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PPARγ-Mediated Ferroptosis in Macrophages Enhances Persistent Pulmonary Infction by Mycobacterium tuberculosis

GSE275146 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 16 samples Submitted 2026/04/24 Platform GPL24247Platform GPL30172
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 16 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
16 samples: 5 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
Mycobacterium tuberculosis IDH-PPARγ interaction suppresses GPX4 to drive macrophage ferroptosis and sustain persistent infectionNature communications · 2026
Summary (written by the submitters)
In this study, we found that Mycobacterium tuberculosis (Mtb) uses the PPARγ-GPX4 axis to induce ferroptosis in host cells, promoting persistent infection. Elevated PPARγ levels in macrophages post-Mtb infection, due to direct interactions with Mtb IDH and impaired degradation, lead to suppressed GPX4 expression and increased lipid peroxidation. Deleting PPARγ reduces lung inflammation, Mtb burden, and restores GPX4 expression in infected macrophages. This discovery of Mtb hijacking PPARγ to induce ferroptosis suggests a promising target for tuberculosis treatment.
Published in
Mycobacterium tuberculosis IDH-PPARγ interaction suppresses GPX4 to drive macrophage ferroptosis and sustain persistent infection
Pu W, Zhang X, Tian M et al. · Nature communications 2026 · PMID 42259813 · doi:10.1038/s41467-026-74032-w
This dataset
Open GSE275146 in finder → Find more mouse ChIP / ATAC / CUT&Tag 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 GSE275146_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 PRJNA1149689 and SRA study SRP527301. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 42259813) ↗
Study design
5 conditions, mostly in duplicate
RAW_NC_ATACseq_rp ×3 RAW_H37Ra_ATACseq_rp ×3 RAW_CUTTag_H3K27ac ×2 RAW_RA_CUTTag_H3K27ac ×2 RAW_Rosi_CUTTag_H3K27ac ×2 RAW_PPARg_NC ×1 RAW_PPARg_H37Ra ×1 RAW_H3K27ac_NC ×1 +1 more

Supports a between-group comparison across 12 samples.

How we read this: 5 replicated groups read from 16 sample titles; they account for 12 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
Datasets on a similar topic

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