GEO series

Single cell RNA sequencing of gp33 tetramer-positive CD8 T cells sorted from the SI-LP and spleen of germ-free and SPF mice 16 days after LCMV Docile infection [scRNA-Seq 10x]

GSE329359 Mus musculus (mouse) Single-cell RNA-seq 12 samples Submitted 2026/04/29 Platform GPL24247

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.
Organism: Mus musculus (mouse)
Samples: 12 samples: 3 × SI_GF vs 3 × SI_SPF vs 3 × SP_GF vs 3 × SP_SPFGroups 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)

Prolonged antigen exposure in chronic viral infections reduces the effector capacity of cytotoxic T cells - a phenomenon known as T cell exhaustion. Development of T cell exhaustion is driven by high viral titers, strong TCR stimulation, and high antigen concentrations associated with strong inflammatory signals. A largely unexplored factor has been the influence of the microbiome in these processes.

Read the full summary ↓

Here, we report that T cell exhaustion progresses independently of the presence or absence of a microbiome in chronic lymphocytic choriomeningitis virus (LCMV) infections. Virus-specific CD8 T cells in germ-free mice showed high expression of the inhibitory receptor PD-1 and decreased cytokine production. Moreover, their global gene expression patterns, as determined by single-cell sequencing, were similar to those of cells in specific pathogen-free mice. In line with this, we observed similar pathogen loads with and without a microbiome. Thus, our study demonstrates that the microbiome is dispensable for the induction of T cell exhaustion and for the limited virus control seen in chronic LCMV infections.

This dataset

Open GSE329359 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 GSE329359_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 PRJNA1458708 and SRA study SRP695642. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

3 × SI_GF vs 3 × SI_SPF vs 3 × SP_GF vs 3 × SP_SPF

Supports a between-group comparison across 12 samples.

How we read this: 4 replicated groups read from 12 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

GSM9702472 SI_GF_1 SI_GF
GSM9702473 SI_GF_2 SI_GF
GSM9702474 SI_GF_5 SI_GF
GSM9702475 SI_SPF_1 SI_SPF
GSM9702476 SI_SPF_2 SI_SPF
GSM9702477 SI_SPF_4 SI_SPF
GSM9702478 SP_GF_1 SP_GF
GSM9702479 SP_GF_2 SP_GF
GSM9702480 SP_GF_5 SP_GF
GSM9702481 SP_SPF_1 SP_SPF
GSM9702482 SP_SPF_2 SP_SPF
GSM9702483 SP_SPF_4 SP_SPF

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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.