GEO series

Gut microbe-derived metabolites drive psoriatic inflammation via modulation of skin Th17 cells

GSE298131 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 18 samples Submitted 2025/08/22 Platform GPL24247

At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 18 samples

What it is: ChIP-seq / ATAC-seq (genome binding and open chromatin)Where proteins bind the genome, or which regions are open and active.
Organism: Mus musculus (mouse)
Samples: 18 samples: 8 conditions, mostly in duplicateGroups 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: Gut microbe-derived metabolites drive psoriatic inflammation via modulation of skin Th17 cellsImmunity · 2025

Summary (written by the submitters)

The maintenance of tissue-specific chronic inflammation results from the interplay of genetic and unidentified environmental factors. Here, we describe an immunoregulatory role for an environmentally driven microbial metabolite in Card14E138A/+-induced spontaneous psoriasis. Through metabolite screening, we demonstrate chronic skin inflammation is accompanied by alterations microbial metabolite.

Read the full summary ↓

Notably, depletion of gut, not skin, microbes alleviates disease symptoms. We further identify indoxyl sulfate (I3S), a bacteriogenic metabolite, as a key driver of psoriatic inflammation and confirm that gut-resident indole-producing microbiota mediate this process. Mechanistically, indole-producing microbiota promote host I3S biothsynthesis via a metabolic relay, and I3S potentiates skin inflammation by reshaping chromatin accessibility in skin Th17 cells through AHR signaling. In human psoriasis cohorts, serum I3S levels correlate with disease severit. In summary, our study uncovers a mechanistic link between gut microbial factors and type 3 skin inflammation, highlighting targeting gut microbiota as a strategy for mitigating skin inflammation.

Published in

Gut microbe-derived metabolites drive psoriatic inflammation via modulation of skin Th17 cells

Wang C, Dai S, Zhang S et al. · Immunity 2025 · PMID 40930076 · doi:10.1016/j.immuni.2025.08.006

This dataset

Open GSE298131 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 GSE298131_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: Look for peak files (.bed, .narrowPeak) and signal tracks (.bigWig) among the supplementary files; the raw reads are on ENA.

Also filed as BioProject PRJNA1266242 and SRA study SRP587480. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40930076) ↗

Study design

8 conditions, mostly in duplicate

Skin-WAT ×3 Skin-ABX ×3 IS ×2 IN ×2 C ×2 ATAC-IS ×2 ATAC-IN ×2 ATAC-C ×2

Supports a between-group comparison across 18 samples.

How we read this: 8 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

GSM9008924 Skin-WAT-1 Skin-WAT
GSM9008925 Skin-WAT-2 Skin-WAT
GSM9008926 Skin-WAT-3 Skin-WAT
GSM9008927 Skin-ABX-1 Skin-ABX
GSM9008928 Skin-ABX-2 Skin-ABX
GSM9008929 Skin-ABX-3 Skin-ABX
GSM9008930 IS-1 IS
GSM9008931 IS-2 IS
GSM9008932 IN-1 IN
GSM9008933 IN-2 IN
GSM9008934 C-1 C
GSM9008935 C-2 C
GSM9008936 ATAC-IS-1 ATAC-IS
GSM9008937 ATAC-IS-2 ATAC-IS
GSM9008938 ATAC-IN-1 ATAC-IN
GSM9008939 ATAC-IN-2 ATAC-IN
GSM9008940 ATAC-C-1 ATAC-C
GSM9008941 ATAC-C-2 ATAC-C

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