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Regulation of IkB kinase family crosstalk by an N4BP1-caspase-8 axis [RNA-seq NGS3799]

GSE218956 Mus musculus (mouse) RNA-seq (gene expression) 36 samples Submitted 2024/04/01 Platform GPL21103
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: 36 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
N4BP1 coordinates ubiquitin-dependent crosstalk within the IκB kinase family to limit Toll-like receptor signaling and inflammationImmunity · 2024
Summary (written by the submitters)
The cell death protease caspase-8 plays an essential role in controlling inflammation, as severe immunodeficiency results from its loss. We previously found that caspase-8 promotes inflammatory responses by cleaving NEDD4-binding protein 1 (N4BP1), a suppressor of cytokine production, but the underlying mechanisms remained unclear.
Read the full summary ↓
Here we find that N4BP1 curtails the duration, rather than initial induction, of proinflammatory signaling through a mechanism involving noncanonical IKK (ncIKK)-mediated inhibition of the canonical IkB kinase (IKK) complex, a crosstalk event among the IKK family facilitated by N4BP1. Accordingly, co-deletion of the ncIKKs or their adaptor protein TANK largely phenocopied deletion of N4BP1, augmenting cytokine responses by macrophages upon engagement of TRIF-independent toll-like receptors (TLR) 1/2, TLR7, or TLR9. Like N4BP1, TANK was largely prevented from inhibiting the TRIF-dependent TLR4 response due to caspase-8. Biochemically, N4BP1 binds both the canonical and noncanonical IKK complexes, in a manner promoted by linear and/or K63-linked polyubiquitin chain binding by N4BP1 and independent of its RNAse activity. Consistent with this, a knock-in mutant of N4BP1 with diminished ubiquitin chain-binding capacity led to increased proinflammatory cytokine responses. These findings thereby unveil a mechanism of late-phase inflammatory gene control, whereby N4BP1 prevents persistent IKK activity through ncIKK-mediated inhibition. This molecular crosstalk among caspase-8, N4BP1, and the IKKs and ncIKKs may have implications for our understanding of genetic immune diseases caused by mutations in caspase-8 or TBK1 and suggest a novel ‘guarding’ mechanism against pathogens that attempt to subvert the ncIKKs.
Published in
N4BP1 coordinates ubiquitin-dependent crosstalk within the IκB kinase family to limit Toll-like receptor signaling and inflammation
Gitlin AD, Maltzman A, Kanno Y et al. · Immunity 2024 · PMID 38697117 · doi:10.1016/j.immuni.2024.04.004
This dataset
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.

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 GSE218956_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA906451 and SRA study SRP410385. Searching any of these in the dataset finder brings you back here.

Study design
36 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 36 sample titles: 36 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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