MRNA microarray analysis of gene changes in Huh7 cells treated with IFN-λ4, IFN-λ1 and IFN-α
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE83085 | GEO | 2016/08/08
SECONDARY ACCESSION(S): PRJNA324708
REPOSITORIES: GEO
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Project description:The change of gene expression in Huh7 cells treated with IFN-λ4, IFN-λ1 and IFN-α was analyzed at 0h, 6h and 16h after different interferon treatments. Huh7 cells that had been treated with IFN-α (10 IU/ml), IFN-λ1 (20 ng/ml) and IFN-λ4 (20 ng/ml). Time points of 6 h and 16 h after stimulation were selected.
2016-08-08 | E-GEOD-83085 | biostudies-arrayexpress
Project description:Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that causes Coronavirus disease 2019 (COVID-19) has caused a global health emergency. A key feature of COVID-19 is dysregulated Interferon-response. Type-I interferon (IFN-I) is one of the earliest antiviral innate immune responses following viral infection and plays a significant role in pathogenesis of SARS-CoV-2. In this study, using a proteomics-based approach, we identified that SARS-CoV-2 infection induces delayed and dysregulated IFN-I signaling in Huh7 cells. We demonstrate that SARS-CoV-2 is able to inhibit RIG-I mediated IFN- production. Our results also confirm the recent findings that IFN-I pretreatment is able to reduce susceptibility of Huh7 cells to SARS-CoV-2, but not post-treatment. Senescent Huh7 cells in spite of showing accentuated IFN-I response were more susceptible to SARS-CoV-2 infection and SARS-CoV-2 effectively inhibited IFIT1 in these cells. Proteomic comparison between SARS-CoV-2, SARS-CoV and MERS-CoV revealed a distinct differential regulatory signature of interferon-related proteins emphasizing that therapeutic strategies based on observations in SARS-CoV and MERS-CoV should be used with caution. Our findings provide a better understanding of SARS-CoV-2 regulation of cellular interferon response and a perspective on its use as a treatment. Characterization of the role of different interferon stimulated genes on the inhibition of SARS-CoV-2 pathogenesis may direct novel antiviral strategies.
2021-05-18 | PXD023450 | Pride
Project description:Objective: Patients with Systemic Lupus Erythematosus (SLE) have an ongoing interferon (IFN) production due to an activation of plasmacytoid dendritic cells (pDCs), which can be triggered to type I IFN synthesis by RNA containing immune complexes (RNA-IC). Considering emerging data suggesting a role of type III interferon (IFN) in the SLE disease process, we asked if RNA-IC can induce type III IFN production in pDC, and how this production can be regulated. Methods: Peripheral blood mononuclear cells (PBMCs) or immune cell subsets were isolated from healthy blood donors or SLE patients and stimulated with IC containing U1 snRNP and SLE-IgG (RNA-IC). Hydroxychloroquine (HCQ) and an interleukin receptor 1 associated kinase 4 inhibitor (IRAK4i) were added to cell cultures. Cytokine mRNA levels were determined with a microarray and protein levels with immunoassays. Single-cell RNA-sequencing of pDCs using ddSEQ technology was performed. Results: Type III IFN mRNA and protein was induced in RNA-IC stimulated pDC-NK and pDC-B cell co-cultures. A subset of activated pDCs (3%) expressed both type III and type I IFN mRNA. IFN-λ2, IFN-α2b, interleukin (IL)-3, IL-6 or granulocyte-macrophage colony stimulating factor (GM-CSF) enhanced IFN-λ1/3 production 2-5-fold. HCQ and an IRAK4i blocked the RNA-IC-triggered IFN-λ1/3 production (p<0.01). IFN-α2b and GM-CSF increased the proportion of SLE patients producing IFN-λ1/3 in response to RNA-IC from 11 to 33%. Conclusions: Type III IFN production is triggered by RNA-IC in pDCs in a TLR-MyD88-dependent manner, enhanced by NK and B cells as well as several pro-inflammatory cytokines. These results support a contributing role for both type I and type III IFNs in SLE, which needs to be considered when targeting the IFN system in this disease.
2020-05-23 | GSE149415 | GEO
Project description:Objective: Patients with Systemic Lupus Erythematosus (SLE) have an ongoing interferon (IFN) production due to an activation of plasmacytoid dendritic cells (pDCs), which can be triggered to type I IFN synthesis by RNA containing immune complexes (RNA-IC). Considering emerging data suggesting a role of type III interferon (IFN) in the SLE disease process, we asked if RNA-IC can induce type III IFN production in pDC, and how this production can be regulated. Methods: Peripheral blood mononuclear cells (PBMCs) or immune cell subsets were isolated from healthy blood donors or SLE patients and stimulated with IC containing U1 snRNP and SLE-IgG (RNA-IC). Hydroxychloroquine (HCQ) and an interleukin receptor 1 associated kinase 4 inhibitor (IRAK4i) were added to cell cultures. Cytokine mRNA levels were determined with a microarray and protein levels with immunoassays. Single-cell RNA-sequencing of pDCs using ddSEQ technology was performed. Results: Type III IFN mRNA and protein was induced in RNA-IC stimulated pDC-NK and pDC-B cell co-cultures. A subset of activated pDCs (3%) expressed both type III and type I IFN mRNA. IFN-λ2, IFN-α2b, interleukin (IL)-3, IL-6 or granulocyte-macrophage colony stimulating factor (GM-CSF) enhanced IFN-λ1/3 production 2-5-fold. HCQ and an IRAK4i blocked the RNA-IC-triggered IFN-λ1/3 production (p<0.01). IFN-α2b and GM-CSF increased the proportion of SLE patients producing IFN-λ1/3 in response to RNA-IC from 11 to 33%. Conclusions: Type III IFN production is triggered by RNA-IC in pDCs in a TLR-MyD88-dependent manner, enhanced by NK and B cells as well as several pro-inflammatory cytokines. These results support a contributing role for both type I and type III IFNs in SLE, which needs to be considered when targeting the IFN system in this disease.
