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

GSE262290 Mus musculus (mouse) RNA-seq (gene expression) 156 samples Submitted 2024/03/27 Platform GPL21103
At a glance

RNA-seq (gene expression) · mouse · 156 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
156 samples: 15 conditions, mostly with about 10 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. The specific molecular mechanisms that drive aging are poorly understood, especially the contribution of the microbiota in these processes. Here, we combined multi-omics with metabolic modeling in mice to comprehensively characterize host–microbiome interactions and how they are affected by aging.
Read the full summary ↓
Our findings reveal a complex dependency of host metabolism on microbial functions, including previously known as well as novel interactions. We observed a pronounced reduction in metabolic activity within the aging microbiome, which we attribute to reduced beneficial interactions in the microbial community and a reduction in the metabolic output of the microbiome. These microbial changes coincided with a corresponding downregulation of key host pathways predicted by our model that are crucial for maintaining intestinal barrier function, cellular replication, and homeostasis. Our results elucidate potential microbiome–host interactions that may influence host aging processes, focusing on microbial nucleotide metabolism as a pivotal factor in aging dynamics.
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
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.

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 GSE262290_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA1090973 and SRA study SRP497311. Searching any of these in the dataset finder brings you back here.

Study design
15 conditions, mostly with about 10 replicates each
Colon, 30 Months, ×12 Liver, 30 Months, ×12 Brain, 30 Months, ×12 Colon, 2 Months, ×10 Colon, 9 Months, ×10 Colon, 15 Months, ×10 Colon, 24 Months, ×10 Liver, 2 Months, ×10 +7 more

Supports a between-group comparison across 156 samples.

How we read this: 15 replicated groups read from 156 sample titles; they account for 156 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

+ 116 more — browse all 156 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.