The Molecular Basis of Viral Inhibition of IRF- and STAT-Dependent Immune Responses

Chiang, Hao-Sen; Liu, Helene Minyi

doi:10.3389/fimmu.2018.03086

Cited by 89 publications

(87 citation statements)

References 133 publications

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“…Therefore, IRF3 has been found to be targeted by several different classes of viruses. Paramyxoviruses, herpesviruses, reovirus and double stranded RNA viruses, to cite some examples, have been shown to interfere with IRF3 signalling through different strategies [65]. These include the control of protein expression, protein cellular localisation, modifications of the PTMs, inhibition of protein-protein interactions or induced cellular degradation [10].…”

Section: Irf3 Tab1 and Nlrp12 Are Important Components That Drive Thmentioning

confidence: 99%

SARS-CoV-2 proteases cleave IRF3 and critical modulators of inflammatory pathways (NLRP12 and TAB1): implications for disease presentation across species and the search for reservoir hosts

Moustaqil

Ollivier

Chiu

et al. 2020

Preprint

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The genome of SARS-CoV-2 (SARS2) encodes for two viral proteases (NSP3/ papain-like protease and NSP5/ 3C-like protease or major protease) that are responsible for cleaving viral polyproteins for successful replication. NSP3 and NSP5 of SARS-CoV (SARS1) are known interferon antagonists. Here, we examined whether the protease function of SARS2 NSP3 and NSP5 target proteins involved in the host innate immune response. We designed a fluorescent based cleavage assay to rapidly screen the protease activity of NSP3 and NSP5 on a library of 71 human innate immune proteins (HIIPs), covering most pathways involved in human innate immunity. By expressing each of these HIIPs with a genetically encoded fluorophore in a cell-free system and titrating in the recombinant protease domain of NSP3 or NSP5, we could readily detect cleavage of cognate HIIPs on SDS-page gels. We identified 3 proteins that were specifically and selectively cleaved by NSP3 or NSP5: IRF-3, and NLRP12 and TAB1, respectively. Direct cleavage of IRF3 by NSP3 could explain the blunted Type-I IFN response seen during SARS-CoV-2 infections while NSP5 mediated cleavage of NLRP12 and TAB1 point to a molecular mechanism for enhanced production of IL-6 and inflammatory response observed in COVID-19 patients. Surprisingly, both NLRP12 and TAB1 have each two distinct cleavage sites. We demonstrate that in mice, the second cleavage site of NLRP12 is absent. We pushed this comparative alignment of IRF-3 and NLRP12 homologs and show that the lack or presence of cognate cleavage motifs in IRF-3 and NLRP12 could contribute to the presentation of disease in cats and tigers, for example. Our findings provide an explanatory framework for in-depth studies into the pathophysiology of COVID-19 and should facilitate the search or development of more effective animal models for severe COVID-19. Finally, we discovered that one particular species of bats, David's Myotis, possesses the five cleavage sites found in humans for NLRP12, TAB1 and IRF3. These bats are endemic from the Hubei province in China and we discuss its potential role as reservoir for the evolution of SARS1 and SASR2.

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Section: Irf3 Tab1 and Nlrp12 Are Important Components That Drive Thmentioning

confidence: 99%

SARS-CoV-2 proteases cleave IRF3 and critical modulators of inflammatory pathways (NLRP12 and TAB1): implications for disease presentation across species and the search for reservoir hosts

Moustaqil

Ollivier

Chiu

et al. 2020

Preprint

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“…Transcription factors Not unexpectedlyand speaking again to validation of the consensomes -the strongest and most significant CoV HCT intersections were observed for HCTs for known transcription factor mediators of the transcriptional response to CoV infection, including members of the NFκB (q-value ranges: SARS1, 1e-7-1e-9; SARS2, 9e-3-2e-3; MERS, 1e-3-1e-4) [33][34][35] , IRF (q-value ranges: SARS1, 2e-2-1e-31; SARS2, 2e-4-1e-17; MERS, 9e-4-7e-5) 36 and STAT (q-value ranges: SARS1, 1e-7-1e-55; SARS2, 2e-3-3e-29; MERS, 5e-2-3e-5) 37-39 transcription factor families ( Fig. 3).…”

Section: To Illuminate Human Signaling Pathways Orchestrating the Tramentioning

confidence: 99%

Consensus transcriptional regulatory networks of coronavirus-infected human cells

