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Pre-existing allergic inflammation alters both innate and adaptive immune responses in mice co-infected with influenza virus

GSE293097 Mus musculus (mouse) RNA-seq (gene expression) 36 samples Submitted 2025/04/30 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 36 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
36 samples: 9 × Lung Saline vs 9 × Lung Influenza vs 9 × Lung HDM vs 9 × Lung HDM InfluenzaGroups 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)
Introduction: Asthma, a chronic airway disease, is marked by allergic inflammation, hyperresponsiveness, and tissue remodeling. Influenza infections in asthma patients can cause severe exacerbations, though the underlying mechanisms remain unclear. This study investigated how pre-existing allergic inflammation affects immune responses to influenza infection in mice exposed to house dust mite (HDM).
Read the full summary ↓
Methods: Mice were repeatedly exposed to HDM, followed by infection with influenza A virus, and were sacrificed three days post-infection. Plasma was analyzed for HDM-specific immunoglobulins, while lung tissue was used for immune cell flow cytometry and RNA sequencing analysis. Results: HDM exposure induced allergic inflammation, evidenced by more HDM-specific IgE, IgG1, IgG2, eosinophils, neutrophils, Th1, and Th17 cells compared to controls. Upon influenza infection, the effects of HDM and influenza co-infection interacted, showing fewer Th1 cells and regulatory T cells and more Th2 cells compared to mice exposed to influenza virus alone. Interestingly, RNA-seq analysis revealed less upregulation of Th1-related genes and antiviral pathways in co-exposed mice, suggesting impaired Th1 immunity and antiviral responses. Conclusion: Pre-existing allergic inflammation significantly altered immune responses in mice coinfected with influenza, revealing underdeveloped antiviral responses as early as three days post-infection. These findings may explain the increased susceptibility of patients with asthma to severe viral diseases.
This dataset
Open GSE293097 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 GSE293097_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 PRJNA1242789 and SRA study SRP573590. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
9 × Lung Saline vs 9 × Lung Influenza vs 9 × Lung HDM vs 9 × Lung HDM Influenza

Supports a between-group comparison across 36 samples.

How we read this: 4 replicated groups read from 36 sample titles; they account for 36 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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