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Metabolic modeling reveals the aging-associated decline of host-microbiome metabolic interactions in mice

GSE278548 Mus musculus (mouse) RNA-seq (gene expression) 119 samples Submitted 2024/10/15 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 119 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
119 samples: 12 conditions, mostly with about 8 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
Metabolic modelling reveals the aging-associated decline of host-microbiome metabolic interactions in miceNature microbiology · 2025
Summary (written by the submitters)
Aging is the predominant cause of morbidity and mortality in industrialized countries, yet the molecular mechanisms driving aging and especially the contribution by the microbiome remain unclear. We combined multi-omics with metabolic modeling to comprehensively characterize host–microbiome interactions during aging in mice. Our findings reveal a complex dependency of host metabolism on known and novel microbial interactions.
Read the full summary ↓
We observed a pronounced reduction in metabolic activity within the aging microbiome accompanied by reduced beneficial interactions between bacterial species. These microbial changes coincided with increased inflammaging as well as a corresponding downregulation of key host pathways, predicted by our model to be microbiome-dependent, that are crucial for maintaining intestinal barrier function, cellular replication, and homeostasis. Our results elucidate microbiome–host interactions that potentially influence host aging processes, focusing on microbial nucleotide metabolism as a pivotal factor in aging dynamics. These pathways could serve as future targets for the development of microbiome-based anti-aging therapies.
Published in
Metabolic modelling reveals the aging-associated decline of host-microbiome metabolic interactions in mice
Best L, Dost T, Esser D et al. · Nature microbiology 2025 · PMID 40140706 · doi:10.1038/s41564-025-01959-z
This dataset
Open GSE278548 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 GSE278548_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 PRJNA1167759 and SRA study SRP536078. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40140706) ↗
Study design
12 conditions, mostly with about 8 replicates each
Liver_CONVD ×8 Liver_GF ×8 Liver_CONV ×8 gWAT_CONVD ×8 gWAT_GF ×8 Quadriceps_CONVD ×8 Quadriceps_GF ×8 Quadriceps_CONV ×8 +28 more

Supports a between-group comparison across 95 samples.

How we read this: 12 replicated groups read from 119 sample titles; they account for 95 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

+ 79 more — browse all 119 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.