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Butyrate and propionate are microbial danger signals that activate the NLRP3-inflammasome in human macrophages in the presence of TLR stimulation

GSE248578 Homo sapiens (human) RNA-seq (gene expression) 18 samples Submitted 2024/08/19 Platform GPL18460
At a glance

RNA-seq (gene expression) · human · 18 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
Homo sapiens (human)
Samples
18 samples: 18 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
Butyrate and propionate are microbial danger signals that activate the NLRP3 inflammasome in human macrophages upon TLR stimulationCell reports · 2024
Summary (written by the submitters)
Short chain fatty acids (SCFAs) are immunomodulatory compounds produced by the microbiome through fermentation of dietary fibre. Although they are generally considered beneficial for gut health, patients suffering from inflammatory bowel disease (IBD) have shown poor tolerance to fibre-rich diets, suggesting that SCFAs may have contrary effects under inflammatory conditions.
Read the full summary ↓
To investigate this, we examined the effect of SCFAs on human macrophages in the presence of toll-like receptor agonists. In contrast to their anti-inflammatory effects under steady state conditions, we observed that the SCFAs butyrate and propionate triggered the activation of the NLRP3 inflammasome when added in conjunction with TLR agonists. Mechanistically, butyrate and propionate activated NLRP3 by inhibiting HDACs 1-3 and 10, leading to an uneven distribution of histone hyperacetylation that resulted in alterations in the transcriptome. Specifically, there was a lack of hyperacetylation at the loci of the CFLAR and IL10 genes, two important inhibitors of NLRP3 inflammasome activation. The concurrent loss of transcription and protein expression of cFLIP and IL-10 enabled caspase-8-dependent NLRP3-inflammasome activation. SCFA-driven NLRP3 activation did not require potassium efflux and did not result in cell death but rather triggered hyperactivation and IL-1b release. Our findings demonstrate that butyrate and propionate are bacterially-derived, viability-dependent danger signals (vita-PAMPs) that regulate NLRP3 inflammasome activation through epigenetic modulation of the inflammatory response.
Published in
Butyrate and propionate are microbial danger signals that activate the NLRP3 inflammasome in human macrophages upon TLR stimulation
Wang W, Dernst A, Martin B et al. · Cell reports 2024 · PMID 39277863 · doi:10.1016/j.celrep.2024.114736
This dataset
Open GSE248578 in finder → Find more human 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 GSE248578_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 PRJNA1044803 and SRA study SRP474050. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39277863) ↗
Study design
18 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 18 sample titles: 18 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
Datasets on a similar topic

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