2020-05-23 | GSE148902 | GEO
Project description:mRNA microarray analysis of gene changes in Huh7 cells treated with IFN-λ4, IFN-λ1 and IFN-α
| PRJNA324708 | ENA
Project description:Hepatitis C virus (HCV) infection is a major cause of chronic hepatitis, liver cirrhosis and hepatocellular carcinoma. HCV can be sensed by host innate immunity to induce expression of interferons (IFNs) and a number of antiviral effectors. HCV-encoded NS3/4 serine protease can subvert host innate immune responses by cleaving MAVS, a critical adaptor protein in the RLR-mediated IFN signaling. To study innate immunity in the context of HCV infection, we constructed Huh7-MAVSR cells which express a mutant MAVS resistant to NS3/4A cleavage. HCV infection induces robust IFN response in Huh7-MAVSR cells, providing a cellular system to study antiviral innate immune response against HCV infection. To analyze host innate antiviral effectors against HCV infection, we performed an mRNA microarray analysis in the HCV-infected Huh7-MAVSR cells.
2018-02-08 | GSE110312 | GEO
Project description:The beneficial effects of glucocorticoids (GCs) in acute lymphoblastic leukemia (ALL) are based on their ability to induce apoptosis. Omics technologies such as DNA microarray analysis are widely used to study the changes in gene expression and have been successfully implemented in biomarker identification. In addition, time series studies of gene expression enable the identification of correlations between kinetic profiles of glucocorticoid receptor (GR) target genes and diverse modes of transcriptional regulation. This study presents a genome-wide microarray analysis of both our and published Affymetrix HG-U133 Plus 2.0 data in GCs-sensitive and -resistant ALL. GCs-sensitive CCRF-CEM-C7-14 cells were treated with dexamethasone at three time points (0 h, 2 h and 10 h). The treated samples were then compared to the control (0 h). The published data used were as follows: GSE2677: GSM51674: B-ALL-24-24h GSM51675: B-ALL-24-6h GSM51676: B-ALL-24-0h GSM51680: B-ALL-17-24h GSM51681: B-ALL-17-8h GSM51682: B-ALL-17-0h GSM51677: B-ALL-13-24h GSM51678: B-ALL-13-8h GSM51679: B-ALL-13-0h GSM51683: B-ALL-31-24h GSM51684: B-ALL-31-6h GSM51685: B-ALL-31-0h GSM51686: B-ALL-32-24h GSM51687: B-ALL-32-6h GSM51688: B-ALL-32-0h GSM51689: B-ALL-33-24h GSM51690: B-ALL-33-6h GSM51691: B-ALL-33-0h GSM51692: B-ALL-37-24h GSM51693: B-ALL-37-6h GSM51694: B-ALL-37-0h GSM51695: B-ALL-38-24h GSM51696: B-ALL-38-6h GSM51697: B-ALL-38-0h GSM51698: B-ALL-40-24h GSM51699: B-ALL-40-6h GSM51700: B-ALL-40-0h GSM51701: B-ALL-43-24h GSM51702: B-ALL-43-6h GSM51703: B-ALL-43-0h GSM51707: T-ALL-25-24h GSM51708: T-ALL-25-6h GSM51709: T-ALL-25-0h GSM51704: T-ALL-20-24h GSM51705: T-ALL-20-8h GSM51706: T-ALL-20-0h GSM51710: T-ALL-2-24h GSM51711: T-ALL-2-8h GSM51712: T-ALL-2-0h GSE2842 GSM60545: S-Line-PreB-6h-EtOH GSM60546: S-Line-PreB-6h-GC GSM60547: S-Line-PreB-24h-GC GSM60542: S-Line-C7H2-6h-EtOH GSM60543: S-Line-C7H2-6h-GC GSM60544: S-Line-C7H2-24h-GC GSM60560: R-Line-CEMC1-6h-EtOH GSM60561: R-Line-CEMC1-6h-GC GSM60562: R-Line-CEMC1-24h-GC GSM60564: R-Line-C7R1-6h-EtOH GSM60566: R-Line-C7R1-6h-GC GSM60576: R-Line-C7R1dim-low-6h-EtOH GSM60578: R-Line-C7R1dim-low-6h-GC GSM60579: R-Line-C7R1dim-low-24h-GC GSM60581: R-Line-PreB-6h-EtOH GSM60583: R-Line-PreB-6h-GC GSM60584: R-Line-PreB-24h-EtOH GSM60586: R-Line-PreB-24h-GC GSM60548: C-Line-CEMC1-ratGR-6h-EtOH GSM60549: C-Line-CEMC1-ratGR-6h-GC GSM60550: C-Line-CEMC1-ratGR-24h-GC GSM60551: C-Line-C7R1dim-high-6h-EtOH GSM60552: C-Line-C7R1dim-high-6h-GC GSM60553: C-Line-C7R1dim-high-24h-GC
