← BioTransfer GEO Dataset Finder
GEO series

Microbiota-Derived Isovalerate Ameliorates Sex-Specific Gut Barrier Dysfunction in Malnutrition

GSE316654 Homo sapiens (human) RNA-seq (gene expression) 16 samples Submitted 2026/07/24 Platform GPL34284
At a glance

RNA-seq (gene expression) · human · 16 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
Homo sapiens (human)
Samples
16 samples: 16 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)
Malnutrition is a major global health challenge that increases intestinal permeability and susceptibility to sepsis, yet the mechanisms driving barrier dysfunction remain poorly defined. We aimed to identify how the gut microbiome and microbiota-derived metabolites regulate intestinal barrier integrity during malnutrition. We used a low-protein, low-fat diet (LPLFD) to induce malnutrition in specific pathogen-free (SPF) and germ-free (GF) mice.
Read the full summary ↓
Colonic permeability and mucus thickness were quantified. Metabolomics identified microbiota-derived metabolites altered by malnutrition. Human colonoids were used to test mechanistic effects of candidate metabolites. Barrier restoration was evaluated following colonic administration of isovalerate or oral supplementation with its precursor amino acid, leucine. LPLFD-induced malnutrition increased colonic permeability and reduced mucus thickness in male, but not female, SPF mice. These defects were absent in malnourished GF mice, indicating a microbiota-dependent and sexually dimorphic mechanism of barrier disruption. Metabolomic analysis revealed reduced colonic levels of branched-chain fatty acids (BCFAs) in malnourished mice. Supplementation of human colonoids with the BCFA isovalerate improved barrier function and altered expression of genes associated with epithelial junctional complexes. Restoring isovalerate levels, either directly via colonic administration or indirectly through oral leucine supplementation, partially rescued barrier defects in malnourished male mice. These findings identify BCFAs, particularly isovalerate, as essential microbiota-derived regulators of intestinal barrier integrity during malnutrition. This work reveals a sex-specific, microbiota-dependent pathway of barrier dysfunction and highlights microbial metabolites as promising therapeutic targets for mitigating sepsis risk in undernourished populations.
This dataset
Open GSE316654 in finder → Find more human 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 GSE316654_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 PRJNA1403545 and SRA study SRP662840. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
16 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 16 sample titles: 16 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
Datasets on a similar topic

Search all human RNA-seq datasets in GEO →

Share this dataset

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.