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The Gut-larynx Axis and its Contribution to Laryngeal Immunity

GSE290718 Mus musculus (mouse) RNA-seq (gene expression) 11 samples Submitted 2025/03/04 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 11 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
11 samples: 11 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.
Paper
Gut-larynx axis and its contribution to laryngeal immunitymSystems · 2025
Summary (written by the submitters)
The larynx is essential for swallowing, breathing, coughing, and voice production, supported by its unique microbial and immunological environment. Our previous research highlighted the role of resident laryngeal microbiota in shaping local immune responses. With growing interest in the gut-lung axis—the bidirectional communication between gut and respiratory immunity—the potential influence of gut microbiota on laryngeal immunity warrants exploration.
Read the full summary ↓
We hypothesized that a gut-larynx axis may exist, where both resident laryngeal and gut microbiota contribute to immune modulation in the larynx. To investigate this, we treated conventionally raised, wild-type C57BL/6J mice with an oral antibiotic regimen known to disrupt gut microbiota, comparing them to untreated controls. Following treatment, the gut microbiota was significantly disrupted, while the laryngeal microbiota remained largely unchanged. However, antibiotic-treated mice exhibited marked changes in epithelial and immune cell proportions, as well as fibroblasts. Differential gene expression across cell types highlighted pathways related to epithelial barrier integrity, immune signaling, and bacterial response. Additionally, gut dysbiosis affected gene regulatory networks, with the activity of regulons Etv4(+), Irf3(+), Hltf(+), Mga(+), and Nfil3(+) showing significant changes. Notably, cell-cell communication was also altered, especially in immune-epithelial interactions, with integrin-mediated signaling emerging as a key ligand-receptor pathway in these intercellular communications. These findings suggest that gut and laryngeal microbiota may work synergistically to modulate immune responses in the larynx, underscoring the importance of considering gut-larynx interactions in studies of respiratory immunity.
Published in
Gut-larynx axis and its contribution to laryngeal immunity
An R, Xie E, Binns J et al. · mSystems 2025 · PMID 41055335 · doi:10.1128/msystems.01044-25
This dataset
Open GSE290718 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 GSE290718_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 PRJNA1229629 and SRA study SRP566885. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41055335) ↗
Study design
11 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 11 sample titles: 11 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
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