Investigating the Mechanisms of Jieduquyuziyin Prescription Improves Lupus Nephritis and Fibrosis via FXR in MRL/lpr Mice

Abstract

Lupus nephritis (LN) is one of the most serious complications of systemic lupus erythematosus (SLE) and one of the leading causes of death. An alternative effective treatment to ameliorate and relieve LN and delay the process of renal tissue fibrosis is urgently needed in the clinical setting. Jieduquyuziyin prescription (JP) has been successfully used to treat SLE, but its potential mechanisms are not sufficiently understood. In this study, we treated MRL/lpr mice with JP for 8 weeks and treated human renal tubular epithelial cells (human kidney 2 (HK-2)) with drug-containing serum to observe the antagonistic effects of JP on inflammation and fibrosis, as well as to investigate the possible mechanisms. Results demonstrated that JP significantly reduced urinary protein and significantly improved pathological abnormalities. Metabolomics combined with ingenuity pathway analysis illustrated that the process of kidney injury in lupus mice may be closely related to farnesoid X receptor (FXR) pathway abnormalities. Microarray biomimetic analysis and LN patients indicated that FXR may play a protective role as an effective therapeutic target for LN and renal fibrosis. JP significantly increased the expression of FXR and inhibited the expression of its downstream targets, namely, nuclear transcription factor κB (NF-κB) and α-smooth muscle actin (α-SMA), in the kidney of MRL/lpr mice and HK-2 cells, as confirmed by in vitro and in vivo experiments. In conclusion, JP may mediate the activation of renal FXR expression and inhibit NF-κB and α-SMA expression to exert anti-inflammatory and antifibrotic effects for LN prevention and treatment.

Figure 1

Composition of the traditional Chinese medicine JP. (a) Total ion flow diagram of UPLC-Q/TOF-MS (b) positive-ion and (c) negative-ion modes. (d) Identification of some components.

Figure 2

Urinary protein, serum autoantibody level, and renal pathology. The indices include urinary protein (a), anti-dsDNA antibody (b), and ANA (c). Renal histopathology (d) included periglomerular inflammatory cell infiltration (HE), glomerular mesangial hyperplasia (PASM), mesangial fibrosis (Masson), and glomerular IgG deposition (scale, 100 μm). The control group was MRL/MPJ mice and the model group was MRL/lpr mice. Data are expressed as the mean ± standard deviation (n = 6). ^#P < 0.05 and 0.01 versus the MPJ group; ^∗#P < 0.05, P < 0.05, and P < 0.01 versus the lpr group.

Figure 3

Serum metabolomics of mice with JP backregulated metabolites and metabolic pathway enrichment analysis. The differential metabolites of mouse serum were analyzed by chromatography–mass spectrometry, and the differential metabolites were screened in positive-ion (a) and negative-ion (b) modes and enriched for metabolic pathways (c). Data are expressed as the mean ± standard deviation (n = 6). ^#P < 0.05 and ^##P < 0.01 versus the MPJ group; ^∗P < 0.05 and ^∗∗P < 0.01 versus the lpr group.

Figure 4

Ingenuity pathway analysis and GEO database combined to analyze serum differential metabolite-related pathways and targets. IPA software was used to analyze the core pathways affected by differential metabolites between JP and lpr groups (a). GEO database was used to determine the differential expression of pathway-related proteins in lupus patients (b). Data are expressed as the mean ± standard deviation (n ≥ 3), ^∗∗P < 0.01.

Figure 5

Prediction of downstream inflammatory and fibrotic targets of FXR in LN. Combination of the downstream targets of FXR predicted using IPA software (a) with the disease target database of LN and differential genes from transcriptome sequencing to screen for possible downstream inflammatory targets of FXR by upset Venn diagram (b). Wenn plots (c) for screening FXR downstream fibrosis-related targets from GEO database, disease target database, and transcriptome-sequencing data for disease–target intersection analysis; they are presented by the heat map of transcriptome data (d). Box plots (e) showing the differential expression of the focused targets in GEO database. Data are expressed as the mean ± standard deviation (n ≥ 3), ^∗P < 0.05, ^∗∗P < 0.01.

Figure 6

NF-κB nuclear transfer decreased in the mouse kidney. The relationship between FXR and α-SMA regulation was investigated through in vitro experiments. WB results (a–c) demonstrated IκB phosphorylation and NF-κB nuclear transfer (n = 3). (d) Renal pathology of clinical lupus patients with FXR (red) and α-SMA (green) double staining (scale bar, 100 μm).

Figure 7

JP can increase FXR expression to suppress α-SMA expression at the transcriptional and protein levels. Mouse kidney fluorescence double-staining (a) results demonstrating FXR (red) and α-SMA (green) expression (scale bar, 100 μm). Mouse kidney tissue qPCR (n = 3) (b) and WB (n = 3) (c–e) results were consistent with the fluorescent double-staining results. ^∗∗P < 0.01.

Figure 8

ELISA detected (a, b) the contents of IL-6 and TNF-α in the supernatant of HK-2 cells transfected and treated with LPS (1 μg/mL, 6 h). Data are expressed as the mean ± standard deviation (n = 3), ^##P < 0.01 versus the blank group; ^∗P < 0.05, ^∗∗P < 0.01 versus the control group. (c–e) WB detection of transfected FXR overexpression or interfering RNA and protein expression of HK-2 cells after stimulation with 10% concentration drug-containing serum and treatment with TGF-β (20 ng/mL, 24 h). Data are expressed as the mean ± standard deviation (n = 3), ^∗P < 0.05, ^∗∗P < 0.01. WB result (f–h) observation of protein expression after transfection of siFXR or siα-SMA and treatment with TGF-β (20 ng/mL, 24 h). ^∗∗P < 0.01 versus the control group; ns: not statistically significant.

Figure 9

Mechanism diagram. JP decreased renal inflammation and fibrosis by increasing the expression of FXR protein in the kidney, thereby inhibiting its downstream NF-κB and α-SMA.