Indole-3-propionic acid exacerbates cisplatin-induced chronic kidney disease through the AHR/NF-κB signaling pathway

Figures

• 

  Figure 1. Kidney function and injury in C57BL/6 mice following repeated cisplatin administration (A) Experimental design: Mice were intraperitoneally (i.p.) injected with either a 0.9% saline vehicle or cisplatin (9 mg/kg) once a week for a total of four weeks and euthanized on day 24. (B) Body weight measurements: The body weight of mice in the different treatment groups was monitored throughout the study. n = 6, Student’s t tests, with statistical significance determined by #p < 0.05, ##p < 0.01, and ###p < 0.001 versus controls. (C) Biochemical parameters: Graphical representations of SCr, BUN, UA, HDL, and LDL levels in the different experimental groups are shown. (D) Histological and fibrotic assessment: Representative micrographs depict kidney and colon histological alterations, with Sirius Red staining used to assess renal fibrosis. Scale bars, 100 μm. In the H&E staining result graph, arrows indicate the injured tubules and inflammatory cytokine infiltration; in the Sirius Red staining result graph, arrows indicate the collagen deposition positive staining. (E) Protein expression analysis: Western blotting was performed to evaluate the renal expression of biomarkers for kidney…

• 

  Figure 2. Repeated administration of cisplatin induces a dysbiosis shift in the microbiome of CKD mice (A) Boxplots depicting alpha diversity indices, including Shannon, Simpson reciprocal, Chao, and observed features, illustrating the diversity within the microbial communities. (B) PCoA of beta diversity, using Bray-Curtis dissimilarity metrics, to visualize group differences in microbiome composition. (C) Quantification of dissimilarity values based on Bray-Curtis distances, emphasizing the degree of variation between CKD and control groups. Data are represented as mean ± SEM, significant differences were determined by two-tailed Student’s t test, with statistical significance determined by ∗p < 0.05, ∗∗p < 0.01, and ∗∗∗p < 0.01 (n = 8). (D) Comparative analysis of the most differentially abundant microbial features at the phylum level between CKD and control mice (n = 8), highlighting specific shifts in microbial populations. (E) Linear discriminant analysis effect size (LEfSe) identifying key differentiating genera within the gut microbiota between CKD and control groups (LDA > 2). (F) KEGG pathway analysis comparing the metabolic functions of gut microbiota in CKD and control mice,…

• 

  Figure 3. Repeated cisplatin dosing induces dysbiosis metabolic alterations in CKD mice and association between microbiota and the levels of tryptophan metabolites in cisplatin-induced CKD in mice (A) Heatmap analysis revealing potential biomarkers of metabolic dysbiosis. (B) Pathway analysis of serum metabolites identified in the CKD and control groups. (C) Comparison of peak areas for potential tryptophan metabolism biomarkers between the control and CKD groups (n = 8). Columns display means ± SEM. ∗p < 0.05 versus controls; ∗∗p < 0.01 versus controls; ∗∗∗p < 0.001 versus controls. (D) Pearson correlation analysis of five potential tryptophan metabolites and intestinal bacteria at the genus level. (E) Correlation analysis between the levels of IPA and specific microbiota genera (Bifidobacterium, Escherichia_Shigella, Lactobacillus, and Clostridia_UGG_014).

• 

  Figure 4. IPA exacerbates CKD in mice and targeted metabolomics revealed alterations in serum tryptophan metabolites in CKD induced by repeated cisplatin administration, following supplementation with IPA (A) Schematic representation: Mice were intraperitoneally (i.p.) injected with either 0.9% saline (vehicle) or cisplatin (9 mg/kg) once a week for four weeks, and euthanized on day 24. IPA or vehicle treatment was administered three days prior to the cisplatin injection. (B) Body weight changes across the different experimental groups (n = 8). Statistical significance between the Control versus model (#), and model versus IPA (∗) groups was obtained by multiple comparison analysis at ### (∗∗∗) p < 0.001, ## (∗∗) p < 0.01, # (∗) p < 0.05. (C) Serum analysis: Graphs show the levels of SCr, BUN, UA, HDL, and LDL in the different groups, as indicated (n = 8). Significant differences were determined by one-way analysis of variance (ANOVA). #p < 0.05, ##p < 0.01, ###p < 0.001, compared with Control group. ∗p < 0.05, ∗∗p < 0.01, ∗∗∗p < 0.001, compared with CKD group. (D) Kidney histopathology: Representative micrographs depicting kidney histological alterations (H&E staining), renal fibrosis…

• 

  Figure 5. Targeted metabolomics revealed alterations in serum tryptophan metabolites in CKD induced by repeated cisplatin administration, following supplementation with IPA (A) UpSet plots of metabolites in metabolic of control, CKD and IPA-treated mice. (B) The disturbed tryptophan pathway in four comparison groups. (C) Metabolites within the kynurenine pathway and indole/AHR pathway are illustrated. Cisplatin-induced metabolites are marked in red, while metabolites regulated by IPA supplementation are highlighted in blue. Metabolites that remained unaffected by either cisplatin or IPA treatment are indicated by a horizontal line. (D) Representative analyses of targeted tryptophan metabolites, including indole-3-lactic acid, IPA, indole-3-carboxaldehyde, IAA, and methyl-3-indolylacetate, are shown. (E) Representative data from untargeted analysis of tryptophan metabolites. (F) A correlation network analysis was performed to examine the relationships between tryptophan metabolites and SCr and BUN levels in CKD mice. Statistical significance between the Control versus model (#), and model versus IPA (∗) groups was obtained by multiple comparison analysis at ### (∗∗∗) p < 0.001, ## (∗∗) p <…

