Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Transcriptomic modulation by adenosine 2A receptors in normal and endotoxemic myocardium

ABSTRACT: Analysis of venticular myocardium from adenosine 2A receptors (A2AR) knockouts following LPS stimulation. Results provide insight into the molecular components of A2AR mediated protection, but also reveal pathogenetic components of endotoxemic myocarditis as a result of LPS exposure. These findings demonstrate that intrinsic A2AR activity exerts limited transcriptional effects in unstressed heart, modifying G-coupled cAMP/PKA signal paths. LPS-dependent injury and dysfunction is associated with profound up-regulation of inflammatory/immune processes, fibrotic and cell death paths, and NF-kB, Erk/MAPK and JAK/Stat signaling, with shifts in multiple determinants of cardiac contraction and survival. Intrinsic A2AR activity modulates key aspects of these inflammatory responses, involving MAPK, JAK/Stat and NF-kB signaling Total RNA obtained from adenosine 2A receptor knockout or wild-type murine ventricular myocardium that were treated for 24 hours with either saline or lipopolysaccharide (n=4/group).

ORGANISM(S): Mus musculus

SUBMITTER: Kevin Ashton

PROVIDER: E-GEOD-44363 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

ACCESS DATA

Similar Datasets

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

Transcriptomic modulation by adenosine 2A receptors in normal and endotoxemic myocardium

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure