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Elevated FTO alleviates sepsis-induced acute kidney injury by regulating macrophage inflammatory phenotypes [MeRIP-seq]

GSE297679 Mus musculus (mouse) RNA-seq (gene expression) 12 samples Submitted 2025/12/04 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 12 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
12 samples: 6 conditions, mostly in duplicateGroups 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
Elevated FTO alleviates sepsis‑induced acute kidney injury by regulating macrophage inflammatory phenotypesInternational journal of molecular medicine · 2026
Summary (written by the submitters)
Recent studies have linked the dysregulation of N6-methyladenosine (m6A) to sepsis-induced acute kidney injury (SAKI), highlighting the persistent challenge of managing excessive proinflammatory cytokine production and subsequent organ dysfunction. In this study, we analyzed the dataset GSE32707 and GSE69063, fat mass and obesity-associated protein (FTO) was identified as the sole gene exhibiting significant downregulation within the transcriptome of peripheral blood samples from sepsis patients among m6A-related proteins.
Read the full summary ↓
We further demonstrated that septic mice subjected to cecal ligation and puncture (CLP) presented increased m6A modifications and reduced FTO expression in both renal tissues and peritoneal macrophages (PMs). Our findings revealed that increased levels of FTO correlated with reduced mortality and kidney damage during sepsis and that the upregulation of FTO in lipopolysaccharide (LPS)-stimulated macrophages led to decreased production of proinflammatory cytokines. Mechanistically, through multiomic analysis of macrophages, we identified a novel mechanism involving matrix metalloproteinase 9 (MMP-9) as a direct target of FTO, which positively affects its translation efficacy. Furthermore, both in vivo and in vitro data confirmed that reduced MMP-9 levels exerted adverse effects on mitigating inflammatory responses and alleviating renal injury. Overall, our findings underscore the critical role of the FTO/m6A/MMP-9 axis in the regulation of proinflammatory secretion and improve our understanding of the transcriptomic landscape during the progression of SAKI.
Published in
Elevated FTO alleviates sepsis‑induced acute kidney injury by regulating macrophage inflammatory phenotypes
Chen X, Sun Z, Chen J et al. · International journal of molecular medicine 2026 · PMID 41235650 · doi:10.3892/ijmm.2025.5689
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 GSE297679_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 PRJNA1265684 and SRA study SRP586595. Searching any of these in the dataset finder brings you back here.

Study design
6 conditions, mostly in duplicate
RNA-seq, NC without LPS treatment ×2 RNA-seq, NC with LPS treatment ×2 MeRIP-seq input, NC without LPS treatment ×2 MeRIP-seq IP, NC without LPS treatment ×2 MeRIP-seq input, NC with LPS treatment ×2 MeRIP-seq IP, NC with LPS treatment ×2

Supports a between-group comparison across 12 samples.

How we read this: 6 replicated groups read from 12 sample titles; they account for 12 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
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