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Toll-Like-Receptor 5 Reduces Lung Dysbiosis and Protects Against Pulmonary Fibrosis

GSE314584 Mus musculus (mouse) RNA-seq (gene expression) 124 samples Submitted 2026/04/03 Platform GPL19057Platform GPL16417Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 124 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
124 samples: 92 distinct titles, 10 of them repeatedGroups 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
Toll-like receptor 5 protects against murine lung fibrosis through reduced dysbiosis, and TLR5 deficiency is associated with human IPFScience translational medicine · 2026
SuperSeries — this record groups several sub-series.
Summary (written by the submitters)
This SuperSeries is composed of the SubSeries listed below.
Published in
Toll-like receptor 5 protects against murine lung fibrosis through reduced dysbiosis, and TLR5 deficiency is associated with human IPF
Sakamachi Y, Wiley E, Trempus CS et al. · Science translational medicine 2026 · PMID 42234773 · doi:10.1126/scitranslmed.adw1028
This dataset
Open GSE314584 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 GSE314584_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 PRJNA1391547 and SRA study SRP656851. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 42234773) ↗
Study design
92 distinct titles, 10 of them repeated
WT ×9 KO ×8 WTD ×5 KOD ×4 Tlr5fx/fx SPC-Cre + bleomycin Rep S ×3 Tlr5fx/fx SPC-Cre + TLR5-agonist/bleomycin Re… ×3 Tlr5 wildtype + ABX/bleomycin Rep S ×3 Tlr5 wildtype + ABX/TLR5-agonist/bleomycin Re… ×3 +2 more

How we read this: Read from 124 sample titles: 92 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

+ 84 more — browse all 124 samples with per-sample file links →

Datasets on a similar topic

Search all mouse 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.