Essential Role of Sirt2 in Type I Interferon Signaling
Ontology highlight
ABSTRACT:
ORGANISM(S): Mus musculus
PROVIDER: GSE66033 | GEO | 2015/12/31
SECONDARY ACCESSION(S): PRJNA275736
REPOSITORIES: GEO
Similar Datasets
Project description:We provide evidence that the Unc-51-like kinase 1 (ULK1) is phosphorylated and activated during engagement of the Type I IFN receptor. Our studies demonstrate that the function of ULK1 controls expression of key interferon stimulated genes (ISGs) that mediate important biological functions, including anti-viral and antineoplastic responses.
2014-08-26 | GSE60778 | GEO
Project description:We provide evidence that the Unc-51-like kinase 1 (ULK1) is phosphorylated and activated during engagement of the Type I IFN receptor. Our studies demonstrate that the function of ULK1 controls expression of key interferon stimulated genes (ISGs) that mediate important biological functions, including anti-viral and antineoplastic responses. Total RNA was isolated from untreated and IFNβ-treated Ulk1/2+/+ and Ulk1/2-/- mouse embryonic fibroblasts (MEFs). Cells were treated for 6 hours with or without mouse IFNβ (2500 IU/ml).
2014-08-26 | E-GEOD-60778 | biostudies-arrayexpress
Project description:We provide evidence that a member of the IFN-regulated member of the Schlafen (SLFN) family of proteins, SLFN5, promotes the malignant phenotype in glioblastoma multiforme (GBM). Our studies demonstrate that SLFN5 negatively regulates expression of key interferon stimulated genes (ISGs) that mediate important biological functions, including anti-viral and antineoplastic responses.
2017-01-31 | GSE88771 | GEO
Project description:Type I interferons (IFN-I) are critical in antimicrobial and antitumor defense. Although IFN-I signal via the interferon-stimulated gene factor 3 (ISGF3) complex consisting of STAT1, STAT2 and IRF9, IFN-I can mediate significant biological effects via ISGF3-independent pathways. For example, absence of STAT1, STAT2 or IRF9 exacerbates neurological disease in transgenic mice with CNS-production of IFN-gamma. Here we determined the role of IFN-I-driven, ISGF3-independent signaling in regulating global gene expression in STAT1, STAT2 or IRF9-deficient murine mixed glial cell cultures (MGCs). Compared with WT, the expression of IFN-gamma-stimulated genes (ISGs) was reduced in number and magnitude in MGCs that lacked STAT1, STAT2 or IRF9. There were significantly fewer ISGs in the absence of STAT1 or STAT2 versus the absence of IRF9. The majority of ISGs regulated in the STAT1-, STAT2- or IRF9-deficient MGCs individually were shared with WT. However, only a minor number of ISGs were common to WT, STAT1-, STAT2- and IRF9-deficient MGCs. While signal pathway activation in response to IFN-gamma was rapid and transient in WT MGCs, this was delayed and prolonged and correlated with increased numbers of ISGs expressed at 12 h versus 4 h IFN-gamma exposure in all three IFN-I-signaling-deficient MGCs. In conclusion, (1) IFN-I can mediate ISG expression in MGCs via ISGF3-independent signaling pathways but with reduced efficiency, with delayed and prolonged kinetics and is more dependent on STAT1 and STAT2 than IRF9, and (2) signaling pathways not involving STAT1, STAT2 or IRF9 play a minor role only in mediating ISG expression in MGCs.
2017-02-15 | E-MTAB-5445 | biostudies-arrayexpress
Project description:Host cells produce interferon (IFN) in response to viral infections. Secreted interferon results in the transcription and production of hundreds of interferon-stimulated genes (ISGs). A genome-wide CRISPR screen using IFN alpha-treated Huh7.5 cells was performed to determine which ISGs were required in order for host cells to suppress yellow fever virus (YFV) infection.
2018-10-25 | GSE121710 | GEO
Project description:The type I interferon (IFN) response protects cells against viral pathogens by inducing the transcription of hundreds of IFN-stimulated genes (ISGs). Transcriptomic and biochemical approaches have established comprehensive catalogues of ISGs across species and cell types, but their antiviral mechanisms remain incompletely characterized. Here, we apply a combination of quantitative proteomic approaches to map IFN-induced rearrangements in the human protein-protein interaction network. Specifically, we analyzed the IFN-induced changes to the HeLa cell proteome with shotgun mass spectrometry. As well, we assessed the IFN-induced interactome with protein correlation profiling coupled to size exclusion chromatography and SILAC. Finally, we utilized label-free quantitative mass spectrometry for affinity purification mass spectrometry of candidate proteins and to analyze the ribosomal protein composition.
2020-05-15 | PXD013809 | Pride
Project description:Host cells produce interferon (IFN) in response to viral infections. Secreted interferon results in the transcription and production of hundreds of interferon-stimulated genes (ISGs). An ISG-targeted CRISPR screen using IFN beta-treated U-2 OS cells was performed to determine which ISGs were required in order for host cells to suppress Venezuelan equine encephalitis virus (VEEV) infection.
