GEO series

Control of Inflammatory Response by Tissue Microenvironment [RNA-seq]

GSE269298 Mus musculus (mouse) RNA-seq (gene expression) 32 samples Submitted 2025/06/03 Platform GPL19057

At a glance

RNA-seq (gene expression) · mouse · 32 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: 32 samples: 14 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: Regulation of inflammatory responses by pH-dependent transcriptional condensatesCell · 2025

Summary (written by the submitters)

Inflammation is an essential defense response but operates at the cost of normal functions. Whether and how the negative impact of inflammation is monitored remains largely unknown. Acidification of the tissue microenvironment is associated with inflammation. Here we investigated whether macrophages sense tissue acidification to adjust inflammatory responses.

Read the full summary ↓

We found that acidic pH restructured the inflammatory response of macrophages in a gene-specific manner. We identified mammalian BRD4 as a novel intracellular pH sensor. Acidic pH disrupts the transcription condensates containing BRD4 and MED1, via histidine-enriched intrinsically disordered regions. Crucially, decrease in macrophage intracellular pH is necessary and sufficient to regulate transcriptional condensates in vitro and in vivo, acting as negative feedback to regulate the inflammatory response. Collectively, these findings uncovered a pH-dependent switch in transcriptional condensates that enables environmental sensing to directly control inflammation, with a broader implication for calibrating the magnitude and quality of inflammation by the inflammatory cost.

Published in

Regulation of inflammatory responses by pH-dependent transcriptional condensates

Wu Z, Pope SD, Ahmed NS et al. · Cell 2025 · PMID 40680734 · doi:10.1016/j.cell.2025.06.033

This dataset

Open GSE269298 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 GSE269298_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 PRJNA1120919 and SRA study SRP512306. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40680734) ↗

Study design

14 conditions, mostly in duplicate

BMDMs, pH 7.4 0h, ×2 BMDMs, pH 7.4 0h, LPS 4h, ×2 BMDMs, pH 6.5 4h, ×2 BMDMs, pH 6.5 4h, LPS 4h, ×2 BMDMs, untreated, ×2 BMDMs, untreated, LPS, ×2 BMDMs, JQ1, ×2 BMDMs, JQ1,LPS, ×2 +10 more

Supports a between-group comparison across 28 samples.

How we read this: 14 replicated groups read from 32 sample titles; they account for 28 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

GSM8312549 BMDMs, pH 7.4 0h, rep1 BMDMs, pH 7.4 0h,
GSM8312550 BMDMs, pH 7.4 0h, rep2 BMDMs, pH 7.4 0h,
GSM8312551 BMDMs, pH 7.4 0h, LPS 4h, rep1 BMDMs, pH 7.4 0h, LPS 4…
GSM8312552 BMDMs, pH 7.4 0h, LPS 4h, rep2 BMDMs, pH 7.4 0h, LPS 4…
GSM8312553 BMDMs, pH 6.5 4h, rep1 BMDMs, pH 6.5 4h,
GSM8312554 BMDMs, pH 6.5 4h, rep2 BMDMs, pH 6.5 4h,
GSM8312555 BMDMs, pH 6.5 4h, LPS 4h, rep1 BMDMs, pH 6.5 4h, LPS 4…
GSM8312556 BMDMs, pH 6.5 4h, LPS 4h, rep2 BMDMs, pH 6.5 4h, LPS 4…
GSM8312557 BMDMs, untreated, rep1 BMDMs, untreated,
GSM8312558 BMDMs, untreated, rep2 BMDMs, untreated,
GSM8312559 BMDMs, untreated, LPS, rep1 BMDMs, untreated, LPS,
GSM8312560 BMDMs, untreated, LPS, rep2 BMDMs, untreated, LPS,
GSM8312561 BMDMs, JQ1, rep1 BMDMs, JQ1,
GSM8312562 BMDMs, JQ1, rep2 BMDMs, JQ1,
GSM8312563 BMDMs, JQ1,LPS, rep1 BMDMs, JQ1,LPS,
GSM8312564 BMDMs, JQ1,LPS, rep2 BMDMs, JQ1,LPS,
GSM8312565 BMDMs, iBET, rep1 BMDMs, iBET,
GSM8312566 BMDMs, iBET, rep2 BMDMs, iBET,
GSM8312567 BMDMs, iBET,LPS, rep1 BMDMs, iBET,LPS,
GSM8312568 BMDMs, iBET,LPS, rep2 BMDMs, iBET,LPS,
GSM8312569 BMDMs, MS645, rep1 BMDMs, MS645,
GSM8312570 BMDMs, MS645, rep2 BMDMs, MS645,
GSM8312571 BMDMs, MS645,LPS, rep1 BMDMs, MS645,LPS,
GSM8312572 BMDMs, MS645,LPS, rep2 BMDMs, MS645,LPS,
GSM8312573 BMDMs, 1,6-hexanediol, rep1 BMDMs, 1,6-hexanediol,
GSM8312574 BMDMs, 1,6-hexanediol, rep2 BMDMs, 1,6-hexanediol,
GSM8312575 BMDMs, 1,6-hexanediol,LPS, rep1 BMDMs, 1,6-hexanediol,L…
GSM8312576 BMDMs, 1,6-hexanediol,LPS, rep2 BMDMs, 1,6-hexanediol,L…
GSM8312577 BMDMs, pH6.5, LPS
GSM8312578 BMDMs, pH6.5 switch to pH7.4 0h, LPS
GSM8312579 BMDMs, pH6.5 switch to pH7.4 2h, LPS
GSM8312580 BMDMs, pH6.5 switch to pH7.4 4h, LPS

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