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c-Myc Inhibits Macrophage Antimycobacterial Response in Mycobacterium tuberculosis Infection

GSE298739 Mus musculus (mouse) RNA-seq (gene expression) 35 samples Submitted 2025/08/28 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 35 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
35 samples: 12 conditions, mostly in triplicateGroups 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
c-Myc Inhibits Macrophage Antimycobacterial Response in Mycobacterium tuberculosis InfectionThe Journal of infectious diseases · 2025
Summary (written by the submitters)
Mycobacterium tuberculosis (MTB) is a major global cause of mortality, responsible for over a million deaths each year. Despite this burden, natural immunity prevents disease in more than 90% of exposed individuals. Previous studies have identified interferon-gamma (IFN-γ) as a key regulator of innate immune defense against MTB. Here, we investigate the impact of IFN-γ timing on macrophage-mediated control of MTB infection.
Read the full summary ↓
We demonstrate that IFN-γ exposure before infection enhances macrophage antibacterial activity, whereas post-infection exposure does not. Further analysis of this phenotype revealed a strong association between c-Myc signaling and macrophage function in MTB control, as identified through unbiased in vitro systems approaches. Given the difficulty of perturbing c-Myc in primary cells, we developed a lentiviral system for c-Myc inhibition and overexpression. We profiled both datasets (IFN-γ timing and c-Myc inhibition) to characterize the resulting transcriptional shifts.
Published in
c-Myc Inhibits Macrophage Antimycobacterial Response in Mycobacterium tuberculosis Infection
Sarti E, Dollé C, Wolfensberger R et al. · The Journal of infectious diseases 2025 · PMID 40884499 · doi:10.1093/infdis/jiaf456
This dataset
Open GSE298739 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 GSE298739_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 PRJNA1271040 and SRA study SRP589291. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40884499) ↗
Study design
12 conditions, mostly in triplicate
not_treated ×3 6h_IFNg_before_infection ×3 6h_IFNg_after_infection ×3 6h_full_IFNg ×3 6h_no_IFNg ×3 24h_IFNg_before_infection ×3 24h_IFNg_after_infection ×3 24h_full_IFNg ×3 +4 more

Supports a case/control comparison: 3 samples read as cases, 3 as controls.

How we read this: 12 replicated groups read from 35 sample titles; they account for 35 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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