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Phagosome-mediated activation of STING by purine and pyrimidine-based bacterial cyclic dinucleotides

GSE331176 Mus musculus (mouse) RNA-seq (gene expression) 380 samples Submitted 2026/07/17 Platform GPL34290
At a glance

RNA-seq (gene expression) · mouse · 380 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
380 samples: 317 distinct titles, 21 of them repeatedGroups 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)
The cytoplasm harbors a spectrum of microbial sensory proteins. Beyond pathogens and their membrane disruptive activities, the contexts and mechanisms whereby bacterial molecules access cytoplasmic sensors are unknown. In this study, we describe the intracellular cyclic dinucleotide (CDN) sensor STING from humans, mice, and other animals as a driver of immune responses to a spectrum of CDNs produced by evolutionarily diverse bacteria, including those containing pyrimidine bases.
Read the full summary ↓
Diverse bacterial CDNs were present in murine tissues and increased in human inflammatory bowel diseases patients. After bacteriolysis in phagolysosomes, bacterial CDNs could activate STING via two CDN transporters. Systemic delivery of dead, CDN-laden bacteria promoted resistance to subcutaneous and liver-localized tumors in mice. X-ray crystallography of STING-CDN complexes revealed distinct binding modes for purine- and pyrimidine-based CDNs. We propose a connection between phagocytosis, bacterial CDNs, and STING that ensures cytoplasmic innate immune responses are a common outcome of host-bacteria interactions.
This dataset
Open GSE331176 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 GSE331176_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 PRJNA1467455 and SRA study SRP701543. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
317 distinct titles, 21 of them repeated
WT iBMDMs, 4hr time point, untreated, ×4 WT iBMDMs, 4hr time point, clearcoli, ×4 WT iBMDMs, 4hr time point, dacA+, ×4 Cgas-/- iBMDMs, 4hr time point, untreated, ×4 Cgas-/- iBMDMs, 4hr time point, clearcoli, ×4 Cgas-/- iBMDMs, 4hr time point, dacA+, ×4 Sting-/- iBMDMs, 4hr time point, untreated, ×4 Sting-/- iBMDMs, 4hr time point, clearcoli, ×4 +13 more

How we read this: Read from 380 sample titles: 317 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

+ 340 more — browse all 380 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.