← BioTransfer GEO Dataset Finder
GEO series

Single-cell multiomics uncovers an endothelial mechanosensitive PIEZO1-IL-33 axis driving pulmonary fibrosis

GSE314943 Mus musculus (mouse) Single-cell RNA-seq 18 samples Submitted 2026/01/30 Platform GPL19057
At a glance

Single-cell RNA-seq · mouse · 18 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
Organism
Mus musculus (mouse)
Samples
18 samples: 18 samples, each with a distinct title — no replicated groupsGroups 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
Single-cell multiomics uncovers an endothelial mechanosensitive PIEZO1-IL-33 axis driving pulmonary fibrosisNature communications · 2026
Summary (written by the submitters)
Pulmonary fibrosis (PF) represents a progressive interstitial lung disease marked by excessive extracellular matrix deposition and architectural distortion. Vascular endothelial cells (ECs) critically contribute to fibrogenesis through paracrine secretion of pro-fibrotic mediators, yet their mechanobiological regulation remains elusive.
Read the full summary ↓
UsingThrough integrated single-cell multi-omics profiling of human PF specimens and experimental fibrosis models induced by bleomycin or silica (Bleomycin/SiO2-induced), we identify identified mechanosensitive Piezo1 upregulation in ECs as a hallmark of fibrotic progression. Endothelial-specific Piezo1 knockout significantly attenuates attenuated Bleomycin-induced fibrotic remodeling, establishing its pathogenic necessity. Mechanistically, Piezo1 activation promotes promoted PF development by inducing a pro-fibrotic molecule interleukin-33 (IL-33) secretion via CAPN2-mediated STAT3 phosphorylation. These findings suggest that the endothelial PIEZO1-CAPN2-STAT3-IL-33 axis is a promising therapeutic target for PF intervention.
Published in
Single-cell multiomics uncovers an endothelial mechanosensitive PIEZO1-IL-33 axis driving pulmonary fibrosis
Zhang L, Gui X, Hou R et al. · Nature communications 2026 · PMID 41862476 · doi:10.1038/s41467-026-70193-w
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 GSE314943_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: 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 PRJNA1393397 and SRA study SRP657947. Searching any of these in the dataset finder brings you back here.

Study design
18 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 18 sample titles: 18 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
Datasets on a similar topic

Search all mouse ChIP / ATAC / CUT&Tag 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.