• 

  Figure 6. Effect of IPA supplementation on the gut microbiota in CKD induced by repeated cisplatin dosing (A) Boxplot depicting alpha diversity, based on the Shannon and Chao indices. (B) PCoA utilizing Bray-Curtis distances to assess beta diversity. (C) Quantitative analysis of the most differentially abundant microbiota features at the class level in Model + IPA, Model, and Control groups. (D) Cladogram derived from LEfSe (Linear discriminant analysis Effect Size) analysis, illustrating microbial taxa differentiating the groups. (E) KEGG orthology (KO) analysis of the genomes involved in tryptophan metabolism in the gut microbiota of Control, IPA+ Model, and Model mice. (F) Relative abundances of tryptophan-metabolizing genomes and associated bacteria across groups. (G) Spearman’s correlation analysis between bacterial abundances and targeted tryptophan metabolites following IPA supplementation in CKD. Data significant differences were determined by one-way ANOVA, n = 8, #p < 0.05, ##p < 0.01, ###p < 0.001, compared with Control group. ∗p < 0.05, ∗∗p < 0.01, ∗∗∗p < 0.001, compared with CKD group.

• 

  Figure 7. Raman spectroscopy analysis in kidney tissues (A) Kidney Raman imaging for control, model and IPA treated group. (B) The average Raman spectra of each groups kidney tissues. (C) Analysis of the metabolites trend identified by Raman spectroscopy. Selective biochemical metabolites identified by Raman spectroscopy including L-tryptophan (1360 cm−1, 830 cm−1), indole (747 cm−1), and IPA (852 cm−1). Statistical significance between the Control versus model (∗), and model versus IPA (∗) groups was obtained by multiple comparison analysis at ∗∗∗p < 0.001, ∗∗p < 0.01, ∗p < 0.05, ns represented non-significant, n = 3.

• 

  Figure 8. Effects of IPA on the expression of key proteins in tryptophan metabolism pathways in cisplatin-induced CKD (A) Specific spatial distribution image of phenylalanylglutamic acid, tryptophol and IPA in the kidney. Data significant differences were determined by one-way ANOVA, n = 4, statistical significance between the Control versus model (#), and model versus IPA (∗) groups at ### (∗∗∗) p < 0.001, ## (∗∗) p < 0.01, # (∗) p < 0.05. (B and C) Immunofluorescence images of AHR and NF-KB p65 proteins across the three experimental groups. Scale bars, 100 μm (upper). (D) Quantitative analysis of relative intensity of tryptophan metabolites and relative expression levels of key proteins in each group. Data significant differences were determined by one-way ANOVA, n = 8, statistical significance between the Control versus model (#), and model versus IPA (∗) groups at ### (∗∗∗) p < 0.001, ## (∗∗) p < 0.01, # (∗) p < 0.05.

• 

  Figure 9. IPA repressed the AHR signaling pathway and inflammatory response in cisplatin-induced CKD (A) Protein expression of the AHR in the cytoplasm and nuclei of kidney tissues from control, model, and IPA-treated CKD mice at various doses. The detailed blots were shown in Data S1. (B) Quantitative analysis of key proteins involved in the NF-κB signaling pathway, including NF-κB p65, IκBα, IκBKB, p-NF-κB p65, p-IκBα, and the AHR target gene CYP1A1. Data are presented as mean ± SD (n = 6). Significant differences were determined by one-way ANOVA, statistical significance between the Control versus model (#), and model versus IPA (∗) groups at ###(∗∗∗) p < 0.001, ##(∗∗) p < 0.01, #(∗) p < 0.05.

• 

  Figure 10. IPA exacerbates cisplatin-induced CKD through the AHR/NF-κB signaling pathway (A) Immunohistochemical analysis of kidney tissue sections stained for MCP-1, TNF-α, F4/80+, and NF-κB p65 in the control, model, and IPA-treated CKD mice groups and quantitative analysis of MCP-1, TNF-α, F4/80+, and NF-κB p65 expression. Arrows indicate MCP-1 positive staining (upper panel) or TNF-α positive staining (middle panel) or F4/80+ positive staining (middle panel) or NF-κB p65 positive staining (lower panel). Scale bars, 100 μm. (B) Western blot analyses of key enzymes involved in kynurenine metabolism, including IDO-1, TDO-2, KMO, and KYAT3. The detailed blots were shown in Data S1. (C) Schematic representation of the mechanism by which IPA exacerbates CKD. IPA supplementation promotes dysregulation of tryptophan metabolism and alterations in the microbiome, leading to inhibition of AHR receptor activity and activation of the NF-κB signaling pathway. This cascade results in an enhanced inflammatory response in the kidneys, thereby exacerbating renal injury. Data significant differences were determined by one-way ANOVA, n = 6. Statistical significance between the Control versus model (#), and…