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A low protein diet drives short and long-term improvements in metabolic health in a mouse model of sleeve gastrectomy

GSE307617 Mus musculus (mouse) RNA-seq (gene expression) 62 samples Submitted 2025/10/14 Platform GPL34290
At a glance

RNA-seq (gene expression) · mouse · 62 samples

What it is
RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
Organism
Mus musculus (mouse)
Samples
62 samples: 62 samples, each with a distinct title — no replicated groupsGroups are read from the sample names, not from the paper. Check the list below.
Data you can get
A processed table (series matrix) and supplementary files from NCBI; the raw sequencing reads from ENA. Which of these hold counts depends on the study, so check the file list.
Summary (written by the submitters)
Despite the largely beneficial impact of bariatric surgery on obesity and metabolic disease, many patients continue to suffer from obesity after surgery and weight recurrence is common. The success of bariatric surgery may be impacted by diet. While bariatric surgery guidelines recommend a high-protein diet following surgery based on the theory that this will preserve lean mass, emerging evidence suggests that both humans and mice are metabolically healthier when consuming low protein diets.
Read the full summary ↓
Here, we assess the effect of varying dietary protein levels on post-surgical weight loss and weight regain in a mouse model of bariatric surgery, sleeve gastrectomy. We find that a low protein diet optimally drives post-surgical weight loss, boosting energy expenditure and improving blood glucose regulation. Using a multi-omics approach, we identified clusters of differentially expressed genes and metabolites that correlated with these phenotypes and find that diet heavily influences the molecular response of the liver to sleeve gastrectomy. These results suggest that current post-surgical dietary guidelines recommending a high protein diet may limit both the short and long-term benefits of surgery and lead us to conclude that a low protein diet may improve patient outcomes.
This dataset
Open GSE307617 in finder → Find more mouse RNA-seq datasets →
Download · which file do I need?

Direct links to NCBI and ENA, 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.

Series matrix ↓
2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE307617_RAW.tar (it can run to tens of gigabytes).

All supplementary files ↗ Whole study · RAW.tar ↓
3 · Start from the raw reads

Raw sequencing reads

The original FASTQ files, straight from the sequencer, held at ENA. Large, and you align them yourself, so only choose this if you need to re-process the study from scratch.

Raw reads on ENA ↗

What the files usually look like: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.

Also filed as BioProject PRJNA1322390 and SRA study SRP618759. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
62 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 62 sample titles: 62 distinct titles with little repetition. These groups are guessed from the sample names, not taken from the paper, so check them against the sample list below before relying on them.

Samples in this study

+ 22 more — browse all 62 samples with per-sample file links →

Datasets on a similar topic

Search all mouse RNA-seq datasets in GEO →

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Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.