2012-09-01 | GSE39338 | GEO
Project description:The beneficial effects of glucocorticoids (GCs) in acute lymphoblastic leukemia (ALL) are based on their ability to induce apoptosis. Omics technologies such as DNA microarray analysis are widely used to study the changes in gene expression and have been successfully implemented in biomarker identification. In addition, time series studies of gene expression enable the identification of correlations between kinetic profiles of glucocorticoid receptor (GR) target genes and diverse modes of transcriptional regulation. This study presents a genome-wide microarray analysis of both our and published Affymetrix HG-U133 Plus 2.0 data in GCs-sensitive and -resistant ALL. GCs-sensitive CCRF-CEM-C7-14 cells were treated with dexamethasone at three time points (0 h, 2 h and 10 h). The treated samples were then compared to the control (0 h). The published data used were as follows: GSE2677: GSM51674: B-ALL-24-24h GSM51675: B-ALL-24-6h GSM51676: B-ALL-24-0h GSM51680: B-ALL-17-24h GSM51681: B-ALL-17-8h GSM51682: B-ALL-17-0h GSM51677: B-ALL-13-24h GSM51678: B-ALL-13-8h GSM51679: B-ALL-13-0h GSM51683: B-ALL-31-24h GSM51684: B-ALL-31-6h GSM51685: B-ALL-31-0h GSM51686: B-ALL-32-24h GSM51687: B-ALL-32-6h GSM51688: B-ALL-32-0h GSM51689: B-ALL-33-24h GSM51690: B-ALL-33-6h GSM51691: B-ALL-33-0h GSM51692: B-ALL-37-24h GSM51693: B-ALL-37-6h GSM51694: B-ALL-37-0h GSM51695: B-ALL-38-24h GSM51696: B-ALL-38-6h GSM51697: B-ALL-38-0h GSM51698: B-ALL-40-24h GSM51699: B-ALL-40-6h GSM51700: B-ALL-40-0h GSM51701: B-ALL-43-24h GSM51702: B-ALL-43-6h GSM51703: B-ALL-43-0h GSM51707: T-ALL-25-24h GSM51708: T-ALL-25-6h GSM51709: T-ALL-25-0h GSM51704: T-ALL-20-24h GSM51705: T-ALL-20-8h GSM51706: T-ALL-20-0h GSM51710: T-ALL-2-24h GSM51711: T-ALL-2-8h GSM51712: T-ALL-2-0h GSE2842 GSM60545: S-Line-PreB-6h-EtOH GSM60546: S-Line-PreB-6h-GC GSM60547: S-Line-PreB-24h-GC GSM60542: S-Line-C7H2-6h-EtOH GSM60543: S-Line-C7H2-6h-GC GSM60544: S-Line-C7H2-24h-GC GSM60560: R-Line-CEMC1-6h-EtOH GSM60561: R-Line-CEMC1-6h-GC GSM60562: R-Line-CEMC1-24h-GC GSM60564: R-Line-C7R1-6h-EtOH GSM60566: R-Line-C7R1-6h-GC GSM60576: R-Line-C7R1dim-low-6h-EtOH GSM60578: R-Line-C7R1dim-low-6h-GC GSM60579: R-Line-C7R1dim-low-24h-GC GSM60581: R-Line-PreB-6h-EtOH GSM60583: R-Line-PreB-6h-GC GSM60584: R-Line-PreB-24h-EtOH GSM60586: R-Line-PreB-24h-GC GSM60548: C-Line-CEMC1-ratGR-6h-EtOH GSM60549: C-Line-CEMC1-ratGR-6h-GC GSM60550: C-Line-CEMC1-ratGR-24h-GC GSM60551: C-Line-C7R1dim-high-6h-EtOH GSM60552: C-Line-C7R1dim-high-6h-GC GSM60553: C-Line-C7R1dim-high-24h-GC
2012-09-01 | GSE39335 | GEO
Project description:To understand the roles of JMJD5 in liver cells, we performed DNA microarray analysis by using JMJD5KO Huh7 cells. We noticed that several transcriptional factors involved in differentiation to hepatocytes were down-regulated in JMJD5KO Huh7 cells compared to parent Huh7 cells..
2016-01-23 | GSE73491 | GEO
Project description:MeRIP-seq mapping of m6A in the IFN-β induced transcriptome in Huh7 cells
| PRJNA649691 | ENA