SMURF1 activates the cGAS/STING/IFN-1 signal axis by mediating YY1 ubiquitination to accelerate the progression of lupus nephritis

Aggravated endoplasmic reticulum stress (ERS) and apoptosis in podocytes play an important role in lupus nephritis (LN) progression, but its mechanism is still unclear. Herein, the role of SMURF1 in regulating podocytes apoptosis and ERS during LN progression were investigated. MRL/lpr mice was used as LN model in vivo. HE staining was performed to analyze histopathological changes. Mouse podocytes (MPC5 cells) were treated with serum IgG from LN patients (LN-IgG) to construct LN model in vitro. CCK8 assay was adopted to determine the viability. Cell apoptosis was measured using flow cytometry and TUNEL staining. The interactions between SMURF1, YY1 and cGAS were analyzed using ChIP and/or dual-luciferase reporter gene and/or Co-IP assays. YY1 ubiquitination was analyzed by ubiquitination analysis. Our results found that SMURF1, cGAS and STING mRNA levels were markedly increased in serum samples of LN patients, while YY1 was downregulated. YY1 upregulation reduced LN-IgG-induced ERS and apoptosis in podocytes. Moreover, SMURF1 upregulation reduced YY1 protein stability and expression by ubiquitinating YY1 in podocytes. Rescue studies revealed that YY1 knockdown abrogated the inhibition of SMURF1 downregulation on LN-IgG-induced ERS and apoptosis in podocytes. It was also turned out that YY1 alleviated podocytes injury in LN by transcriptional inhibition cGAS/STING/IFN-1 signal axis. Finally, SMURF1 knockdown inhibited LN progression in vivo. In short, SMURF1 upregulation activated the cGAS/STING/IFN-1 signal axis by regulating YY1 ubiquitination to facilitate apoptosis in podocytes during LN progression.</p

SLE signature comparison.

<p>SLE signature comparison.</p

Pathway analysis of SLEmetaSig100 genes.

<p>Pathway analyses of SLEmetaSig100 genes identified genes involving DNA sensors and the cytokines constructing an innate immune DNA-sensor model. SLEmetaSig100 genes are marked in white circles or rectangles. DNA sensors include MB21D1(cGAS), multiple TLR genes, TMEM173/STING, and IF16 genes. In the Toll-like receptor signaling pathway, the stimulation of DNA sensor genes by microbe-derived and/or host DNA are positively regulated by MYD88 and TMEM173/STING genes and negatively regulated by TREX1 and TREX2 genes. The downstream cytokine-cytokine receptor interaction genes include NF-kappa B signaling pathway mediated IFNs, inflammatory cytokines (e.g. IL1R1), and STATs mediated chemokines (CXCL and CXCR genes).</p

Receiver operating characteristic (ROC) curves for SLEmetaSig100.

<p>Area under receiver operating characteristic curve (AUC) for performance of SLEmetaSig100 were calculated in two testing cohorts, GSE65391(solid line) and GSE11909(dash line), and SLEmetaSig100 significantly outperforms the random prediction of SLE disease (AUC, 0.89 in GSE65391 and 0.85 in GSE11909). The sub-table shows SLEmetaSig100 prediction performance in two test datasets. *Note: SLE prediction by SLEmetaSig100 in two test data sets was examined by Fisher Exact test (P value = 1.48E-36).</p

Co-expression analysis of the 100 meta-signature genes from the SLE training data sets.

<p>Using EXALT meta-analysis, thirteen SLE signatures in columns with similar phenotypes indicated in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0198325#pone.0198325.s004" target="_blank">S1 Table</a> were displayed in a heat map with 100 genes (SLEmetaSig100) displayed in rows. The colors in the meta-heat map represent the direction of differential gene expression within a given transcriptional profile (red for up, green for down, and black for a missing match). Color intensity reflects the confidence levels of differential expression in the signatures.</p