← BioTransfer GEO Dataset Finder
GEO series

Intestinal mucosal barrier repair and immune regulation with an AI-developed gut-restricted PHD inhibitor

GSE280622 Mus musculus (mouse) RNA-seq (gene expression) 18 samples Submitted 2024/12/11 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 18 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
18 samples: 6 × colon_sham_day2 vs 6 × colon_Vehicle_day2 vs 6 × PHDi-ISM012-042_day2Groups 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
Intestinal mucosal barrier repair and immune regulation with an AI-developed gut-restricted PHD inhibitorNature biotechnology · 2025
Summary (written by the submitters)
Hypoxia-inducible factor-prolyl hydroxylase (HIF-PHD) inhibitors have been approved for treating renal anemia, yet have failed clinical testing for inflammatory bowel disease (IBD) due to lack of efficacy. We use a multimodel multimodal generative AI platform to design an orally gut-restricted selective PHD1/2 inhibitor, which exhibits favorable safety and pharmacokinetic profiles in preclinical studies. ISM012-042 restores intestinal barrier function and alleviates gut inflammation in multiple experimental colitis models.
Published in
Intestinal mucosal barrier repair and immune regulation with an AI-developed gut-restricted PHD inhibitor
Fu Y, Ding X, Zhang M et al. · Nature biotechnology 2025 · PMID 39663371 · doi:10.1038/s41587-024-02503-w
This dataset
Open GSE280622 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 GSE280622_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 PRJNA1179502 and SRA study SRP541872. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39663371) ↗
Study design
6 × colon_sham_day2 vs 6 × colon_Vehicle_day2 vs 6 × PHDi-ISM012-042_day2

Supports a between-group comparison across 18 samples.

How we read this: 3 replicated groups read from 18 sample titles; they account for 18 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

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.