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B cell deficiency induces cytotoxic memory CD8+ T cells during influenza-associated bacterial pneumonia

GSE288913 Mus musculus (mouse) RNA-seq (gene expression) 14 samples Submitted 2025/05/27 Platform GPL34328
At a glance

RNA-seq (gene expression) · mouse · 14 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
14 samples: 4 × WT, FF, biol vs 4 × WT, FFS, biol vs 3 × MuMT, FF, biol vs 3 × MuMT, FFS, biolGroups 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
B cell deficiency induces cytotoxic memory CD8+ T cells during influenza-associated bacterial pneumoniaThe Journal of clinical investigation · 2025
Summary (written by the submitters)
This study explores the role B cells play in protection against super-infection with previous heterotypic influenza memory. B cell deficiency results in increased inflammatory lung environment and lung tissue injury during super-infection. Loss of B cells increased populations of memory CD8+ T cells in the lung and these CD8+ T cells were transcriptionally and functionally distinct from WT mice.
Read the full summary ↓
RNA-seq: WT (C57BL6) and uMT mice were challenged with influenza (X31) at D0, challenged with influenza (PR8) at day 54, challenged with MRSA USA300 or PBS vehicle at day 60 followed by lung tissue harvest at day 61. RNA was extracted from CD8 T cells sorted from harvested lungs.
Published in
B cell deficiency induces cytotoxic memory CD8+ T cells during influenza-associated bacterial pneumonia
Miller LM, Duray AM, Cipolla EM et al. · The Journal of clinical investigation 2025 · PMID 40493422 · doi:10.1172/JCI188342
This dataset
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.

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 GSE288913_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA1220005 and SRA study SRP561969. Searching any of these in the dataset finder brings you back here.

Study design
4 × WT, FF, biol vs 4 × WT, FFS, biol vs 3 × MuMT, FF, biol vs 3 × MuMT, FFS, biol

Supports a between-group comparison across 14 samples.

How we read this: 4 replicated groups read from 14 sample titles; they account for 14 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
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