Network Pharmacology and Metabolomics Reveal Anti-Ferroptotic Effects of Curcumin in Acute Kidney Injury

Abstract

Introduction: Acute kidney injury (AKI) is linked to high rates of mortality and morbidity worldwide thereby posing a major public health problem. Evidences suggest that ferroptosis is the primary cause of AKI, while inhibition of monoamine oxidase A(MAOA) and 5-hydroxytryptamine were recognized as the defender of ferroptosis. Curcumin (Cur) is a natural polyphenol and the main bioactive compound of Curcuma longa, which has been found nephroprotection in AKI. However, the potential mechanism of Cur in alleviating AKI ferroptosis remains unknown.

Objective: This study aims to investigate the effects of Cur on AKI ferroptosis.

Methods: Folic acid (FA)-induced AKI mouse model and erastin/(rsl-3)-induced HK-2 model were constructed to assess the renoprotection of Cur. The nuclear magnetic resonance (NMR)-based metabolomics coupled network pharmacology approach was used to explore the metabolic regulation and potential targets of Cur. Molecular docking and enzyme activity assay was carried out to evaluate the effects of Cur on MAOA.

Results: Our results showed that in vivo Cur preserved renal functions in AKI mice by lowering levels of serum creatinine, blood urea nitrogen, while in vitro ameliorated the cell viability of HK-2 cells damaged by ferroptosis. Mechanistic studies indicated that Cur protected AKI against ferroptosis via inhibition of MAOA thereby regulating 5-hydroxy-L-tryptophan metabolism.

Conclusion: Our study for the first time clarified that Cur might acts as a MAOA inhibitor and alleviates ferroptosis in AKI mice, laying a scientific foundation for new insights of clinical therapy on AKI.

Keywords: acute kidney injury; curcumin; ferroptosis; metabolomics; monoamine oxidase A; network pharmacology.

Figure 1

Curcumin exerted renoprotective effects in folate-induced AKI. (A) Schematic representation of the folic acid-induced (FA-induced) AKI model and drug treatment. (B and C) Blood urea nitrogen (BUN) and creatinine (CRE) levels in mice with FA-AKI. (D) Representative haematoxylin-eosin staining of kidneys. The scale bar represents 500 μm. Experimental data are presented as mean ± SD. Statistical significances (N=10): p < 0.01, **; p < 0.0001, ****. Each repeat was performed as a separate, independent experiment or observation.

Figure 2

Typical one-dimensional (1D) ¹H spectrum of kidney aqueous extracts. The region of H₂O (4.75–4.85 ppm) was excluded, and the region of 4.85–9.6 ppm was magnified five times compared to the region of 0.5–4.75 ppm. Numbers in the panels represent: 1. Pantothenate; 2. Leucine; 3. Isoleucine; 4. Valine; 5. Ethanol; 6. 3-Hydroxybutyrate; 7. Alanine; 8. Lactate; 9. Proline; 10. Glutamate; 11. Succinate; 12. 5-Hydroxytryptophan 13. Dimethylamine; 14. Aspartate; 15. Arginine; 16. Glutathione; 17. Trimethylamine; 18. Creatine; 19. Lysine; 20. Ornithine; 21. Ethanolamine; 22. Choline; 23. Trimethylamine N-oxide; 24. Betaine; 25. Taurine; 26. Myo-Inositol; 27. Glycine; 28. Threonine; 29. Tryptophan; 30. Glutamine; 31. Serine; 32. sn-Glycero-3-phosphocholine; 33. Glucose; 34. Uridine; 35. Fumarate; 36. Tyrosine; 37. Phenylalanine; 38. Formate; 39. NAD⁺; 40. Niacinamide; 41. Inosine.

Figure 3

Multivariate statistical analysis of kidney metabolites in the control (Con), folic-acid (FA), and curcumin (Cur) groups of mice (N=10). (A–C) Score plot of PCA models. (D and E) Score plots of the PLS-DA models (F) and the permutation validation plot (G) for the FA versus Con groups. (F and G) Score plots of the PLS-DA models (F) and the permutation validation plot (G) for the FA versus Con groups. (H and I) The important metabolites (VIP >1) identified from the PLS-DA model of the FA vs Con (H) and Cur versus FA (I) groups.

Figure 4

The heatmap analysis of the identified metabolites in the control (Con), folic acid (FA), and curcumin (Cur) groups (n=10). Significantly altered metabolites found in the FA versus Con groups are marked with “*”, while those found in the Cur versus FA groups are marked with “#”. Each repeat was performed as a separate, independent experiment or observation.