Ochsner

Pillich

McKenna

2020

Preprint

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15Identifying transcriptional responses that are most consistently associated with 16 experimental coronavirus (CoV) infection can help illuminate human cellular signaling 17 pathways impacted by CoV infection. Here, we distilled over 3,000,000 data points from 18 publically archived CoV infection transcriptomic datasets into consensus regulatory 19 signatures, or consensomes, that rank genes based on their transcriptional 20 responsiveness to infection of human cells by MERS, SARS-CoV-1 and SARS-CoV-2 21 subtypes. We computed overlap between genes with elevated rankings in the CoV 22 consensomes against those from transcriptomic and ChIP-Seq consensomes for nearly 23 880 cellular signaling pathway nodes. Validating the CoV infection consensomes, we 24 identified robust overlap between their highly ranked genes and high confidence targets 25 of signaling pathway nodes with known roles in CoV infection. We then developed a 26 series of use cases that illustrate the utility of the CoV consensomes for hypothesis 27 generation around mechanistic aspects of the cellular response to CoV infection. We 28 make the CoV infection consensomes and their universe of underlying data points freely 29 accessible through the Signaling Pathways Project web knowledgebase. 30 31 65 points in a series of use cases illuminates previously uncharacterized intersections 66 between CoV infection and human cellular signaling pathways. The CoV infection 67 consensome and its underlying datasets provide researchers with a unique and freely 68 accessible framework within which to generate and pressure test hypotheses around 69 human cellular signaling pathways impacted by CoV infection.70 71 72 73 5 Results 74Generation of the CoV consensomes 75 We first set out to generate a set of consensomes ranking human genes based on the 76 frequency of their significant differential expression in response to infection by MERS, 77 SARS1 and SARS2 CoVs. To do this we searched the Gene Expression Omnibus 78 (GEO) and ArrayExpress databases to identify datasets involving infection of human 79 cells by these species. From this initial collection of datasets, we next carried out a 80 three step quality control check as previously described (Ochsner et al., 2019), yielding 81 a total of 3,041,047 million data points in 111 experiments from 25 independent CoV 82 infection transcriptomic datasets (Supplementary information, Section 1). Using these 83 curated datasets, we next generated consensomes for each CoV species, as well as 84 one ranking genes across all CoV infection experiments (ALL CoV). As a reference 85 consensome for a virus whose transcriptional impact on human cells has been studied 86 in depth, we also generated a consensome for human influenza A virus (IAV) infection. 87The Supplementary information files contain the full human ALL CoV (Section 2), MERS 88 (Section 3), SARS1 (Section 4), SARS2 (Section 5) and IAV (Section 6) infection 89 transcriptomic consensomes. To assist researchers in inferring transcriptional regulation 90 of sig...

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“…IRF2 and IRF4 have been implicated in the suppression of type I IFN signaling. [43,44]. IRF-4 and ZNF148 TF are involved in Epstein -Barr virus (EBV) infections.…”

Section: Discussionmentioning

confidence: 99%

Severe Acute Respiratory Syndrome Coronavirus 2 could exploit human transcription factors involved in Interferon-mediated response

Bari

Franzin

Picerno

et al. 2020

Preprint

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Background The novel SARS-CoV-2 causing the pandemic acute respiratory disease COVID-19 is considered a worldwide emergency since no vaccines or effective antiviral are still available. As virus are dependent on the host transcriptional factors (TFs) to express the viral genes, efforts are required to understand the molecular interplay between virus and host response. Methods By bioinformatic analysis, we investigated human TFs involved in viral transcription. In particular, we analyzed the key role of the TF induced by Interferon regulatory factors (IRFs) exploiting the way of antiviral response related to interferon antiviral cytokines released during an infection. We compared SARS-CoV-2 consensus sequence from Italian patients with sequences in Coronaviridae ViPR database, to identify elements and TF binding sites that were present uniquely in the Italian viral sequence.Results Several TFs were induced by IRFs, others were induced by IFN-stimulated gene factor 3 (ISGF3) and by un-phosphorylated ISGF3 that was found to promote the transcription of several viral open reading frame. These data shed light on SARS-CoV2 dependence from the host transcription machinery associated to interferon-related antiviral response. We found binding sites for 11 TF present only in sequence of virus infecting humans and among these IRF8, IRF4, GLIS2, POU4F2 that were expressed in response to the viral infection and induced by interferon. POU4F2 binds in ORF1ab promoter; IRF8, and IRF4 both bind within the ORF1ab gene.Conclusions Our data suggest that SARS-CoV-2 can exploit the interferon-related host response, inducing the expression of genes by host TF involved in the regulation of transcription by RNA polymerase II, thus facilitating its own replication cycle.These data strengthen our knowledge about the transcription and replicative activity of the virus and could pave the way for new targets drug design.

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The Molecular Basis of Viral Inhibition of IRF- and STAT-Dependent Immune Responses

Cited by 89 publications

References 133 publications

SARS-CoV-2 proteases cleave IRF3 and critical modulators of inflammatory pathways (NLRP12 and TAB1): implications for disease presentation across species and the search for reservoir hosts

SARS-CoV-2 proteases cleave IRF3 and critical modulators of inflammatory pathways (NLRP12 and TAB1): implications for disease presentation across species and the search for reservoir hosts

Consensus transcriptional regulatory networks of coronavirus-infected human cells

Severe Acute Respiratory Syndrome Coronavirus 2 could exploit human transcription factors involved in Interferon-mediated response

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