Roles of interferon induced protein with tetratricopeptide repeats (IFIT) family in autoimmune disease

RNAseq of Gingival Fibroblasts Exposed to PRF Membrane Lysates and PRF Serum

Platelet-rich fibrin (PRF) is prepared by spontaneous coagulation of fractionated blood. When squeezed between two plates, PRF is separated into solid PRF membranes and a liquid exudate, the PRF serum. The question arises regarding how much the overall activity remains in the PRF membranes and what is discarded into the PRF serum. To this end, we have exposed gingival fibroblasts to lysates prepared from PRF membranes and PRF serum, followed by bulk RNA sequencing. A total of 268 up- and 136 down-regulated genes in gingival fibroblasts exposed to PRF membrane lysates were significantly regulated under the premise of a minimum log2 with 2.5-fold change and a minus log10 significance level of two, respectively. PRF serum only caused 62 up- and 32 down-regulated genes under these conditions. Among the 46 commonly up-regulated genes were CXCL1, CXCL5, CXCL6, CXCL8, IL33, IL6, and PTGS2/COX2, stanniocalcin-1-all linked to an inflammatory response. PRF membrane lysates further increased chemokines CCL2, CCL7, CXCL2, CXCL3, and IL1R1, IL1RL1, and IL1RN, as well as the paracrine factors IL11, LIF, IGF1, BMP2, BMP6, FGF2, and CCN2/CTGF, and all hyaluronan synthases. On the other hand, PRF serum increased DKK1. The genes commonly down-regulated by PRF membrane lysates and PRF serum included interferon-induced protein with tetratricopeptide repeats (IFIT1, IFIT2, IFIT3) and odd-skipped-related transcription factors (OSR1 and OSR2), as well as FGF18 and GDF15, respectively. Taken together, PRF membrane lysates, compared to PRF serum, cause a more complex response in gingival fibroblasts, but each increased chemokine expression in gingival fibroblasts.

Bacillus cereus CwpFM induces colonic tissue damage and inflammatory responses through oxidative stress and the NLRP3/NF-κB pathway

Bacillus cereus (B. cereus) from cow milk poses a threat to public health, causing food poisoning and gastrointestinal disorders in humans. We identified CwpFM, an enterotoxin from B. cereus, caused oxidative stress and inflammatory responses in mouse colon and colonic epithelial cells. Colon proteomics revealed that CwpFM elevated proteins associated with inflammation and oxidative stress. Notably, CwpFM induced activation of the NLRP3/NF-κB signaling, but suppressed antioxidant NFE2L2/HO-1 expression in the intestine and epithelial cells. Consistently, CwpFM exposure led to cytotoxicity and ROS accumulation in Caco-2 cells in a dose-dependent manner. Further, NAC (ROS inhibitor) treatment abolished NLRP3/NF-κB activation due to CwpFM. Moreover, overexpression of Nfe2l2 or activation of NFE2L2 by NK-252 reduced ROS production and inhibited activation of the NLRP3/NF-κB pathway. Inhibition of NF-κB by ADPC and/or suppression of NLRP3 by MCC950 attenuated CwpFM-induced inflammatory responses in Caco-2 cells. Collectively, CwpFM induced oxidative stress and NLRP3/NF-κB activation by inhibiting the NFE2L2/HO-1 signaling and ROS accumulation, leading to the development of intestinal inflammation. Our data elucidate the role of oxidative stress and innate immunity in CwpFM enterotoxicity and contribute to developing diagnostic and therapeutic products for B. cereus-related food safety issues.

The Role of Interferon-Induced Proteins with Tetratricopeptide Repeats 1 and 2 in Sepsis-Induced Acute Liver Injury

Background

Sepsis refers to a life-threatening organ dysfunction which can be resulted from the infection-induced dysregulated host response. A large number of inflammatory cytokines are released to act on the liver, making the liver one of the common target organs for the development of multiple organ dysfunction syndrome (MODS) in patients with sepsis. Sepsis-induced acute liver injury (SALI) can aggravate systemic disease. As a result, it is of great clinical significance to comprehend the molecular biological mechanism of SALI and to identify the markers for evaluating SALI. Interferon-induced proteins with tetratricopeptide repeats 1 and 2 (IFIT1, IFIT2) have been recognized as the anti-inflammatory factors that are widely expressed in various organs. The present study was aimed at clarifying the roles of IFIT1 and IFIT2 in the development of SALI.

Methods

A two-sample Mendelian randomization (MR) analysis was employed. Summary statistics datas were obtained from GWAS for inflammatory factors [tumor necrosis factor (TNF-α), interleukin-1β (IL-1β), and interleukin-6 (IL-6)], IFIT2, and sepsis as well as liver injury. Independent SNPs were selected as instrumental variables (IVs). Inverse variance weighted (IVW) in the MR analysis was adopted as the primary method for estimating the causal associations of inflammatory factors and IFIT2 with two diseases, and the associations of inflammatory factors with IFIT2. Additionally, weighted median method, MR-Egger and sensitivity analyses were applied in assessing the robustness of the results and ensure the result reliability. Subsequently, 119 healthy volunteers, 116 patients with sepsis and 116 SALI patients were recruited. The ELISA method was employed to quantify the expression levels of TNF-α, IL-1β, and IL-6. Additionally, qRT-PCR was conducted to measure the expression of IFIT1 and IFIT2. Furthermore, the correlations of IFIT1 and IFIT2 with inflammatory factors, alanine aminotransferase (ALT) and aspartate aminotransferase (AST) were explored.

Results

As shown by the MR analysis, the genetically predisposed sepsis was significantly associated with the risk of IL-1β, with an odds ratio (OR) of 1.069 (95% confidence interval (CI), 1.015-1.127, p = 0.0119), and negatively associated with the risk of IL-6, with an OR of 0.880 (95% CI: 0.792-0.979, p= 0.0184). Meanwhile, there were positive causal effects of IL-6 (OR = 1.269, 95% CI: 1.032-1.561, p= 0.0238), IL-1β (OR = 1.106, 95% CI: 1.010-1.211, p = 0.0299) and IFIT2 (OR = 1.191, 95% CI: 1.045-1.359, p = 0.0090) on liver injury. Additionally, there was a positive causal effect of IFIT2 (OR = 1.164, 95% CI: 1.035-1.309, p= 0.0110) on IL-1β. Upon sensitivity analyses, there was weak evidence of such effects, indicating that the findings of this study were robust and reliable. Our results revealed the elevated levels of TNF-α, IL-1β, and IL-6 in the blood samples of sepsis and SALI patients (p < 0.0001). Conversely, IFIT1 and IFIT2 demonstrated the significantly decreased levels in peripheral blood mononuclear cells (PBMCs) of SALI patients (p < 0.0001). Furthermore, the expression levels of IFIT1 and IFIT2 were both negatively correlated with ALT activity (r = -0.3426, p = 0.0002; r = -0.3069, p = 0.0008) and AST activity (r = -0.2483, p = 0.0072; r = -0.3261, p = 0.0004), respectively. Moreover, the expression of IFIT1 and IFIT2 was both negatively related to the levels of TNF-α (r = -0.5027, p < 0.0001; r = -0.4218, p < 0.0001), IL-1β (r = -0.3349, p = 0.0002; r = -0.4070, p < 0.0001) and IL-6 (r = -0.2734, p = 0.0030; r = -0.3536, p < 0.0001), respectively.

Conclusion

IFIT1 and IFIT2 can serve as the diagnostic markers for sepsis-related liver injury, and IFIT1 and IFIT2 may participate in the pathological process of sepsis-related liver injury by regulating inflammation and liver function.

Discovery of Potential Drug Targeting Key Genes in Alzheimer's Disease: Insights from Transcriptome Analysis and Molecular Docking

Alzheimer's disease (AD) is a prevalent neurodegenerative disorder that presents a significant global health challenge. To explore drugs targeting key genes in AD, R software was used to analyze the data of single nuclei transcriptome from human cerebral frontal cortex in AD, and the differentially expressed genes (DEGs) were screened. Then the gene ontology (GO) analysis, Kyoto gene and genome encyclopedia (KEGG) pathway enrichment and protein-protein interaction (PPI) network were analyzed. The hub genes were calculated by Cytoscape software. Molecular docking and molecular dynamics simulation were used to evaluate and visualize the binding between candidate drugs and key genes. A total of 564 DEGs were screened, and the hub genes were ISG15, STAT1, MX1, IFIT3, IFIT2, RSAD2, IFIT1, IFI44, IFI44L and DDX58. Enrichment terms mainly included response to virus, IFN-γ signaling pathway and virus infection. Diclofenac had good binding effect with IFI44 and IFI44L. Potential drugs may act on key gene targets and then regulate biological pathways such as virus response and IFN-γ-mediated signal pathway, so as to achieve anti-virus, improve immune balance and reduce inflammatory response, and thus play a role in anti-AD.

Integrated analysis of single-cell RNA-seq and chipset data unravels PANoptosis-related genes in sepsis

Background

The poor prognosis of sepsis warrants the investigation of biomarkers for predicting the outcome. Several studies have indicated that PANoptosis exerts a critical role in tumor initiation and development. Nevertheless, the role of PANoptosis in sepsis has not been fully elucidated.

Methods

We obtained Sepsis samples and scRNA-seq data from the GEO database. PANoptosis-related genes were subjected to consensus clustering and functional enrichment analysis, followed by identification of differentially expressed genes and calculation of the PANoptosis score. A PANoptosis-based prognostic model was developed. In vitro experiments were performed to verify distinct PANoptosis-related genes. An external scRNA-seq dataset was used to verify cellular localization.

Results

Unsupervised clustering analysis using 16 PANoptosis-related genes identified three subtypes of sepsis. Kaplan-Meier analysis showed significant differences in patient survival among the subtypes, with different immune infiltration levels. Differential analysis of the subtypes identified 48 DEGs. Boruta algorithm PCA analysis identified 16 DEGs as PANoptosis-related signature genes. We developed PANscore based on these signature genes, which can distinguish different PANoptosis and clinical characteristics and may serve as a potential biomarker. Single-cell sequencing analysis identified six cell types, with high PANscore clustering relatively in B cells, and low PANscore in CD16+ and CD14+ monocytes and Megakaryocyte progenitors. ZBP1, XAF1, IFI44L, SOCS1, and PARP14 were relatively higher in cells with high PANscore.

Conclusion

We developed a machine learning based Boruta algorithm for profiling PANoptosis related subgroups with in predicting survival and clinical features in the sepsis.