← BioTransfer GEO Dataset Finder
GEO series

Microbiome-produced nicotinic acid controls colon regional identity and injury susceptibility (scRNAseq)

GSE285770 Mus musculus (mouse) Single-cell RNA-seq 13 samples Submitted 2026/03/09 Platform GPL24247
At a glance

Single-cell RNA-seq · mouse · 13 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
13 samples: 5 conditions, mostly in triplicateGroups 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
Microbiome-produced nicotinic acid controls colon regional identity and injury susceptibilityCell · 2026
Summary (written by the submitters)
The gut epithelium exhibits regional specialization critical for its function and susceptibility to disease, as gut diseases localize to specific regions of the organ. However, how regionalization is established and its influence on disease susceptibility remain poorly understood. Here, we investigate the role of the gut microbiome—which comprises all microorganisms residing in the gut lumen and is itself regionalized—in regulating regionalization of the colon.
Read the full summary ↓
We demonstrate that the regional identity of colonocytes is disrupted in mice lacking a microbiome. Mechanistically, we show that the proximal colonic microbiome produces high levels of nicotinic acid, which induces Pparα expression to establish proximal colonocyte identity. Furthermore, we find that microbiome-driven proximal identity confers protection against tissue injury in the mouse. Finally, we show that colon regionalization and the loss of proximal identity during disease are also present in human.
Published in
Microbiome-produced nicotinic acid controls colon regional identity and injury susceptibility
Rispal J, Garcia JR, Palikuqi B et al. · Cell 2026 · PMID 41812662 · doi:10.1016/j.cell.2026.02.007
This dataset
Open GSE285770 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 GSE285770_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: 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 PRJNA1205804 and SRA study SRP555034. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41812662) ↗
Study design
5 conditions, mostly in triplicate
scRNAseq_Abx_cDNA ×3 scRNAseq_Abx_MULTI ×3 scRNAseq_Abx_MULTI_repeat ×3 scRNAseq_GF_cDNA ×2 scRNAseq_GF_MULTI ×2

Supports a between-group comparison across 13 samples.

How we read this: 5 replicated groups read from 13 sample titles; they account for 13 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.