Limited specificity of IRF3 and ISGF3 in the transcriptional innate-immune response to double-stranded RNA

Ourthiague, Diana R.; Birnbaum, Harry; Ortenlöf, Niklas; Vargas, Jesse D.; Wollman, Roy; Hoffmann, Alexander

doi:10.1189/jlb.4a1014-483rr

Cited by 29 publications

(30 citation statements)

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“…Thus datasets from additional pertubation studies may lead to the inclusion of additional TFs and regulatory mechanisms in future iterations of the models. For example, this may reveal distinctions in transcriptional control by NFκB family members RelA vs cRel vs RelB (Almaden et al, 2016; Alves et al, 2014) or IRF3 vs ISGF3 (Ourthiague et al, 2015). Further, challenging the model to account for longer timecourses may require inclusion of a variety of late inducible TFs such as ATF3 (Gilchrist et al, 2006), CEBPβ and CEBPδ (Litvak et al, 2009) as well as LDTFs leading to the establishment of poised enhancers and promoters (Garber et al, 2012; Kaikkonen et al, 2013; Miele and Dekker, 2008).…”

Section: Discussionmentioning

confidence: 99%

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Iterative Modeling Reveals Evidence of Sequential Transcriptional Control Mechanisms

et al. 2017

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SUMMARY Combinatorial control of gene expression is presumed to be mediated by molecular interactions between coincident transcription factors (TFs). While information on the genome-wide locations of TFs is available, the genes they regulate and whether they function combinatorially often remain open questions. Here, we developed a mechanistic, rather than statistical, modeling approach to elucidate TF control logic from gene expression data. Applying this approach to hundreds of genes in 85 datasets measuring the transcriptional responses of murine fibroblasts and macrophages to cytokines and pathogens, we found that stimulus-responsive TFs generally function sequentially in logical OR gates or singly. Logical AND gates were found between NFκB-responsive mRNA synthesis and MAPKp38-responsive control of mRNA half-life, but not between temporally coincident TFs. Our analyses identified the functional target genes of each of the pathogen-responsive TFs and prompts a revision of the conceptual underpinnings of combinatorial control of gene expression to include sequentially acting molecular mechanisms that govern mRNA synthesis and decay.

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Section: Discussionmentioning

confidence: 99%

“…Primary BMDMs were prepared by culturing bone marrow cells from femurs of male or female 8–12 week old WT mice in L929-conditioned medium by standard methods (Cheng et al, 2011; Ourthiague et al, 2015). BMDMs were stimulated on day 8.…”

Section: Star Methodsmentioning

confidence: 99%

Iterative Modeling Reveals Evidence of Sequential Transcriptional Control Mechanisms

et al. 2017

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“…Expression of a subset of ISGs can be induced in the absence of IFN signaling (55,56). It is likely to be at least partially attributed to similar and overlapping consensus DNA-binding motifs for the interferon regulatory factor (IRF) family, most notably IRF3 and IRF7, which are key regulators of type I IFN production, and for IFN-stimulated gene factor 3 (ISGF3), which promotes the expression of many ISGs in response to IFN signaling (57)(58)(59)(60). For example, an IRF3 chromatin immunoprecipitation sequencing (ChIP-seq) experiment with adenovirus-infected human primary bronchial/tracheal epithelial cells demonstrated IRF3 binding to the promoter region of induced ISGs, including MX1 and ISG15, which have the IFNstimulated response element (ISRE) bound by IRFs and ISGF3 in the promoter regions (61).…”

Section: Downloaded Frommentioning

confidence: 99%

Cell-to-Cell Variation in Defective Virus Expression and Effects on Host Responses during Influenza Virus Infection

