Integrative metabolomics and proteomics reveal the effect and mechanism of Zi Qi decoction on alleviating liver fibrosis

Abstract

Liver fibrosis is a common progressive liver disease that can cause liver dysfunction and lead to serious complications. Zi Qi decoction (ZQ) is a traditional formulation that exerts pharmacological effects on the treatment of liver fibrosis. However, precise intervention mechanisms remain unclear. The aim of this study was to synergistically harness proteomics and metabolomics techniques to elucidate the specific target of ZQ and its potential mechanism of action. A carbon tetrachloride (CCl₄)-induced liver fibrosis mouse model was established. Subsequently, the protective effect of ZQ on liver fibrosis mice was evaluated according to histopathological examination and biochemical indicators. Quantitative proteomics based on data independent acquisition (DIA) and non-targeted metabolomic analyses revealed the pharmacodynamic mechanism of ZQ. In addition, various cellular and molecular assays were used to detect changes in glycolysis levels in LSECs and mouse liver fibrosis models. The study results showed that ZQ significantly alleviated CCl₄-induced liver injury and fibrosis in mice. DIA-based quantitative proteomics and non-targeted metabolomics analyses indicated that ZQ treatment downregulated glycolysis-related proteins such as PKM2, PFKP, and HK2, while regulating glycolysis-related metabolites and pathways. In addition, ZQ down-regulated glycolytic activity in mice with liver fibrosis and in LSECs, and inhibited CXCL1 secretion and neutrophil recruitment. ZQ inhibited LSEC glycolysis and mitigated neutrophil infiltration, thereby playing a therapeutic role in liver fibrosis.

Keywords: Glycolysis; Liver fibrosis; Liver sinusoidal endothelial cell; Neutrophil infiltration; Zi Qi Decoction.

Fig. 1

Efficacy of ZQ in the treatment of liver injury and fibrosis. (A) The serum levels of ALT, AST, ALP, and TBIL in mice subjected to different treatments were determined using serology. (B) Serum levels of HA, LN, PC-III, and TBIL in mice subjected to different treatments were determined using serology. (C) H&E staining, Sirius red staining and Masson staining in liver tissues, scale bar: 100 μm. For statistical significance of this figure: Bars indicate mean ± standard error of the means, n = 6 per group; ### P < 0.001 compared to control and ** P < 0.01, *** P < 0.001 compared to model.

Fig. 2

Effect of ZQ on liver proteomics of CCl₄-induced liver fibrosis in mice. (A) The heatmap of the expression of liver proteins in the Control, Model, and ZQ groups. (B) Volcano plots showing the distribution of significance and fold change of identified proteins between the Control vs. Model and ZQ vs. Model groups. (C) Venn diagram summarising the differential and overlapping proteins among the Control vs. Model groups, ZQ vs. Model groups (FC > 1.5 or FC < 0.67, unpaired two-sided student’s t-tests, P < 0.05). (D) Clustering of the differentially expressed proteins. The differentially expressed proteins were assigned to two clusters by FCM clustering algorithm.

Fig. 3

Effect of ZQ on liver proteomics of CCl₄-induced liver fibrosis in mice. (A) The KEGG pathway analysis of the differentially expressed proteins. (P < 0.05).(B) The function analysis of the differentially expressed proteins in Metascape platform. (P < 0.01).

Fig. 4

ZQ inhibits glycolysis of CCl₄-induced liver fibrosis in mice. (A) Box plots depicting the relative protein expression levels of HK2, PFKP, and PKM2 in each group. (B) Western blot analysis revealed the protein expression of HK2, PFKP, and PKM2 in liver tissues from each group. GAPDH was used as a loading control. (C) The RT-qPCR results showed the mRNA expressions of HK2, PFKP, and PKM2 in the liver tissues from each group. β-Actin was used as a loading control. (D) Serum lactic acid levels in mice subjected to different treatments were detected using serological analysis. For statistical significance of this figure: bars indicate mean ± standard error of the means, n ≥ 3 per group; ## P < 0.01; ### P < 0.001 compared to control and ** P < 0.01; ***P < 0.001 compared to model.

Fig. 5

Effect of ZQ on liver metabolomics of CCl4-induced liver fibrosis in mice. (A and B) The OPLS-DA model and score plot for distinguishing the metabolites in the liver between the Control and Model groups. (C and D) The OPLS-DA model and score plot for distinguishing the metabolites in the liver between the Model and ZQ groups. (E) The upset plot for differentially expressed metabolites among the Control vs. Model groups, ZQ vs. Model groups. (F) The heatmap of the differential expression of liver metabolites in the three groups. (G) The box plots depict the differentially expressed metabolites in the three groups.

Fig. 6

Inhibition of ZQ on LSECs glycolysis. (A) Immunofluorescence analysis of PFKPB3 and LYVE1 in liver tissues. Cells were stained for DAPI (blue), LYVE1 (green), and PFKPB3 (red), scale bar: 50 μm. (B) Effect of ZQ drug-containing serum on cell viability was detected by CCK8 reagent. (C) Measurements of glucose consumption indicated by GOD activity. (D) Measurements of intracellular lactate levels. (E) Western blot analyses of protein expression of PKM2, PFKP, and HK2 with quantification. (F) Measurements of intracellular enzyme activities of PKM2, PFKP and HK2. For statistical significance of this figure: bars indicate mean ± standard error of the means, n ≥ 3 per group; ## P < 0.01; ### P < 0.001 compared to control and ** P < 0.01; *** P < 0.001 compared to model.

Fig. 7

Effect of ZQ on the CXCL1 secretion and neutrophil infiltration. (A) Immunohistochemistry analysis of CXCL1 in liver tissues; Scale bars: 100 μm. (B) The level of CXCL1 release in culture medium was evaluated using an ELISA kit. (C) Immunofluorescence analysis of MPO in liver tissues. Cells were stained for DAPI (blue) and MPO (green). Scale bars: 100 μm. (D) The expression levels of MPO in liver tissue were evaluated using a kit. For statistical significance of this figure: bars indicate mean ± standard error of the means, n ≥ 3 per group; ### P < 0.001 compared to control and ** P < 0.01; ***P < 0.001 compared to model.

Fig. 8

ZQ address liver fibrosis by modulating glycolysis of LSEC and inhibiting neutrophil infiltration.