← BioTransfer GEO Dataset Finder
GEO series

Two microbiome metabolites compete for tRNA modification and mammalian cell proliferation

GSE233846 Mus musculus (mouse) RNA-seq (gene expression) 72 samples Submitted 2025/06/02 Platform GPL24676Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 72 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
72 samples: 68 distinct titles, 4 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
Two microbiome metabolites compete for tRNA modification to impact mammalian cell proliferation and translation quality controlNature cell biology · 2025
Summary (written by the submitters)
Microbiome interacts with the eukaryotic host through many metabolites to affect cell physiology. A direct molecular pathway of microbial-host interaction is the incorporation of the microbial metabolite queuine at the wobble anticodon nucleotide of host tRNAs by a host enzyme that regulates host cell translation. Microbes also produce the intermediary metabolite pre-queuosine1 (preQ1) in the queuine pathway, and how preQ1 affects the host cell biology has not been explored.
Read the full summary ↓
Here we show that preQ1 strongly represses human and mouse cell proliferation, but this effect is suppressed or reversible with queuine and depends on the same host enzyme that installs queuosine tRNA modification. PreQ1 and queuine are present in plasma and mouse tissues and incorporated into tRNA in cells and in mice, and preQ1 reduces mouse xenograft tumor growth. Mechanistically, preQ1 reduces cognate tRNA levels specifically and translation of house-keeping genes in a highly codon dependent manner. Genomic-wide CRISPR screen and validation identify pathways in sterol biosynthesis regulation, lipid metabolism, and Golgi-ER transport that mitigate the preQ1 proliferation effects through alleviation of cognate tRNA levels. Our results show an inter-dependent relationship of two microbial metabolites from the same biosynthesis pathway that compete and regulate host cell proliferation through multiple pathways.
Published in
Two microbiome metabolites compete for tRNA modification to impact mammalian cell proliferation and translation quality control
Zhang W, Lahry K, Cipurko D et al. · Nature cell biology 2025 · PMID 40957911 · doi:10.1038/s41556-025-01750-6
This dataset
Open GSE233846 in finder → Find more 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 GSE233846_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 PRJNA978085 and SRA study SRP440554. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40957911) ↗
Study design
68 distinct titles, 4 of them repeated
mRNA_0Q_input ×2 mRNA_preQ1_input ×2 mRNA_0Q_polysome ×2 mRNA_preQ1_polysome ×2

How we read this: Read from 72 sample titles: 68 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

+ 32 more — browse all 72 samples with per-sample file links →

Datasets on a similar topic

Search all RNA-seq datasets in GEO →

Share this dataset

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.