GEO series

Type I interferon signaling and peroxisomal dysfunction contribute to enhanced inflammatory cytokine production in Irgm1-deficient macrophages

GSE276820 Mus musculus (mouse) RNA-seq (gene expression) 28 samples Submitted 2024/12/26 Platform GPL24247Platform GPL34290

At a glance

RNA-seq (gene expression) · mouse · 28 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: 28 samples: 7 conditions, mostly with about 4 replicates eachGroups 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: Type I interferon signaling and peroxisomal dysfunction contribute to enhanced inflammatory cytokine production in IRGM1-deficient macrophagesThe Journal of biological chemistry · 2024

Summary (written by the submitters)

The human IRGM gene has been linked to inflammatory diseases including sepsis and Crohn’s disease. Decreased expression of human IRGM, or of the mouse orthologues Irgm1 and Irgm2, leads to increased production of a number of inflammatory chemokines and cytokines in vivo and/or in cultured macrophages. Prior work has indicated that increased cytokine production is instigated by metabolic alterations and by changes in mitochondrial homeostasis; however, a comprehensive mechanism has not been elucidated.

Read the full summary ↓

In the studies presented here, RNA deep sequencing and quantitative PCR were used to show that increases in cytokine production, as well as most changes in the transcriptional profile of Irgm1-/- bone marrow-derived macrophages (BMM), are dependent on increased type I IFN production seen in those cells. Metabolic alterations that drive increased cytokines in Irgm1-/- BMM - specifically increases in glycolysis and increased accumulation of acyl-carnitines - were unaffected by quenching type I IFN signaling. Dysregulation of peroxisomal homeostasis was identified as a novel upstream pathway that governs type I IFN production and inflammatory cytokine production. Collectively, these results enhance our understanding of the complex biochemical changes that are triggered by lack of Irgm1 and contribute to inflammatory disease seen with Irgm1-deficiency.

Published in

Type I interferon signaling and peroxisomal dysfunction contribute to enhanced inflammatory cytokine production in IRGM1-deficient macrophages

Fee BE, Fee LR, Menechella M et al. · The Journal of biological chemistry 2024 · PMID 39395806 · doi:10.1016/j.jbc.2024.107883

This dataset

Open GSE276820 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 GSE276820_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 PRJNA1159166 and SRA study SRP531833. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39395806) ↗

Study design

7 conditions, mostly with about 4 replicates each

BMM, WT ×4 BMM, Irgm1-KO ×4 BMM, Irgm_IFNAR-KO ×4 BMM, WT_control ×4 BMM, WT_fenofibrate ×4 BMM, Irgm1KO_control ×4 BMM, Irgm1KO_fenofibrate ×4

Supports a between-group comparison across 28 samples.

How we read this: 7 replicated groups read from 28 sample titles; they account for 28 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

GSM8506237 BMM, WT_1 BMM, WT
GSM8506238 BMM, WT_2 BMM, WT
GSM8506239 BMM, WT_3 BMM, WT
GSM8506240 BMM, WT_4 BMM, WT
GSM8506241 BMM, Irgm1-KO_1 BMM, Irgm1-KO
GSM8506242 BMM, Irgm1-KO_2 BMM, Irgm1-KO
GSM8506243 BMM, Irgm1-KO_3 BMM, Irgm1-KO
GSM8506244 BMM, Irgm1-KO_4 BMM, Irgm1-KO
GSM8506245 BMM, Irgm_IFNAR-KO_1 BMM, Irgm_IFNAR-KO
GSM8506246 BMM, Irgm_IFNAR-KO_2 BMM, Irgm_IFNAR-KO
GSM8506247 BMM, Irgm_IFNAR-KO_3 BMM, Irgm_IFNAR-KO
GSM8506248 BMM, Irgm_IFNAR-KO_4 BMM, Irgm_IFNAR-KO
GSM8506249 BMM, WT_control_1 BMM, WT_control
GSM8506250 BMM, WT_control_2 BMM, WT_control
GSM8506251 BMM, WT_control_3 BMM, WT_control
GSM8506252 BMM, WT_control_4 BMM, WT_control
GSM8506253 BMM, WT_fenofibrate_1 BMM, WT_fenofibrate
GSM8506254 BMM, WT_fenofibrate_2 BMM, WT_fenofibrate
GSM8506255 BMM, WT_fenofibrate_3 BMM, WT_fenofibrate
GSM8506256 BMM, WT_fenofibrate_4 BMM, WT_fenofibrate
GSM8506257 BMM, Irgm1KO_control_1 BMM, Irgm1KO_control
GSM8506258 BMM, Irgm1KO_control_2 BMM, Irgm1KO_control
GSM8506259 BMM, Irgm1KO_control_3 BMM, Irgm1KO_control
GSM8506260 BMM, Irgm1KO_control_4 BMM, Irgm1KO_control
GSM8506261 BMM, Irgm1KO_fenofibrate_1 BMM, Irgm1KO_fenofibrate
GSM8506262 BMM, Irgm1KO_fenofibrate_2 BMM, Irgm1KO_fenofibrate
GSM8506263 BMM, Irgm1KO_fenofibrate_3 BMM, Irgm1KO_fenofibrate
GSM8506264 BMM, Irgm1KO_fenofibrate_4 BMM, Irgm1KO_fenofibrate

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