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The Impact of TLR5 on Liver Function in Age-Related Metabolic Disorders

GSE272622 Mus musculus (mouse) RNA-seq (gene expression) 20 samples Submitted 2025/06/18 Platform GPL21626
At a glance

RNA-seq (gene expression) · mouse · 20 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
20 samples: 5 × WT-ND vs 5 × WT-MCD vs 5 × TLR5 KO-ND vs 5 × TLR5 KO-MCDGroups 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
The Impact of Toll-Like Receptor 5 on Liver Function in Age-Related Metabolic DisordersAging cell · 2025
Summary (written by the submitters)
Toll-like receptor 5 (TLR5) plays a critical role beyond its traditional function in innate immunity, significantly impacting metabolic regulation and liver health. Previously, we reported that TLR5 activation extends healthspan and lifespan in aging mice. This study demonstrates that TLR5 deficiency leads to pronounced metabolic abnormalities with age, primarily affecting liver metabolic functions rather than intestinal inflammation.
Read the full summary ↓
Comprehensive RNA sequencing analysis revealed that TLR5 deficiency induces gene expression changes in liver tissue similar to those caused by the methionine-choline deficient (MCD) diet, particularly affecting lipid metabolism and circadian rhythm-related genes. TLR5 KO mice displayed an increased propensity for liver fibrosis and lipid accumulation under the MCD diet, exacerbating liver pathology. Both hepatocytes and hepatic stellate cells in TLR5 KO mice were functionally impacted, leading to metabolic dysfunction and fibrosis. These findings suggest that TLR5 could be a significant target for addressing metabolic diseases that arise and worsen with aging. Furthermore, understanding the mechanisms by which TLR5 activation extends healthspan could provide valuable insights into therapeutic strategies for enhancing longevity and managing age-related metabolic disorders.
Published in
The Impact of Toll-Like Receptor 5 on Liver Function in Age-Related Metabolic Disorders
Kim DH, Go HS, Jeon EJ et al. · Aging cell 2025 · PMID 39957532 · doi:10.1111/acel.70009
This dataset
Open GSE272622 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 GSE272622_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 PRJNA1137845 and SRA study SRP520956. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39957532) ↗
Study design
5 × WT-ND vs 5 × WT-MCD vs 5 × TLR5 KO-ND vs 5 × TLR5 KO-MCD

Supports a between-group comparison across 20 samples.

How we read this: 4 replicated groups read from 20 sample titles; they account for 20 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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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.