Dataset Information

Proteomic analysis of Human Adenovirus B and C infections in the presence of interferon

ABSTRACT: 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.

INSTRUMENT(S): Orbitrap Fusion Lumos

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Epithelial Cell, Cell Culture

DISEASE(S): Lung Cancer

SUBMITTER: Drayson Graves

LAB HEAD: Peter Pelka

PROVIDER: PXD045673 | Pride | 2024-06-26

REPOSITORIES: Pride

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			Action	DRS
	S13021_C_Plus_24H_1_200_220329.mzid.gz	Mzid
	S13021_C_Plus_24H_1_200_220329.mzid_S13021_C_Plus_24H_1_200_220329.MGF	Mzid
	S13022_7_Plus_24H_1_200_220329.mzid.gz	Mzid
	S13022_7_Plus_24H_1_200_220329.mzid_S13022_7_Plus_24H_1_200_220329.MGF	Mzid
	S13081_7_2_Plus_24h_1_200_220408.mzid.gz	Mzid

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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.

Dataset Information

Proteomic analysis of Human Adenovirus B and C infections in the presence of interferon

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