Wang

Forst

Chou

et al. 2020

mBio

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Virus and host factors contribute to cell-to-cell variation in viral infections and determine the outcome of the overall infection. However, the extent of the variability at the single-cell level and how it impacts virus-host interactions at a system level are not well understood. To characterize the dynamics of viral transcription and host responses, we used single-cell RNA sequencing to quantify at multiple time points the host and viral transcriptomes of human A549 cells and primary bronchial epithelial cells infected with influenza A virus. We observed substantial variability in viral transcription between cells, including the accumulation of defective viral genomes (DVGs) that impact viral replication. We show (i) a correlation between DVGs and virus-induced variation of the host transcriptional program and (ii) an association between differential inductions of innate immune response genes and attenuated viral transcription in subpopulations of cells. These observations at the single-cell level improve our understanding of the complex virus-host interplay during influenza virus infection. IMPORTANCE Defective influenza virus particles generated during viral replication carry incomplete viral genomes and can interfere with the replication of competent viruses. These defective genomes are thought to modulate the disease severity and pathogenicity of an influenza virus infection. Different defective viral genomes also introduce another source of variation across a heterogeneous cell population. Evaluating the impact of defective virus genomes on host cell responses cannot be fully resolved at the population level, requiring single-cell transcriptional profiling. Here, we characterized virus and host transcriptomes in individual influenza virus-infected cells, including those of defective viruses that arise during influenza A virus infection. We established an association between defective virus transcription and host responses and validated interfering and immunostimulatory functions of identified dominant defective viral genome species in vitro. This study demonstrates the intricate effects of defective viral genomes on host transcriptional responses and highlights the importance of capturing host-virus interactions at the single-cell level.

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“…Activated IRF3 induces IFN-β gene expression which, in turn, activates JAK/STAT signaling, leading to the transcription of a variety of ISGs (39). Here, we showed that statins inhibit the phosphorylation of both IRF3 and STAT1 in poly(I:C)-treated macrophages (Fig.…”

Section: Discussionmentioning

confidence: 52%

“…Hyperlipidemic mice exhibit altered immune responses (23,24,33). Atorvastatin improved plaque stability in ApoE-knockout mice (39), and exerted hypolipidemic and anti-inflammatory action in ApoE/LDL receptor-knockout mice (40). However, to our knowledge, the effects of statins on the antiviral immune response in hyperlipidemic mice have not been evaluated.…”

Section: Discussionmentioning

confidence: 99%

Statins attenuate antiviral IFN-β and ISG expression via inhibiting IRF3/JAK/STAT signaling in poly(I:C)-treated hyperlipidemic mice and macrophages

Koike

Tsujinaka

Fujimori

2020

Preprint

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Viral infection is a significant burden to healthcare worldwide. Statins, 3-hydroxy-3-methyl glutaryl coenzyme A reductase inhibitors, are widely used as cholesterol-lowering drugs. Recently, long term statin therapy was shown to reduce the antiviral immune response; however, the underlying molecular mechanisms are unclear. Here, we found that simvastatin decreased polyinosinic-polycytidylic acid [poly(I:C)]-induced expression of antiviral interferon (IFN)-β and IFN-stimulated genes (ISGs) in the bronchoalveolar lavage fluid and lungs of mice with high-fat diet-induced hyperlipidemia. As macrophages were the dominant cell type in the bronchoalveolar lavage fluid of poly(I:C)-treated mice, we examined the molecular mechanisms of statin-mediated inhibition of antiviral gene expression using murine J774.1/JA-4 macrophages. Simvastatin and pitavastatin decreased poly(I:C)-induced expression of IFN-β and ISGs. Moreover, they repressed poly(I:C)-induced phosphorylation of IFN regulatory factor (IRF) 3 and signal transducers and activators of transcription (STAT) 1, which is involved in Janus kinase (JAK)/STAT signaling. Mevalonate and geranylgeranylpyrophosphate (GGPP), but not cholesterol, counteracted the negative effect of statins on IFN-β and ISG expression and phosphorylation of IRF3 and STAT1. These results suggest that statins suppressed the expression of IFN-β and ISGs in poly(I:C)-treated hyperlipidemic mice and murine macrophages, and that these effects occured through the inhibition of IRF3-mediated JAK/STAT signaling in macrophages. Furthermore, GGPP recovered the statin-suppressed IRF3/JAK/STAT signaling pathway in poly(I:C)-treated macrophages.

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Limited specificity of IRF3 and ISGF3 in the transcriptional innate-immune response to double-stranded RNA

Cited by 29 publications

References 50 publications

Iterative Modeling Reveals Evidence of Sequential Transcriptional Control Mechanisms

Iterative Modeling Reveals Evidence of Sequential Transcriptional Control Mechanisms

Cell-to-Cell Variation in Defective Virus Expression and Effects on Host Responses during Influenza Virus Infection

Statins attenuate antiviral IFN-β and ISG expression via inhibiting IRF3/JAK/STAT signaling in poly(I:C)-treated hyperlipidemic mice and macrophages

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