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IL-17RC signaling connects intestinal microbiota and neuroimmune interactions in atherosclerosis

GSE322757 Mus musculus (mouse) RNA-seq (gene expression) 42 samples Submitted 2026/03/11 Platform GPL17021
At a glance

RNA-seq (gene expression) · mouse · 42 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
42 samples: 42 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.
Summary (written by the submitters)
While dysbiosis and inflammation were previously implicated in cardiovascular diseases, the circuits of how microbiota drives distant perivascular innervation, neuroinflammation, and atherosclerosis remains unknown. Here, we report that IL-17RC signaling in the intestine protects from atherosclerosis controlling intestinal barrier and microbiota, and loss of IL-17RC in intestinal epithelial cells alters microbiota, enhances perivascular innervation and aortic inflammation, augmenting the disease.
Read the full summary ↓
Neuronal outgrowth is functionally dependent on microbiota and is essential for neuroinflammation and augmentation of atherosclerosis as chemical denervation or chemogenetic inhibition reduces inflammation, macrophage activation and disease progression. Microbiota-dependent IL-17A producing gd T cells accumulate in the aorta to promote neuronal outgrowth and activation that can be reversed by gd T cell blockade. Perivascular neuron activation is further dependent on cell-autonomous IL-17 signaling as IL-17RC ablation in sympathetic neurons protected mice from microbiota-driven atherosclerosis. Together, our data illuminate how intestinal cytokine signaling distantly restrains neuroimmune interactions in aorta and uncovers a novel link between IL-17 signaling, microbiota, perivascular innervation and neuroimmune pro-inflammatory crosstalk instrumental for atherosclerosis progression.
This dataset
Open GSE322757 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 GSE322757_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 PRJNA1431413 and SRA study SRP680672. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
42 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 42 sample titles: 42 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

+ 2 more — browse all 42 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.