Expression of IFN-Inducible Genes with Antiviral Function OAS1 and MX1 in Health and under Conditions of Recurrent Herpes Simplex Infection

Transcriptional Profiling of SARS-CoV-2-Infected Calu-3 Cells Reveals Immune-Related Signaling Pathways

The COVID-19 disease, caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), emerged in late 2019 and rapidly spread worldwide, becoming a pandemic that infected millions of people and caused significant deaths. COVID-19 continues to be a major threat, and there is a need to deepen our understanding of the virus and its mechanisms of infection. To study the cellular responses to SARS-CoV-2 infection, we performed an RNA sequencing of infected vs. uninfected Calu-3 cells. Total RNA was extracted from infected (0.5 MOI) and control Calu-3 cells and converted to cDNA. Sequencing was performed, and the obtained reads were quality-analyzed and pre-processed. Differential expression was assessed with the EdgeR package, and functional enrichment was performed in EnrichR for Gene Ontology, KEGG pathways, and WikiPathways. A total of 1040 differentially expressed genes were found in infected vs. uninfected Calu-3 cells, of which 695 were up-regulated and 345 were down-regulated. Functional enrichment analyses revealed the predominant up-regulation of genes related to innate immune response, response to virus, inflammation, cell proliferation, and apoptosis. These transcriptional changes following SARS-CoV-2 infection may reflect a cellular response to the infection and help to elucidate COVID-19 pathogenesis, in addition to revealing potential biomarkers and drug targets.

RNA sequencing analyses of gene expressions in a canine macrophages cell line DH82 infected with canine distemper virus

Virulent morbillivirus infections, including Meals Virus (MeV) and Canine Distemper Virus (CDV), caused severe immune suppression and leukopenia, while attenuated vaccine strains developed protective host immune responses. However, the detailed molecular foundations of host antiviral responses were poorly characterized. In order to better understand the interactions between attenuated vaccine and host antiviral responses, the global gene expression changes in CDV-11-infected DH82 cells, a macrophage-derived cell line from canine, were investigated by transcriptomic analysis, and portions of results were confirmed with quantitative RT-PCR. The results exhibited that 372 genes significantly up-regulated (p < .01) and 119 genes were significantly down-regulated (p < .01) in CDV-infected macrophages DH82 at 48 h p.i.. The enriched functions of the significantly up-regulated (p < .01) genes were closely associated with interferon stimulated genes (ISGs), chemokine genes and pro-inflammatory factor genes. Gene ontology and pathway analysis of differentially expressed genes (DEGs) revealed that the most significantly involved pathways in CDV-infected DH82 cells were NF-κB and TNF signaling pathway, cytokine-cytokine receptor interaction, and pathogen associated molecular patterns (PAMPs), such as Toll-like, RIG-I-like and NOD-like receptor signalings. Thus, the findings indicated that pattern recognition receptors (PRRs) possibly mediated host innate and protective antiviral immune responses in CDV-11 infected DH82 cells.

Comprehensive Analysis of Gene Expression Profiles and DNA Methylome reveals Oas1, Ppie, Polr2g as Pathogenic Target Genes of Gestational Diabetes Mellitus

Gestational Diabetes Mellitus (GDM) has a high incidence of pregnancy, which seriously affects the life quality of pregnant women and fetal health. DNA methylation is one of the most important epigenetic modification that can regulate the gene expression level, and thus affect the occurrence of various diseases. Increasing evidence has shown that gene expression changes caused by DNA methylation play an important role in metabolic diseases. Here we explored the mechanisms and biological processes that affect the occurrence and development of GDM through analyzing the gene expression profiles and DNA methylation data of GDM. We detected 24,577 differential CpG sites mapping to 9339 genes (DMGs, differential methylation gene) and 931 differential expressed genes (DEGs) between normal samples and GDM samples. GO (gene ontology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway analysis of 326 overlapping genes between DMGs and DEGs showed obvious enrichment in terms related to metabolic disorders and immune responses. We identified Oas1, Ppie, Polr2g as possible pathogenic target genes of GDM by combining protein-protein interaction analysis. Our study provides possible targets for early diagnosis of GDM and information for clinical prevention of abnormal fetal development and type 2 diabetes.