Mus musculus
Ontology highlight
ABSTRACT:
PROVIDER: PRJDB13512 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| DRR377507_1.fastq.gz | Fastqsanger.gz | |||
| DRR377507_2.fastq.gz | Fastqsanger.gz | |||
| DRR377508_1.fastq.gz | Fastqsanger.gz | |||
| DRR377508_2.fastq.gz | Fastqsanger.gz | |||
| DRR377509_1.fastq.gz | Fastqsanger.gz |
Items per page: 5 1 - 5 of 8 |
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Project description:NMuMG cell response to TGF-beta and TGF-beta +2APB treatments
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Project description:This model is from the article:
Quantitative analysis of transient and sustained transforming growth factor-β signaling dynamics.
Zhike Zi, Zipei Feng, Douglas A Chapnick, Markus Dahl, Difan Deng, Edda Klipp, Aristidis Moustakas & Xuedong Liu Molecular Systems Biology
2011 May 24;7:492. 21613981
,
Abstract:
Mammalian cells can decode the concentration of extracellular transforming growth factor-β (TGF-β) and transduce this cue into appropriate cell fate decisions. How variable TGF-β ligand doses quantitatively control intracellular signaling dynamics and how continuous ligand doses are translated into discontinuous cellular fate decisions remain poorly understood. Using a combined experimental and mathematical modeling approach, we discovered that cells respond differently to continuous and pulsating TGF-β stimulation. The TGF-β pathway elicits a transient signaling response to a single pulse of TGF-β stimulation, whereas it is capable of integrating repeated pulses of ligand stimulation at short time interval, resulting in sustained phospho-Smad2 and transcriptional responses. Additionally, the TGF-β pathway displays different sensitivities to ligand doses at different time scales. While ligand-induced short-term Smad2 phosphorylation is graded, long-term Smad2 phosphorylation is switch-like to a small change in TGF-β levels. Correspondingly, the short-term Smad7 gene expression is graded, while long-term PAI-1 gene expression is switch-like, as is the long-term growth inhibitory response. Our results suggest that long-term switch-like signaling responses in the TGF-β pathway might be critical for cell fate determination.
Note:
Developer of the model: Zhike Zi
Reference: Zi Z. et al., Quantitative Analysis of Transient and Sustained Transforming Growth Factor-beta Signaling Dynamics, Molecular Systems Biology, 2011
1. The global parameter that set the type of stimulation
(a) for sustained TGF-beta stimulation: set stimulation_type = 1.
(b) for single pulse of TGF-beta stimulation: set stimulation_type = 2.
parameter "single_pulse_duration" is for the duration of stimulation, for example,
single_pulse_duration = 0.5, for 0.5 min (30 seconds) of TGF-beta stimulation.
*Note: make sure that the time course cover the time point when the event is triggered.
(c) for single pulse of TGF-beta stimulation in COPASI
change the trigger of event "single_pulse_TGF_beta_washout"
from
"and(eq(stimulation_type, 2), eq(time, single_pulse_duration))" (for SBML-SAT)
to
"and(eq(stimulation_type, 2), gt(time, single_pulse_duration))" (for COPASI)
2. Notes for TGF-beta dose in terms of molecules per cell
(a) The following equation applies for conversion of TGF-beta dose in molecules per cell
TGF_beta_dose_mol_per_cell = initial TGF_beta_ex*1e-9*Vmed*6e23
(b) for standard experimental setup 1e6 cells in 2 mL medium
0.001 nM initial TGF_beta_ex is approximately equal to the dose of 1200 TGF-beta molecules/cell
0.050 nM initial TGF_beta_ex is approximately equal to the dose of 60000 TGF-beta molecules/cell
(c) For 1e6 cells in 10 mL medium, please change the initial compartment size of Vmed and the corresponding assignment rule for Vmed.
initial Vmed = 1e-8 (1e6 cells in 10 mL medium)
Vmed = 0.010/(1e6*exp(log(1.45)*time/1440)) (1e6 cells in 10 mL medium)