2023-05-26 | GSE233196 | GEO
Project description:Host cells produce interferon (IFN) in response to viral infections. Secreted interferon results in the transcription and production of hundreds of interferon-stimulated genes (ISGs). A genome-wide CRISPR screen using IFN beta-treated U-2 OS cells was performed to determine which ISGs were required in order for host cells to suppress Venezuelan equine encephalitis virus (VEEV) infection.
2023-05-26 | GSE233195 | GEO
Project description:Human adenoviruses (HAdV) are a large family of DNA viruses generally infecting the airway, the gut, the eye, and the urinary tract. However, certain strains of HAdVs are capable of causing severe infections in the very young, the elderly, the immunocompromised, and sometimes healthy individuals. In particular, species B HAdVs are often associated with more severe disease, involving serotype 7 and 14. Despite the severity of the disease caused by these strains, little is known about the molecular mechanisms underpinning the disease outcomes. Activation of interferon stimulated genes (ISGs) occurs rapidly after interferon (IFN) stimulation and relies on recruitment of the transcription factor complex IFN-stimulated gene factor 3 (ISGF3) to promoters, which happens via the canonical JAK-STAT pathway. Therefore, suppression of IFNs is a key aspect of evading innate immunity by viral pathogens, including HAdVs; and as such, HAdVs have evolved multiple ways by which they suppress activation of ISGs in order to drive viral replication. Our previous work investigated the molecular mechanism of interferon suppression by HAdV-C5. We observed that E1A of HAdV-C5 interacts with the AAA+ DNA helicase RuvBL1/Pontin in order to suppress activation of interferon stimulated genes (ISGs) during infection. We therefore wanted to determine whether RuvBL1 is also a target for the more highly pathogenic HAdV-B7 and B14. As part of this investigation, we examined the broad-range effect of HAdV species C2, B7, and B14 on cells in response to interferon. These results are presented here.
2024-06-26 | PXD045673 | Pride
Project description:Maier2022 - Stochastic Dynamics of Type I Interferon Responses
Our study aims to determine whether and how biochemical noise affects the information transduced in the JAK-STAT signaling pathway and investigate the transition between basal and activated state. To this end, we studied the stochastic responses of MxA and IFIT1 expression in Huh7.5 cells stimulated with IFN-$\alpha$. Using fluorescent reporters under the control of the authentic promoter/enhancer region of IFIT1 and MxA we collected data displaying the differences between expressing and non-expressing cells for the marker genes in a time-course experiment. We hypothesize that the JAK-STAT signaling pathway efficiently transmits information under stochastic environments. To test our working hypothesis, we developed a detailed mathematical model using the obtained time-resolved flow cytometry data to describe the elements in the JAK-STAT signaling pathway at single-cell resolution. This model allowed us to systematically test the influence of intrinsic and extrinsic noise in the IFN response.
The developed model consists of 42 species and 62 reactions (reactions m1 to m62). To name the variables in the model we used the following conventions: 1) variables referring to mRNA are denoted by $m$ prefix. 2) Variables in phosphorylated use $p$ as prefix. 3) Gene promoters are represented by the gene's name in lowercase. 4) R1, R2, IR, AR and RC, represent the IFN receptor subunits, inactive, active and complex forms, respectively. 5) The compartment is superscripted to the species if the species exist in multiple compartments. A graphical representation of the interaction between variables in the model is given in Maier et. al 2022 (Fig. 1) and all reactions are listed in the Supplementary Information, Section S2.1.
Note that we publish the SBML model without the observables (e.g. exp_IRF9_n) as the change in the number of particles is defined in relation to the starting value in the COPASI model which is not supported in SBML format. In order to reproduce the parameter estimation without any extra worj, we recommend the direct download of the provided copasi model linked in the article.
This model is described in the article:
Stochastic Dynamics of Type I Interferon Responses
Benjamin D. Maier(*), Luis U. Aguilera(*), Sven Sahle, Pascal Mutz, Priyata Kalra, Christopher Dächert, Ralf Bartenschlager, Marco Binder, Ursula Kummer
PLOS Computational Biology, 2022
(*) Equally contributing authors
Abstract:
Interferon (IFN) activates the transcription of several hundred of IFN stimulated genes (ISGs) that constitute a highly effective antiviral defense program. Cell-to-cell variability in the induction of ISGs is well documented, but its source and effects are not completely understood. The molecular mechanisms behind this heterogeneity have been related to randomness in molecular events taking place during the JAK-STAT signaling pathway. Here, we study the sources of variability in the induction of the IFN-alpha response by using MxA and IFIT1 activation as read-out. To this end, we integrate time-resolved flow cytometry data and stochastic modeling of the JAK-STAT signaling pathway. The complexity of the IFN response was matched by fitting probability distributions to time-course flow cytometry snapshots. Both, experimental data and simulations confirmed that the MxA and IFIT1 induction circuits generate graded responses rather than all-or-none responses. Subsequently, we quantify the size of the intrinsic variability at different steps in the pathway. We found that stochastic effects are transiently strong during the ligand-receptor activation steps and the formation of the ISGF3 complex, but negligible for the final induction of the studied ISGs. We conclude that the JAK-STAT signaling pathway is a robust biological circuit that efficiently transmits information under stochastic environments.
2022-10-25 | MODEL2210070001 | BioModels