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Inflammasome Hyperactivation Disrupts Construction of the Gas Exchange Surface through the NLRP3-IL-18-TNFa Axis [RNA-seq]

GSE342046 Mus musculus (mouse) Single-cell RNA-seq 17 samples Submitted 2026/08/04 Platform GPL24247
At a glance

Single-cell RNA-seq · mouse · 17 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
Organism
Mus musculus (mouse)
Samples
17 samples: 5 conditions, mostly in triplicateGroups 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)
Inflammation is a prominent feature of tissue injury, and a driver of chronic disease. However, the precise molecular mechanisms underlying the impact of inflammation remains unclear in many injury settings including in alveolar development to build the gas exchange surface in lung. Here we show that in mice, overexpression of patient-derived activated variants of Nlrp3 (Nlrp3act), a central sensor within the inflammasome, resulted in severe simplification of alveoli.
Read the full summary ↓
Such histology is accompanied by a striking decrease of cell proliferation and marker expression of secondary crest myofibroblasts (SCMFs) whose contractility is essential for septa formation. Such a drastic effect on lung structure was only observed when the variants were overexpressed in the first two weeks after birth, but not later. While both downstream proinflammatory cytokines IL-1β and IL-18 are upregulated, inactivation of Il18, but not Il1b in the Nlrp3act background reversed simplification. Also unlikely in other tissue settings where Mmp9 is a critical mediator downstream of the inflammasome, inactivation of Mmp9 also did not reverse Nlrp3act phenotypes, suggesting context-dependent mechanisms. scRNAseq followed by validation revealed IL-18-dependent increase of Tnfα in myeloid cells, capable of signaling through its widely-expressed receptors to all structural cells including SCMFs. Addition of recombinant TNFα to mesenchymal cells enriched for SCMFs led to reduced contractile gene expression. Finally, inactivation of Tnfα in the Nlrp3act background led to a robust reversal of simplification. These findings together demonstrate an inflammasome-IL-18-TNFα axis that dictate lung mesenchymal cell states, thereby control the building of the gas exchange surface.
This dataset
Open GSE342046 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 GSE342046_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 PRJNA1505483 and SRA study SRP723045. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
5 conditions, mostly in triplicate
Il18r1 control ×4 LysMcre;Nlrp3A350V;Il181r-/ ×4 Control ×3 LysMcre;Nlrp3A350V ×3 LysMcre;Nlrp3A350V;Il181r+/ ×3

Supports a between-group comparison across 17 samples.

How we read this: 5 replicated groups read from 17 sample titles; they account for 17 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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