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Acetyl-CoA Carboxylase-1 Inhibition Increases Regulatory T-Cell Metabolism, Mitochondrial Fusion and Graft-vs-Host Disease Treatment Efficacy [L2_cGvHD]

GSE296708 Homo sapiens (human) RNA-seq (gene expression) 35 samples Submitted 2025/07/15 Platform GPL34284
At a glance

RNA-seq (gene expression) · human · 35 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
35 samples: 25 distinct titles, 2 of them repeatedGroups 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
Acetyl-CoA carboxylase 1 inhibition increases Treg metabolism and graft-versus-host disease treatment efficacy via mitochondrial fusionThe Journal of clinical investigation · 2025
Summary (written by the submitters)
Regulatory T-cells (Treg) are critical for maintaining immune homeostasis, and their adoptive transfer can treat murine inflammatory disorders. In patients, Treg therapies have been variably efficacious. Therefore, new strategies to enhance Treg therapeutic efficacy are needed. Treg predominantly depend upon oxidative phosphorylation (OXPHOS) for energy and suppressive function.
Read the full summary ↓
Fatty acid oxidation (FAO) contributes to Treg OXPHOS and can be important for Treg “effector” differentiation, but FAO activity is inhibited by coordinated activity of isoenzymes acetyl-CoA Carboxylase-1 and -2 (ACC1/2). Here, we show that small molecule inhibition or Treg-specific genetic deletion of ACC1 significantly increases Treg suppressive function in vitro and in mice with established chronic GVHD. ACC1 inhibition skewed Treg towards an “effector” phenotype and enhanced FAO-mediated OXPHOS, mitochondrial function, and mitochondrial fusion. Inhibiting mitochondrial fusion diminished the effect of ACC1 inhibition. Reciprocally, promoting mitochondrial fusion, even in the absence of ACC1 modulation, resulted in a Treg functional and metabolic phenotype similar to ACC1 inhibition, indicating a key role for mitochondrial fusion in Treg suppressive potency. Ex vivo expanded, ACC1 inhibitor treated human Treg similarly augmented suppressor function as observed with murine Treg. Together, these data suggest that ACC1 manipulation may be exploited to modulate Treg function in patients.
Published in
Acetyl-CoA carboxylase 1 inhibition increases Treg metabolism and graft-versus-host disease treatment efficacy via mitochondrial fusion
McDonald-Hyman C, Aguilar EG, Compeer EB et al. · The Journal of clinical investigation 2025 · PMID 41026528 · doi:10.1172/JCI182480
This dataset
Open GSE296708 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 GSE296708_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 PRJNA1260799 and SRA study SRP584104. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41026528) ↗
Study design
25 distinct titles, 2 of them repeated
20190418_treg ×10 20190809_tcon ×2

How we read this: Read from 35 sample titles: 25 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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