Figure 5

Metabolic pathway enrichment analysis. (A and B) Disorder metabolic pathways in the FA-induced model (A) regulated by treatment with Cur. Important metabolic pathways was screened by combing p-values (<0.05) and pathway impact values (PIV>0.1). Numbers in the panels stand for metabolic pathways: 1. Phenylalanine, tyrosine and tryptophan biosynthesis; 2. Nicotinate and nicotinamide metabolism; 3. Taurine and hypotaurine metabolism; 4. Phenylalanine metabolism; 5. Arginine and proline metabolism; 6. Alanine, aspartate and glutamate metabolism; 7. Glycine, serine and threonine metabolism; 8. Tryptophan metabolism; 9. Tyrosine metabolism; 10. Inositol phosphate metabolism; and 11. Glyoxylate and dicarboxylate metabolism.

Figure 6

Network pharmacology analysis of the effects of curcumin (Cur) on acute kidney injury (AKI). (A) Venn diagram showing an intersection of predicted targets between Cur and AKI. Green, red, and overlapped yellow areas indicate targets for Cur, AKI, and common targets, respectively. (B) Compound-target network of Cur and AKI-related targets. (C) Gene Ontology enrichment analysis of predicted targets by using ClueGO. (D) Kyoto Encyclopedia of Genes and Genomes pathways enrichment analysis by using ClueGO. All pathways had a p-value <0.05.

Figure 7

The interaction network among the key genes, enzymes, pathways, and metabolites. Red hexagons: active compounds; Grey diamonds: reactions; Green rectangles: proteins; Purple circles: genes. The key genes, proteins and metabolites were enlarged for emphasis. The red background highlights the significantly regulated in both the pairwise comparisons of the folic acid (FA) versus control (Con) and curcumin (Cur) versus FA groups in the metabolomics study.

Figure 8

Molecular docking diagram of curcumin (Cur) with predicted core target proteins. (A–C) Two-dimensional (2D) molecular docking diagram of Cur with the key target proteins monoamine oxidase A (MAOA) (A), glutaminase 2 (GLS2) (B), and glutaminase (GLS1) (C). Purple arrows indicate hydrogen-bonding interactions, and red arrows indicate π-cation-bonding interactions. (D–F) Three-dimensional (3D) interaction diagrams of Cur and the crucial target proteins MAOA (D), GLS2 (E), and GLS1 (F). Yellow and green dashed lines indicate hydrogen-bonding and π-cation-bonding interactions, respectively.

Figure 9

Effect of curcumin (Cur) on renal 5-hydroxy-L-tryptophan (5-HT) metabolism. (A) RT-PCR analysis of monoamine oxidase A (MAOA) mRNA levels. The mRNA levels were represented as fold change of the levels determined in the control (Con) group which normalized to those of β-actin. (B) Enzymatic activity of MAOA, represented as fold change of the levels measured in the Con group. (C) Relative levels of 5-HT, represented as fold change of the content determined in the Con group. Experimental data are presented as mean ± SD. Statistical significances (N=6): p < 0.01, **; p < 0.001, ***. Each repeat was performed as a separate, independent experiment or observation.

Figure 10

Curcumin (Cur) inhibited ferroptosis in HK2 cells and kidneys. (A and B) Cell viability assayed by CCK-8. HK2 cells were treated with 2 μM Erastin (A) or 2 μM RSL-3 (B) to induce ferroptosis, followed by treatment with Cur (50, 25, 10, 5, 1, and 0.1 μM) for 24 h. Data is presented as mean ± SD (N=5). ***: (p < 0.001) for statistical significances between the Control and erastin or rsl-3 groups by non-paired Student’s t-test. ###: (p < 0.001) for statistical significances between the Control and Cur groups by non-paired Student’s t-test. (C) Malondialdehyde (MDA) levels tested by the using MDA assay kit at 530 nm wavelength (N=5). The MDA levels, represented as fold change of the levels measured in the control (Con) group, were utilized to reflect the extent of lipid peroxidation in kidneys. (D) The levels of iron were measured utilizing a tissue iron assay kit (N=5). Iron levels expressed as fold change of the levels measured in the Con group. Experimental data are presented as mean ± SD. Statistical significances (N=5): p < 0.05, *; p < 0.01, **. Each repeat was performed as a separate, independent experiment or observation.