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Early and Delayed STAT1-Dependent Responses Drive Local Trained Immunity of Macrophages in the Spleen [bulk_RNA_seq_MS4A3]

GSE252009 Mus musculus (mouse) Single-cell RNA-seq 53 samples Submitted 2025/01/06 Platform GPL24247
At a glance

Single-cell RNA-seq · mouse · 53 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
Organism
Mus musculus (mouse)
Samples
53 samples: 53 samples, each with a distinct title — no replicated groupsGroups 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
Early and delayed STAT1-dependent responses drive local trained immunity of macrophages in the spleeneLife · 2025
Summary (written by the submitters)
Trained immunity (TI) is the process wherein innate immune cells gain functional memory upon exposure to specific ligands or pathogens, leading to augmented inflammatory responses and pathogen clearance upon secondary exposure. While the differentiation of hematopoietic stem cells (HSCs) and reprogramming of bone marrow progenitors are well-established mechanisms underpinning durable TI protection, the characteristics of effector differentiated cells within the tissue remains underexplored.
Read the full summary ↓
In this study, we delve into the nature of TI in splenic myeloid cells, both recruited and local, responsible for tissue mediated protection. Our findings emphasize the centrality of the JAK-STAT1 pathway, activated by the presence of BCG in peripheral immune tissues, in driving TI. Utilizing single cell RNA-sequencing and flow cytometry, we discerned STAT1-regulated genes in TI-associated resident and recruited splenic myeloid populations. The temporal dynamics of TI were further elucidated, revealed both early and late classical and non-classical monocyte subsets with time-dependent, STAT1-specific signatures. Tissue-resident red pulp macrophages (RPM), initially depleted by BCG exposure, are restored from both a pool of tissue-trained, self-renewing macrophages and from bone marrow-derived progenitors, fostering long lasting local defense. Lastly, upon transient application of specific JAK-STAT inhibitors acting upstream of STAT1 activation, we were able to pinpoint a pivotal temporal window soon after BCG vaccination that anticipates the onset of training; the interference of which obstructs the TI phenotype. As a whole, our study unravels the diverse manifestations of TI as it emerges in mature immune cells, demonstrating its role within the functional tissue milieu of the spleen.
Published in
Early and delayed STAT1-dependent responses drive local trained immunity of macrophages in the spleen
Solomon A, Bossel Ben-Moshe N, Hoffman D et al. · eLife 2025 · PMID 39819562 · doi:10.7554/eLife.100922
This dataset
Open GSE252009 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 GSE252009_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA1057100 and SRA study SRP480130. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39819562) ↗
Study design
53 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 53 sample titles: 53 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

+ 13 more — browse all 53 samples with per-sample file links →

Datasets on a similar topic

Search all mouse RNA-seq datasets in GEO →

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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.