3. Please note that this model contains events and the medium compartment size is varied.
4. For the model simulation in SBML-SAT, please remove initialAssignments and save it as SBML Level 2 Verion 1 file.
2024-09-02 | BIOMD0000000342 | BioModels
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Project description:It is known that ubiquitination is important for T cell receptor (TCR) signaling during T cell activation but the breadth of ubiquitination events triggered during TCR signaling is not completely understood. This dataset utilizes di-glycine remnant profiling combined with mass spectrometry to identify a global landscape of ubiquitination events downstream of the TCR and to quantify changes ubiquitin abundance in response to TCR stimulation. Additionally, whole cell proteomics data were generated to measure protein abundances during TCR stimulation. Mouse primary T cells were isolated, proliferated and either remained resting or stimulated with CD3/CD28 to activate downstream signaling through the TCR and co-stimulatory pathways. Di-glycine remnant profiling and whole cell proteomics was performed on rested cells and cells that had undergone CD3/CD28 TCR stimulation for 4 hours. These data were analyzed to identify the ubiquitination events during TCR activation and to quantify the change in peptide-based ubiquitin abundance and total protein abundance over the course of the 4 hour TCR stimulation. Integration of di-glycine and whole cell proteomics was used to generate protein-specific predictions of whether ubiquitination events downstream of TCR signaling lead to a decrease in associated protein abundance. The analysis of these data suggests that T cell activation leads to an increase in ubiquitination that is not associated with proteasomal or lysosomal degradation.
2019-05-09 | PXD012831 | Pride
Project description:Translational research is commonly performed in the C57B6/J mouse strain, chosen for its genetic homogeneity and phenotypic uniformity. Here, we evaluate the suitability of the white-footed deer mouse (Peromyscus leucopus) as a model organism for aging research, offering a comparative analysis against C57B6/J and diversity outbred (DO) Mus musculus strains. Our study includes comparisons of body composition, skeletal muscle function, and cardiovascular parameters, shedding light on potential applications and limitations of P. leucopus in aging studies. Notably, P. leucopus exhibits distinct body composition characteristics, emphasizing reduced muscle force exertion and a unique metabolism, particularly in fat mass. Cardiovascular assessments showed changes in arterial stiffness, challenging conventional assumptions and highlighting the need for a nuanced interpretation of aging-related phenotypes. Our study also highlights inherent challenges associated with maintaining and phenotyping P. leucopus cohorts. Behavioral considerations, including anxiety-induced responses during handling and phenotyping assessment, pose obstacles in acquiring meaningful data. Moreover, the unique anatomy of P. leucopus necessitates careful adaptation of protocols designed for Mus musculus. While showcasing potential benefits, further extensive analyses across broader age ranges and larger cohorts are necessary to establish the reliability of P. leucopus as a robust and translatable model for aging studies.
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Project description:BackgroundCopy number variation is an important dimension of genetic diversity and has implications in development and disease. As an important model organism, the mouse is a prime candidate for copy number variant (CNV) characterization, but this has yet to be completed for a large sample size. Here we report CNV analysis of publicly available, high-density microarray data files for 351 mouse tail samples, including 290 mice that had not been characterized for CNVs previously.ResultsWe found 9634 putative autosomal CNVs across the samples affecting 6.87% of the mouse reference genome. We find significant differences in the degree of CNV uniqueness (single sample occurrence) and the nature of CNV-gene overlap between wild-caught mice and classical laboratory strains. CNV-gene overlap was associated with lipid metabolism, pheromone response and olfaction compared to immunity, carbohydrate metabolism and amino-acid metabolism for wild-caught mice and classical laboratory strains, respectively. Using two subspecies of wild-caught Mus musculus, we identified putative CNVs unique to those subspecies and show this diversity is better captured by wild-derived laboratory strains than by the classical laboratory strains. A total of 9 genic copy number variable regions (CNVRs) were selected for experimental confirmation by droplet digital PCR (ddPCR).ConclusionThe analysis we present is a comprehensive, genome-wide analysis of CNVs in Mus musculus, which increases the number of known variants in the species and will accelerate the identification of novel variants in future studies.
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Project description:BackgroundLong terminal repeat (LTR) retrotransposons make up a large fraction of the typical mammalian genome. They comprise about 8% of the human genome and approximately 10% of the mouse genome. On account of their abundance, LTR retrotransposons are believed to hold major significance for genome structure and function. Recent advances in genome sequencing of a variety of model organisms has provided an unprecedented opportunity to evaluate better the diversity of LTR retrotransposons resident in eukaryotic genomes.ResultsUsing a new data-mining program, LTR_STRUC, in conjunction with conventional techniques, we have mined the GenBank mouse (Mus musculus) database and the more complete Ensembl mouse dataset for LTR retrotransposons. We report here that the M. musculus genome contains at least 21 separate families of LTR retrotransposons; 13 of these families are described here for the first time.ConclusionsAll families of mouse LTR retrotransposons are members of the gypsy-like superfamily of retroviral-like elements. Several different families of unrelated non-autonomous elements were identified, suggesting that the evolution of non-autonomy may be a common event. High sequence similarity between several LTR retrotransposons identified in this study and those found in distantly-related species suggests that horizontal transfer has been a significant factor in the evolution of mouse LTR retrotransposons.
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