IFNA2 p.Ala120Thr impairs the inhibitory activity of Interferon-α2 against the hepatitis B virus through altering its binding to the receptor

Roles of APOBEC3 in hepatitis B virus (HBV) infection and hepatocarcinogenesis

APOBEC3 (A3) cytidine deaminases inhibit hepatitis B virus (HBV) infection and play vital roles in maintaining a variety of biochemical processes, including the regulation of protein expression and innate immunity. Emerging evidence indicates that the deaminated deoxycytidine biochemical activity of A3 proteins in single-stranded DNA makes them a double-edged sword. These enzymes can cause cellular genetic mutations at replication forks or within transcription bubbles, depending on the physiological state of the cell and the phase of the cell cycle. Under pathological conditions, aberrant expression of A3 genes with improper deaminase activity regulation may threaten genomic stability and eventually lead to cancer development. This review attempted to summarize the antiviral activities and underlying mechanisms of A3 editing enzymes in HBV infections. Moreover, the correlations between A3 genes and hepatocarcinogenesis were also elucidated.

NLRX1 can counteract innate immune response induced by an external stimulus favoring HBV infection by competitive inhibition of MAVS-RLRs signaling in HepG2-NTCP cells

INTRODUCTION

This study is aimed at the determination of the effect of the immune-regulatory factor NLRX1 on the antiviral activity of hepatocytes against an external stimuli favoring hepatitis B virus infection, and to explore its mechanism of action.

METHODS

A HepG2-NTCP model was established using the LV003 lentivirus. Cells were transfected using an overexpression vector and NLRX1 siRNA to achieve overexpression and interference of NLRX1 expression (OV-NLRX1, si-NLRX1). Levels of HBsAg and HBcAg were determined using Western blotting analysis and immunohistochemical analysis. The levels of hepatitis B virus DNA and hepatitis B virus cccDNA were determined by real-time quantitative polymerase chain reaction. The expression and transcriptional activity of IFN-α, IFN-β, and IL-6 were measured using real-time quantitative polymerase chain reaction, enzyme-linked immunosorbent assay, and promoter-luciferase reporter plasmids. Co-immunoprecipitation was used to determine the effect of NLRX1 on the interaction between MAVS and RIG-1. Western blotting was used to obtain the phosphorylation of essential proteins in the MAVS-RLRs signaling pathways.

RESULTS

NLRX1 promoted HepG2-NTCP cell hepatitis B virus infection. Compared to the control group, the levels of HBsAg, HBcAg, hepatitis B virus cccDNA, and hepatitis B virus DNA increased in the OV-NLRX1 group and decreased in the si-NLRX1. Co-immunoprecipitation results showed that NLRX1 competitively inhibited the interaction between MAVS and RIG-1, and inhibited the phosphorylation of p65, IRF3, and IRF7. Additionally, NLRX1 reduced the transcription activity and expression levels of the final products: IFN-α, IFN-β, and IL-6.

CONCLUSIONS

NLRX1 can counteract innate immune response induced by an external stimuli favoring hepatitis B virus infection by competitive inhibition of MAVS-RLRs signaling in HepG2-NTCP cells. Inhibition of the MAVS-RLR-mediated signaling pathways leads to a decline in the expression levels of I-IFN and IL-6.

Identification of potential mRNA panels for severe acute respiratory syndrome coronavirus 2 (COVID-19) diagnosis and treatment using microarray dataset and bioinformatics methods

The goal of the present investigation is to identify the differentially expressed genes (DEGs) between SARS-CoV-2 infected and normal control samples to investigate the molecular mechanisms of infection with SARS-CoV-2. The microarray data of the dataset E-MTAB-8871 were retrieved from the ArrayExpress database. Pathway and Gene Ontology (GO) enrichment study, protein–protein interaction (PPI) network, modules, target gene–miRNA regulatory network, and target gene–TF regulatory network have been performed. Subsequently, the key genes were validated using an analysis of the receiver operating characteristic (ROC) curve. In SARS-CoV-2 infection, a total of 324 DEGs (76 up- and 248 down-regulated genes) were identified and enriched in a number of associated SARS-CoV-2 infection pathways and GO terms. Hub and target genes such as TP53, HRAS, MAPK11, RELA, IKZF3, IFNAR2, SKI, TNFRSF13C, JAK1, TRAF6, KLRF2, CD1A were identified from PPI network, target gene–miRNA regulatory network, and target gene–TF regulatory network. Study of the ROC showed that ten genes (CCL5, IFNAR2, JAK2, MX1, STAT1, BID, CD55, CD80, HAL-B, and HLA-DMA) were substantially involved in SARS-CoV-2 patients. The present investigation identified key genes and pathways that deepen our understanding of the molecular mechanisms of SARS-CoV-2 infection, and could be used for SARS-CoV-2 infection as diagnostic and therapeutic biomarkers.