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Insights into microbial modulation of host peripheral lipid and glucose metabolism using mouse gut organoids

GSE59644 Mus musculus (mouse) Expression microarray 32 samples Submitted 2014/07/23 Platform GPL6885
At a glance

Expression microarray · mouse · 32 samples

What it is
Expression microarrayGene activity read on a chip (the older technology that RNA-seq replaced).
Organism
Mus musculus (mouse)
Samples
32 samples
Data you can get
A processed expression table (series matrix) and the array files, from NCBI.
Summary (written by the submitters)
The gastrointestinal microbiota is involved in the development of various diseases, such as obesity and diabetes, by affecting nutrient acquisition, energy balance, and metabolic signaling of the host. However, the underlying mechanisms of these host-microbiota interactions remain unclear. The aim of this study was to characterize effects of the microbiota on the host epithelium using a novel gastrointestinal model based on mouse organoids.
Read the full summary ↓
We have explored the transcriptional response of organoids upon exposure to short chain fatty acids (SCFA) and products generated by two conspicuous members of the gastrointestinal microbiota; Akkermansia muciniphila and Faecalibacterium prausnitzii. We observed that A. muciniphila metabolites affect a large variety of transcription factors and genes involved in cellular lipid metabolism and growth, supporting previous in vivo findings. F. prausnitzii products exerted only a weak effect on the host transcription profile. While, A. muciniphila, and its main metabolite propionate, both stimulate fasting-induced adipose factor/angiopoietin-like protein 4 (Fiaf/Angptl4) and Ppar? expression, important regulators of lipolysis and satiety. This work illustrates that specific members of the microbiota and their metabolites differentially modulate epithelial transcription in mouse organoid lines.
This dataset
Download · which file do I need?

Direct links to NCBI, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.

1 · Just have a look

Processed table

The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.

2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need.

All supplementary files ↗
3 · The original raw files

Whole study · RAW.tar

Everything the authors deposited as one archive (GSE59644_RAW.tar), including the raw array or instrument files. Can be large; the picker in step 2 takes just the samples you need.

What the files usually look like: For arrays the series matrix is normally the normalised expression table you want; the raw array files (CEL and similar) are in the RAW.tar.

Also filed as BioProject PRJNA255853. Searching any of these in the dataset finder brings you back here.

Samples in this study

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+ 32 more — browse all 32 samples with per-sample file links →

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