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Itaconate mediates a metabolic crosstalk between osteoclasts and osteoblasts

GSE236452 Homo sapiens (human) RNA-seq (gene expression) 27 samples Submitted 2024/07/24 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 27 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
27 samples: 27 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.
Summary (written by the submitters)
Bone remodeling is a highly dynamic process dependent on the precise coordination of osteoblasts and hematopoietic-cell derived osteoclasts. Emerging evidence indicates that cellular differentiation is associated with a metabolic rewiring in conjunction with the acquisition of specific effector functions. Changes in core metabolic pathways during osteoclastogenesis, however, are largely unexplored and it is unknown whether and how these processes are involved in bone homeostasis.
Read the full summary ↓
We show that during differentiation preosteoclasts rearrange their tricarboxylic acid (TCA) cycle, a process crucially depending on both glucose and glutamine. This rearrangement is characterized by induction of immunoresponsive gene 1 (Irg1) and production of itaconate, which accumulates intra- and extracellularly. While the IRG1-itaconate axis is dispensable for osteoclast generationin vitroandin vivo, we demonstrate that itaconate stimulates osteoblasts by accelerating osteogenic differentiation, reducing proliferation and shifting ATP production from mitochondrial respiration to glycolysis. Additionally, supplementation of itaconate increases bone formation by boosting osteoblast activity in mice. Conversely,Irg1deficient mice exhibit decreased bone mass and have reduced osteoproliferative lesions in experimental arthritis. In summary, we identify itaconate, generated as a result of the metabolic rewiring during osteoclast differentiation, as a previously unrecognized regulator of the crosstalk between osteoclasts and osteoblasts
This dataset
Open GSE236452 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 GSE236452_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 PRJNA990825 and SRA study SRP447198. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
27 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 27 sample titles: 27 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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Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.