Inhibitory mechanisms of decoy receptor 3 in cecal ligation and puncture-induced sepsis

Abstract

Despite its high mortality, specific and effective drugs for sepsis are lacking. Decoy receptor 3 (DcR3) is a potential biomarker for the progression of inflammatory diseases. The recombinant human DcR3-Fc chimera protein (DcR3.Fc) suppresses inflammatory responses in mice with sepsis, which is critical for improving survival. The Fc region can exert detrimental effects on the patient, and endogenous peptides are highly conducive to clinical application. However, the mechanisms underlying the effects of DcR3 on sepsis are unknown. Herein, we aimed to demonstrate that DcR3 may be beneficial in treating sepsis and investigated its mechanism of action. Recombinant DcR3 was obtained in vitro. Postoperative DcR3 treatment was performed in mouse models of lipopolysaccharide- and cecal ligation and puncture (CLP)-induced sepsis, and their underlying molecular mechanisms were explored. DcR3 inhibited sustained excessive inflammation in vitro, increased the survival rate, reduced the proinflammatory cytokine levels, changed the circulating immune cell composition, regulated the gut microbiota, and induced short-chain fatty acid synthesis in vivo. Thus, DcR3 protects against CLP-induced sepsis by inhibiting the inflammatory response and apoptosis. Our study provides valuable insights into the molecular mechanisms associated with the protective effects of DcR3 against sepsis, paving the way for future clinical studies.

Importance: Sepsis affects millions of hospitalized patients worldwide each year, but there are no sepsis-specific drugs, which makes sepsis therapies urgently needed. Suppression of excessive inflammatory responses is important for improving the survival of patients with sepsis. Our results demonstrate that DcR3 ameliorates sepsis in mice by attenuating systematic inflammation and modulating gut microbiota, and unveil the molecular mechanism underlying its anti-inflammatory effect.

Keywords: anti-inflammatory; decoy receptor 3; gut microbiota; sepsis.

Fig 1

Effects of DcR3 on LPS-stimulated RAW264.7 cells and mice with LPS-induced sepsis. (A) Effect of DcR3 treatment (0–1.0 µg/mL) on cell viability. (B–G) RAW264.7 cells were pretreated with DcR3 treatment (0–2.0 µg/µL) and stimulated with LPS. (B–D) The mRNA levels of the cytokines IL-6, TNF-α, and IL-1β in RAW264.7 cells were measured using qPCR. (E–G) The levels of inflammatory cytokines (E) IL-1β, (F) IL-6, and (G) TNF-α determined using ELISA. (H) Effect of DcR3 on the survival of the Sham group (n = 10). (I) Effect of DcR3 on the expression levels of inflammatory factors in the serum of the Sham (S) group and Sham + DcR3 (S + D) group (n = 10). (J–L) Changes in mRNA levels of cytokines IL-6, TNF-α, and IL-1β in RAW264.7 cells following DcR3 treatment alone or co-treatment with LPS using qPCR. (M–O) Changes in the LPS-induced septic mice serum levels of inflammatory cytokines (M) IL-1β, (N) IL-6, and (O) TNF-α determined using ELISA at 12 h after DcR3 and DcR3.Fc treatment. ANOVA and Tukey’s post hoc test were used to analyze the data. (∗) P < 0.05, (∗∗) P < 0.01, (∗∗∗) P < 0.001, and (∗∗∗∗) P < 0.0001. An independent experiment was conducted thrice to produce the results.

Fig 2

DcR3 displayed a significant therapeutic effect in mice with CLP-induced sepsis. (A) Experimental procedure timeline for generating CLP-induced sepsis mouse model. (B) Typical behavioral changes in septic mice after 12 h of DcR3 treatment. (C) The murine sepsis score (MSS) in septic mice (n = 6). (D) Effect of DcR3 on the survival of septic mice (n = 30). (E) Effect of DcR3 treatment on body temperature in septic mice. Data were statistically analyzed using the Mantel-Cox test (B), and two-way ANOVA followed by Bonferroni’s post hoc test (C–E). (∗) P < 0.05, (∗∗) P < 0.01, (∗∗∗) P < 0.001, and (∗∗∗∗) P < 0.0001. Sample sizes are indicated in brackets.

Fig 3

DcR3 treatment reduced the expression levels of inflammatory factors in the serum of CLP-induced septic mice. (A–C) DcR3 treatment in CLP-induced septic mice at 12 h. (A) IL-1β, (B) IL-6, and (C) TNF-α. (D–F) DcR3 treatment of CLP-induced septic mice at 24 h. (D) IL-1β, (E) IL-6, and (F) TNF-α. ANOVA and Tukey’s post hoc test were used to analyze the data. (∗) P < 0.05, (∗∗) P < 0.01, (∗∗∗) P < 0.001, and (∗∗∗∗) P < 0.0001. An independent experiment was conducted thrice to produce the results.

Fig 4

DcR3 exerts protective effects against the lung, liver, and heart tissue lesions in CLP-induced septic mice at 12 and 24 h (scale bars = 50 µm). Representative microscopic images of the (A, B) lung, (C, D) liver, and (E, F) renal tissues of mice with CLP-induced sepsis after hematoxylin and eosin (H&E) staining (magnification, 200×). Pathological scores of the (B) lung, (D) liver, and (F) renal tissues of CLP-induced septic mice. Data are expressed as mean ± standard deviation. (∗∗∗∗) P < 0.0001; ns, not significant (P > 0.05). An independent experiment was conducted five times to produce the results.

