Aguilera2017 - Model for gene constitutive expression circuit
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ABSTRACT:
SUBMITTER: 
Luis Ubaldo Aguilera de Lira
PROVIDER: MODEL1608100000 | BioModels | 2017-03-17
REPOSITORIES: BioModels
Similar Datasets
Project description:Model destription:
The model describes the dynamics of murine IRF7 gene expression upon IFN stimulation. The present model comprises known key components and feedback mechanisms. The overall system describes the active IRF7 promoter (Pa) by the binding of IRF7 dimer and ISGF3 to the DNA binding sites ISRE and IRFE, respectively, the transcription and translation of IRF7, and its subsequent phosphorylation and dimerization. IRF7 protein binding to the IRFE binding site in the promoter results in the production of more IRF7 protein, constituting a positive feedback loop.
Publication:
A New Efficient Approach to Fit Stochastic Models on the Basis of High-throughput Experimental Data Using a Model of IRF7 Gene Expression as Case Study
Authors
Luis U. Aguilera, Christoph Zimmer and Ursula Kummer.
2017-03-17 | MODEL1608100001 | BioModels
Project description:This SuperSeries is composed of the following subset Series: GSE36241: Identification of a FOXO3/IRF7 circuit that limits inflammatory sequelae of antiviral responses (ChIP-Seq) GSE37051: Identification of a FOXO3/IRF7 circuit that limits inflammatory sequelae of antiviral responses (expression) Refer to individual Series
2012-09-19 | E-GEOD-37052 | biostudies-arrayexpress
Project description:We predict that a member of the forkhead family of transcription factors, FOXO3, is a negative regulator of a subset of antiviral genes. This prediction was validated using macrophages isolated from Foxo3-null mice. Genome-wide location analysis combined with gene deletion studies identified the Irf7 gene as a critical target of FOXO3. FOXO3 was identified as a negative regulator of Irf7 transcription. Our data suggest that the FOXO3-IRF7 regulatory circuit represents a novel mechanism for establishing the requisite set points in the interferon pathway.
2012-09-19 | GSE36241 | GEO
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
Project description:We predict that a member of the forkhead family of transcription factors, FOXO3, is a negative regulator of a subset of antiviral genes. This prediction was validated using macrophages isolated from Foxo3-null mice. Genome-wide location analysis combined with gene deletion studies identified the Irf7 gene as a critical target of FOXO3. FOXO3 was identified as a negative regulator of Irf7 transcription. Our data suggest that the FOXO3-IRF7 regulatory circuit represents a novel mechanism for establishing the requisite set points in the interferon pathway. C57BL/6 mice were obtained from Jackson Laboratories. Foxo3-/- mice in the FVB background were obtained from MMRRC and were backcrossed to C57BL/6 mice at least 5 times to generate congenic mice. C57BL/6 Foxo3+/- heterozygotes were intercrossed to generate Foxo3-/- mice. Mice were maintained at the animal facility of the Institute for Systems Biology and used at 8–12 weeks of age. All animals were housed and handled according to the approved protocols of University of Washington and Institute for Systems Biology's Institutional Animal Care and Use Committees.
2012-09-19 | E-GEOD-36241 | biostudies-arrayexpress
Project description:Primary outcome(s): Gene expression of targeted genes
| 2625389 | ecrin-mdr-crc
Project description:Gene expression signatures in IRF7 overexpressed 3T3-L1 adipocytes
| PRJNA622292 | ENA
Project description:Interventions: Group 1: Quantitative Expression Analysis of the proteom and gene Expression of Primary Tumor, normal tissue, and metastases
Primary outcome(s): Disease associated Proteins and Genes
Study Design: Allocation: ; Masking: ; Control: ; Assignment: ; Study design purpose: basic science
| 2431957 | ecrin-mdr-crc
Project description:Primary outcome(s): The clinical significance of immune and gene-expression profile in colorectal cancer
| 2659791 | ecrin-mdr-crc
Project description:Rantasalo2015-Synthetic_expresion_modulator_constitutiveSTF_VP16
This model is part of a family of models describing a modular synthetic expression system that modulates the expression level of a gene in S. Cerevisae. The whole family of models is described in the article:
Synthetic transcription amplifier system for orthogonal control of gene expression in Saccharomyces cerevisiae, by
Anssi Rantasalo, Elena Czeizler, Riitta Virtanen, Juho Rousu, Harri Lähdesmäki, Merja Penttilä, Jussi Jäntti and Dominik Mojzita (submitted).
The family comprises 5 different models corresponding to the synthetic systems using:
1) the methionine induced synthetic transcription factor sTF-VP16 construct,
2) the methionine induced synthetic transcription factor sTF-B42 construct,
3) the constitutive sTF-VP16 construct,
4) the constitutive sTF-B42 construct, and
5) the constitutive sTF-VP16 construct with a different core promoter for the reporter gene.
The computational models were designed, developed and implemented by Elena Czeizler, Harri Lahdesmaki and Juho Rousu and they are all hosted separately in the Biomodels database.
The only difference between the models corresponding to the constitutive and the methionine-induced systems stands in the sTF transcription process. The only difference between the models for the systems using the sTF16 or sTF42 constructs stands in the kinetic rates associated to 2 reactions: i) the association of the polymerase with the sTF’s bound to their specific DNA sites and ii) the degradation rate of the sTF proteins corresponding to the two transcription factors sTF16 or sTF42. The first 4 models correspond to systems using the pBID2-EP core promoter for the reporter mCherry gene. Starting from the model associated to the constitutive system using the sTF16 construct we derived the 5th model corresponding to the case when the core promoter for the reporter mCherry gene is switched from pBID2-EP to pBID2-ED. The only difference between these two last models stands in the kinetic rates for the association of polymerase bound to sTF and the core promoter.
Since the 5 considered models have many parts in common, the values for the kinetic parameters corresponding to these common parts are identical in all of them.
The current model describes the gene expression modulation system using the constitutive synthetic transcription factor sTF-VP16 composed of a LexA DNA binding domain, the Herpes simplex virus transactivation domain (VP16) and a 6×His-tag. In this model, the number of boxes to which this sTF can bind (encoded in the species B) is set to 2. In the experimental setups, the number of binding boxes varied between 0 and 16 (8 binding sites on each of the 2 DNA constructs), which can be easily modified in the model by changing the initial value for B. The core promoter used for the reporter mCherry gene is pBID-EP.
All model analysis and simulations were done by using the software COPASI (Hoops, S., Sahle, S., Gauges, R., Lee, C., Pahle, J., Simus, N., Singhal, M., Xu, L., Mendes, P. and Kummer, U. (2006) COPASI- A COmplex PAthway SImulator. Bioinformatics, 22, 3067-3074.)
2016-02-23 | MODEL1510230001 | BioModels