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Coupling ER stress to STAT1-mediated immunity against bacterial infection

GSE287755 Homo sapiens (human) RNA-seq (gene expression) 12 samples Submitted 2025/03/31 Platform GPL30173
At a glance

RNA-seq (gene expression) · human · 12 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
Homo sapiens (human)
Samples
12 samples
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)
Endoplasmic reticulum (ER) stress and activation of the unfolded protein response (UPR) are hallmarks of pathogen infection. The UPR drives pro-inflammatory responses to ER stress but its role in interferon signaling is unknown. Using metabolomics approaches, we observed that pharmacological ER stress reprogrammed macrophage metabolism to a pro-inflammatory “M1-like” phenotype and enhanced the microbicidal activity of these cells to restrict bacterial infection.
Read the full summary ↓
Phospho-proteomics analysis showed that this anti-microbial response was mediated via the UPR serine/threonine-protein kinase/endoribonuclease IRE1 (ERN1) and activation of signal transducer and transcription activator 1 (STAT1) required for interferon signaling. We also demonstrated that blockade of IRE1 signaling by the bacterial pathogen Legionella pneumophila inhibited STAT1-mediated immune responses to infection. These findings reveal the potential for ER stress to initiate anti-microbial STAT1 signaling in the absence of other pro-inflammatory stimuli and how this response is inhibited by a bacterial pathogen during infection.
This dataset
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.

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 GSE287755_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA1214396 and SRA study SRP559241. Searching any of these in the dataset finder brings you back here.

Samples in this study

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+ 12 more — browse all 12 samples with per-sample file links →

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