Fig 5

Effect of DcR3 treatment on immune cells in CLP-induced septic mice. (A–D) White blood cells (WBC), monocytes (Mon), granulocytes (Gran), and lymphocytes (LymPh) in peripheral blood were analyzed at 12 h after DcR3 administration in CLP-induced septic mice (n = 3). (E) Flow chart and detection markers of NK and activated NK cells using flow cytometry in CLP-induced septic mice at 12 h (n = 12). (F) Number of NK cells at 12 h. ANOVA and Tukey’s post hoc test were performed to analyze the data. (∗) P < 0.05, (∗∗) P < 0.01, (∗∗∗) P < 0.001, and (∗∗∗∗) P < 0.0001; ns, not significant (P > 0.05). Sample sizes are indicated in brackets.

Fig 6

The role of DcR3 in restoring intestinal morphology and barrier function in CLP-induced sepsis mice. (A) Representative HE-stained histological sections. The scale bars are shown in the figure. (B, C) Relative mRNA expression of Cldn1 and Ocln. (D) Western blotting to measure the protein expression levels of Claudin-1 and Occludin in colon tissue after 12 h of DcR3 (1 mg/kg) treatment. (E, F) Densitometric analysis of bands via ImageJ software. Details the relative protein levels of Claudin-1 and Occludin. Data are expressed as mean ± standard deviation and analyzed using ANOVA and Tukey’s post hoc test. Statistical significance is denoted by (∗) P < 0.05, (∗∗) P < 0.01, (∗∗∗) P < 0.001, and (∗∗∗∗) P < 0.0001; ns, not significant (P > 0.05).

Fig 7

DcR3 remodels the intestinal microbiota homeostasis in CLP-induced septic mice. (A) Venn diagram showing OTUs of intestinal microorganisms. (B, C) Alpha diversity analysis of intestinal microbiota at the OTU level. (B) Shannon and (C) Simpson indices. (D, E) Beta diversity analysis of the intestinal microbiota at the OTU level. (D) Beta diversity PCoA plots based on weighted UniFrac Adonis analysis in distinct groups. (E) Beta diversity based on weighted UniFrac ANOSIM analysis in distinct groups. (F) Histogram showing species distribution at the genus level. (G) Heat map analysis of the relative abundance of intestinal microorganisms in the distinct groups at the genus level. Relative abundance of (H) Alloprevotella, (I) Lachnospiraceae_NK4A136_group, (J) Parabacteroides, (K) uncultured_bacterium_f_Muribaculaceae, (L) Bacillus, (M) Klebsiella, (N) Morganella, and (O) Streptococcus. The value corresponding to the heat map is the Z-value obtained after the standardization of the relative abundance of species in each row. ANOVA and Tukey’s post hoc test were performed to analyze the data. (∗) P < 0.05, (∗∗) P < 0.01, (∗∗∗) P < 0.001, and (∗∗∗∗) P < 0.0001; ns, not significant (P > 0.05). An independent experiment was conducted five to produce the results.

Fig 8

Correlation between intestinal microbiota and environmental factors in CLP-induced septic mice after DcR3 treatment. Effects of DcR3 on (A) acetic, (B) butyric, and (C) propionic acid levels produced by intestinal microorganisms in CLP-induced septic mice (n = 5). (D) Spearman’s rank correlation heat map among bacterial genera, levels of SCFAs, and serum, as well as levels of IL-6, IL-1β, and TNF-α in the lungs of WT mice and CLP-induced septic mice. (E) Redundancy analysis/canonical correspondence analysis between bacterial genera and levels of SCFAs in CLP-induced septic mice. Data are expressed as mean ± standard deviation. ANOVA and Tukey’s post hoc test were performed to analyze the data. (∗) P < 0.05, (∗∗) P < 0.01, (∗∗∗) P < 0.001, and (∗∗∗∗) P < 0.0001; ns, not significant (P > 0.05). An independent experiment was conducted five to produce the results.

Fig 9

Impact of DcR3 on NF-κB and caspase pathways in septic mice induced by CLP. (A–F) Analysis of gene profiles in septic mice post-CLP with DcR3 treatment. (A) Clustered heatmap detailing gene expression in Sham, CLP and DcR3-treated septic mice. (B) DEG heatmap in Sham, CLP and DcR3-treated septic mice. (C) KEGG analysis of DEGs in Sham, CLP and DcR3-treated septic mice (Sham vs CLP and CLP vs CLP + DcR3). (D) GO enrichment of DEGs (P < 0.05). (E) Volcano plot showcasing DEGs post-DcR3 treatment compared with those in CLP-induced septic mice (CLP vs CLP + DcR3; downregulated genes, blue; upregulated genes, red; insignificantly altered genes, black). (F) Identification of protein interaction networks among TNF, NF-κB, and Bcl2 using the STRING database. (G) Effect of DcR3 treatment on FasL, LIGHT, and TL1A in CLP-induced septic mice. (H) Western blotting to assess MyD88, NF-κB (P65) and p-NF-κB (P-P65) protein levels in lung homogenates after 12 h of DcR3 (1 mg/kg) treatment. (I) Western blotting to measure the protein expression levels of cleaved caspase 3, pro-caspase 3, cleaved caspase 8, pro-caspase 8, Bcl-2, and TNFSF10 in lung homogenates after 12 h of DcR3 (1 mg/kg) treatment. (G–I) Densitometric analysis of bands via ImageJ software. (J) p-NF-κB (P-P65) levels in lung tissues determined through immunohistochemistry. Scale bar  =  50  µm. Data are presented as mean ± standard deviation (n = 3). ANOVA and Tukey’s post hoc test was performed to analyze the data. (∗∗) P < 0.01, (∗∗∗) P < 0.001, and (∗∗∗∗) P < 0.0001.