Altered de novo lipogenesis contributes to low adipose stores in cystic fibrosis mice.
Transcriptomics Dataset
FAIR Metrics
0 evaluations
General Information
AccessionGSE33319
TitleAltered de novo lipogenesis contributes to low adipose stores in cystic fibrosis mice.
DescriptionCystic fibrosis (CF) mouse models exhibit exocrine pancreatic function yet do not develop adipose stores to the levels of non-CF mice. CF mice homozygous for the Cftr mutation (F508del) at 3 weeks (post-weaning) and 6 weeks (young adult) of age had markedly less adipose tissue than non-CF mice. Both 3- and 6-week old mice had dietary lipid absorption and fecal lipid excretion comparable to non-CF controls. Fractional hepatic de novo synthesis of palmitate and stearate (de novo lipogenesis, DNL) as determined by deuterium incorporation was reduced in CF mice. At 3 weeks of age, F508del mice had significantly decreased DNL of palmitate and stearate, by 83%% and 80%%, respectively. By 6 weeks of age, DNL rates in non-CF mice remained unchanged as compared to 3-week old mice, while DNL rates of F508del mice were still reduced, by 33%% and 40%%, respectively. Adipose tissue fatty acid profiles were comparable in CF and non-CF mice, indicating that adipose differences are quantitative, not qualitative. A correspondingly lower content of deuterium-labeled fatty acids was found in CF adipose tissue, consistent with reduced deposition of newly made hepatic triglycerides and/or decreased adipose tissue lipogenesis. Hepatic transcriptome analysis revealed lower mRNA expression from several genes involved in fatty acid biosynthesis, suggesting down-regulation of several enzymes in fatty acids synthesis as a mechanism for the reduced lipogenesis. These novel data provide a model for altered fat and fatty acid metabolism in CF, independent of malabsorption, and may partly explain the inability of pancreatic enzyme replacement therapy to completely restore normal body mass to CF patients
Landing Pagehttps://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE33319
RepositoryGene Expression Omnibus
Tools used to analyze the dataset
Keyword
Dataset Accession
Enrichr
Published May 2016
A comprehensive gene set enrichment analysis web server 2016 update
7759
65
Characteristic Direction
Published March 2014
A geometrical multivariate approach to identify differentially expressed genes
26829
L1000CDS2
Published August 2016
An ultra-fast LINCS L1000 Characteristic Direction signature search engine
7756
GeneMANIA
Published June 2010
Biological network integration for gene prioritization and predicting gene function
7435
PAEA
Published November 2015
Enrichment analysis tool implementing the principal angle method
3879
Canned Analyses generated with the dataset
Filters  
Dataset Accession
Tool Name
Direction
Geneset
Interaction network and enrichment analysis of genes downregulated in cystic fibrosis
GeneMANIA, Characteristic Direction
The analysis explores the gene interaction network and pathway enrichment of the top 50 mo...
Interaction network and enrichment analysis of genes upregulated in cystic fibrosis
GeneMANIA, Characteristic Direction
The analysis explores the gene interaction network and pathway enrichment of the top 50 mo...
Small molecules which mimic cystic fibrosis
L1000CDS2, Characteristic Direction
The L1000 database was queried in order to identify small molecule perturbations which mim...
Small molecules which reverse cystic fibrosis
L1000CDS2, Characteristic Direction
The L1000 database was queried in order to identify small molecule perturbations which rev...
Enrichment analysis of genes dysregulated in cystic fibrosis
PAEA, Characteristic Direction
An enrichment analysis was performed on the top most dyresgulated genes determined by appl...
Enrichment analysis of genes downregulated in cystic fibrosis
Enrichr, Characteristic Direction
An enrichment analysis was performed on the top 500 most downregulated genes identified by...
Enrichment analysis of genes upregulated in cystic fibrosis
Enrichr, Characteristic Direction
An enrichment analysis was performed on the top 500 most upregulated genes identified by a...
FAIR Evaluation
Sorry, you must be signed in to evaluate this object.