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Antibiotic use during influenza infection augments lung eosinophils that impair lung immunity against secondary bacterial pneumonia

GSE259429 Mus musculus (mouse) RNA-seq (gene expression) 12 samples Submitted 2024/08/21 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 12 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
12 samples
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)
A leading cause of morbidity and mortality during influenza infection is the development of a secondary bacterial pneumonia, which is appropriately treated with antibiotics. In the absence of a bacterial superinfection, prescribing antibiotics is not indicated but has nevertheless become a common clinical practice for those presenting with a respiratory viral illness.
Read the full summary ↓
We found that antibiotic use during an antecedent influenza infection impaired the lung innate immunologic defenses toward a secondary challenge with methicillin-resistantStaphylococcus aureus(MRSA). The antibiotics perturbed the gut microbiome causing a fungal dysbiosis that drives an increase in lung eosinophils. We also demonstrate eosinophils, through the release of major basic protein, impair macrophage ability to clear MRSA. Moreover, we provide clinical evidence that eosinophils positively correlate with antibiotic use and worsened outcomes in patients hospitalized for viral infections. Altogether, our work establishes a counterproductive effect of antibiotic treatment during influenza infection that have negative immunologic consequences in the lungs thereby increasing the risk of developing a secondary bacterial infection.
This dataset
Open GSE259429 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 GSE259429_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 PRJNA1081465 and SRA study SRP492154. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Samples in this study

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+ 12 more — browse all 12 samples with per-sample file links →

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