by curcumin, resulting in decreased CT-1 activity of the 20S proteasome; thus, this axis was adopted as a presumable therapeutic target for TNBC therapy (Liu et al., 2020). Curcumin hindered the tumour microenvironment by synergistically activating anti-PD-1 lymphocytes, suppressing immune escape, and downregulating TGF-β1 expression (Guo et al., 2021). By affecting the polarization of macrophages, mutation or knockdown of CREBBP or EP300 in B-cell lymphoma cells leads to the inhibition of H3K27 acetylation, resulting in the M2 polarization of tumour-associated macrophages. Abnormal regulation of histone acetylation influences the tumour microenvironmenty (Huang et al., 2021). In this study, a multitarget drug molecule-specific signal node-disease model was constructed. Molecular docking revealed the relationship between curcumin and AAA target genes. Therefore, in this study, topological analysis and molecular docking strategies were combined with network pharmacology to construct and analyse target networks, and target enrichment analysis was conducted to reveal the presumable therapeutic mechanism of curcumin for AAA and to study the presumable targets of curcumin against AAA. We also used bioinformatics and additional experiments to verify the results in human tissues.
Curcumin, as an active ingredient in turmeric, represents a highly cost-effective potential treatment method. Delivered as a dietary supplement, the cost of curcumin is significantly lower than many existing AAA drugs on the market. Manufacturing curcumin supplements is a tried and tested process, with significant room for economies of scale as demand increases. However, we acknowledge that the adoption of curcumin as a treatment option would necessitate further research into its bioavailability and optimal delivery methods, which may have associated costs. Additionally, standardized protocols for supplement dosage and frequency would have to be established, factoring in variables such as patient's weight, the severity of AAA, and the patient's overall health condition—this, of course, may impact the overall cost of treatment. In conclusion, while curcumin presents a promising and potentially cost-effective treatment for AAA, more research is needed to establish the full financial implications of adopting curcumin as a therapeutic option.
5 Conclusion
In exploring the therapeutic mechanism of curcumin in AAA by using network pharmacology, we found hub target genes such as AKT1, STAT3, EGFR, EP300, GSK3B and MMP14. The docking results of hub target genes and curcumin molecules showed that the binding energy of histone acetyltransferase, EP300, and curcumin was the lowest and therefore the strongest. We determined that histone acetyltransferase (EP300) is the hub target of curcumin therapy for AAA. In our in vitro study, regulation of the histone acetyltransferase EP300 altered aortic inflammation through the immune microenvironment. Therefore, by reducing the expression of EP300 in M0 macrophages, we can control the polarization of macrophages towards the M2 anti-inflammatory phenotype, thus promoting AAA remission. In summary, EP300 may be involved in regulating macrophage polarization and promoting aortic inflammation. The expression of EP300 is inhibited by curcumin, which is important in AAA therapy.
Funding
This work was supported by the Fundamental Research Funds for the Central Universities (grant number: DUT22YG107), the National Natural Science Foundation of China (grant number: 81600370), the China Postdoctoral Science Foundation (grant number: 2018M640270) and the Natural Science Foundation of Liaoning Province (2023-MS-096) for Yanshuo Han, and supported by National Natural Science Foundation of China (grant number: 81970402 and 82170507) for Jian Zhang.
7 Institutional review board statement
The Ethics Committees of the First Hospital of China Medical University approved our study protocol (ethical approval number: 2019-97-2).
8 Informed consent statement
Informed consent was obtained from all subjects involved in the study.
Acknowledgments
We would like to express our sincere gratitude to Springer Nature Author Services for their invaluable assistance with language editing. Their expertise has greatly improved the readability of our manuscript. We also wish to extend our appreciation to the reviewers whose insightful feedback and constructive recommendations have significantly contributed to the refinement of this paper. Their dedication and thoroughness have been instrumental in enhancing the quality and rigor of our work.
Declaration of Competing Interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
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