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Rapid modulation of gut microbiota composition by hypothalamic circuits in mice.

GSE266230 Mus musculus (mouse) RNA-seq (gene expression) 39 samples Submitted 2025/02/24 Platform GPL30172
At a glance

RNA-seq (gene expression) · mouse · 39 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
39 samples: 14 × Saline-water, vs 13 × Leptin-water, vs 6 × Saline-antibiotic, vs 6 × Leptin-antibiotic,Groups 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
Rapid modulation of gut microbiota composition by hypothalamic circuits in miceNature metabolism · 2025
Summary (written by the submitters)
In recent years, the gut microbiota and derived metabolites have emerged as relevant players in modulating several brain functions, including energy balance control. This form of distant communication mirrors that of metabolic hormones (e.g., leptin, ghrelin), that convey information about the organism's energy status by exerting effects on diverse brain regions including the master homeostatic centre the hypothalamus.
Read the full summary ↓
However, whether the hypothalamus is also able to influence gut microbiota composition remains enigmatic. Here, we present a proof-of-concept study designed to unravel this challenging question. To this aim, we employed chemogenetics (to selectively activate or inhibit the activity of hypothalamic POMC or AgRP neurons) or administered leptin or ghrelin centrally to mice. Subsequently, we conducted microbiota composition analysis throughout the gut using 16S rRNA gene sequencing. Our results showed that these brain interventions significantly changed the gut microbiota in an anatomical and short-term (2-4h) fashion. Transcriptomic analysis indicated that these changes were associated with the reconfiguration of neuronal and synaptic pathways in the duodenum concomitant with increased sympathetic tone. Interestingly, diet-induced obesity attenuated brain-mediated changes induced by leptin in gut microbiota communities and sympathetic activation. Our findings reveal a novel and unanticipated brain-to-gut axis that acutely attunes microbiota composition at fast timescales, with potential implications for meal-to-meal adjustments and systemic energy balance control.
Published in
Rapid modulation of gut microbiota composition by hypothalamic circuits in mice
Toledo M, Martínez-Martínez S, Van Hul M et al. · Nature metabolism 2025 · PMID 40263603 · doi:10.1038/s42255-025-01280-3
This dataset
Open GSE266230 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 GSE266230_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 PRJNA1106420 and SRA study SRP504903. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40263603) ↗
Study design
14 × Saline-water, vs 13 × Leptin-water, vs 6 × Saline-antibiotic, vs 6 × Leptin-antibiotic,

Supports a between-group comparison across 39 samples.

How we read this: 4 replicated groups read from 39 sample titles; they account for 39 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
Datasets on a similar topic

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