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Life-long microbiome rejuvenation improves intestinal metabolism and inflammaging in mice [bulk RNA-seq]

GSE272841 Mus musculus (mouse) Single-cell RNA-seq 39 samples Submitted 2025/03/12 Platform GPL24247
At a glance

Single-cell RNA-seq · mouse · 39 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
Organism
Mus musculus (mouse)
Samples
39 samples: 6 conditions, mostly with about 5 replicates eachGroups 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.
Paper
Life-long microbiome rejuvenation improves intestinal barrier function and inflammaging in miceMicrobiome · 2025
Summary (written by the submitters)
Alterations in composition and function of the intestinal microbiota have been observed in organismal aging across a broad spectrum of animal phyla. Recent findings, which have been derived mostly in simple animal models, have even established a causal relationship between age-related microbial shifts and lifespan, suggesting microbiota-directed interventions as a potential tool to decelerate aging processes.
Read the full summary ↓
To test whether a life-long microbiome rejuvenation strategy could delay or even prevent aging in mammals, we performed recurrent fecal microbial transfer (FMT) in mice throughout life. Transfer material was either derived from 8-week-old mice (young microbiome, yMB) or from animals of the same age as the recipients (isochronic microbiome, iMB) as control. Physiological responses were analyzed by rotarod and a grip strength test, intestinal barrier function by FITC gavage and LAL assay, transcriptional responses by single cell RNA sequencing and microbiome function by 16S profiling and metagenomics. Colonization with yMB improved coordination and intestinal permeability compared to iMB. yMB encoded fewer pro-inflammatory factors and altered metabolic pathways favoring oxidative phosphorylation. Ecological interactions among bacteria in yMB were more antagonistic than in iMB hinting at more stable microbiome communities. Single cell RNA sequencing analysis of intestinal mucosa revealed a salient shift of cellular phenotypes in the yMB group with markedly increased ATP synthesis and mitochondrial pathways in enterocytes and TA cells but reduced inflammatory signaling in macrophages. Taken together, we demonstrate that life-long and repeated transfer of microbiota material from young mice improved age-related processes including motor coordination, intestinal permeability and immune cell phenotypes.
Published in
Life-long microbiome rejuvenation improves intestinal barrier function and inflammaging in mice
Sommer F, Bernardes JP, Best L et al. · Microbiome 2025 · PMID 40176137 · doi:10.1186/s40168-025-02089-8
This dataset
Open GSE272841 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 GSE272841_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA1139096 and SRA study SRP521553. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40176137) ↗
Study design
6 conditions, mostly with about 5 replicates each
control_Final ×11 8w_Final ×7 aging-MB_Final ×6 ctrl_w40 ×5 8w-mb_w40 ×5 aging-mb_w40 ×4 aging-mb_Final ×1

Supports a between-group comparison across 38 samples.

How we read this: 6 replicated groups read from 39 sample titles; they account for 38 of them. 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

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