GEO series

Treg-microglia partnership in the injured spinal cord preserves Treg cells function and regulates microglial cholesterol metabolism

GSE243607 Mus musculus (mouse) Single-cell RNA-seq 12 samples Submitted 2025/09/29 Platform GPL30215

At a glance

Single-cell RNA-seq · mouse · 12 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: 12 samples: 12 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.

Summary (written by the submitters)

The quantitative variations and specific roles of regulatory T cells (Treg cells) within spinal cord injury (SCI) remain elusive. Utilizing single-cell RNA sequencing, flow cytometry, and immunofluorescence, we discovered that Treg cells began to infiltrate the injured spinal cords in mice approximately three days after SCI. Selective depletion of Treg cells resulted in an expansion of the injury area, reduction in neuronal survival, and a decrease in long-term functional recovery post-SCI.

Read the full summary ↓

Transcriptomic analyses of Treg cells unveiled potent anti-inflammatory functions and the potential to influence neighboring immune cells within the spinal cord after SCI. Adoptive transfer of Treg cells demonstrated measurable improvement in SCI recovery and increased neuronal retention in mice. However, selective depletion of microglia inhibited the neuroprotective effects of Treg cells, indicating that the effect of Treg cells in the spinal cord depends on the presence of microglia. Mechanistically, Treg cells promoted spinal cord functional recovery by upregulating microglial Abcg1 receptor expression, enhancing cholesterol transport, reducing microglial lipid droplet formation, and moderating the M1 phenotype after SCI. In summary, our study elucidates the spatiotemporal distribution of Treg cells after SCI and their unique transcriptomic features, clarifying the impact of Treg cells on microglial cholesterol metabolism and inflammatory phenotype. These findings indicate that Treg cells may serve as a potential target for SCI treatment.

This dataset

Open GSE243607 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 GSE243607_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 PRJNA1019140 and SRA study SRP461898. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

12 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 12 sample titles: 12 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

GSM7791818 Sample1_Treg spleen 1
GSM7791819 Sample2_Treg spleen 2
GSM7791820 Sample3_Treg spleen 3
GSM7791821 Sample4_Treg spinal cord 1
GSM7791822 Sample5_Treg spinal cord 2
GSM7791823 Sample6_Treg spinal cord 3
GSM7791824 Sample7_Microglia control 1
GSM7791825 Sample8_Microglia control 2
GSM7791826 Sample9_Microglia control 3
GSM7791827 Sample10_Microglia Treg co-cultured 1
GSM7791828 Sample11_Microglia Treg co-cultured 2
GSM7791829 Sample12_Microglia Treg co-cultured 3

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