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Spatial hepatocyte plasticity of gluconeogenic gene expression and gluconeogenic activity during the metabolic transitions between fed, fasted and starvation states [RNA-Seq]

GSE263415 Mus musculus (mouse) Single-cell RNA-seq 18 samples Submitted 2025/01/23 Platform GPL24247
At a glance

Single-cell RNA-seq · mouse · 18 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
Organism
Mus musculus (mouse)
Samples
18 samples: 6 conditions, mostly in triplicateGroups 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
Spatial hepatocyte plasticity of gluconeogenesis during the metabolic transitions between fed, fasted and starvation statesNature metabolism · 2025
Summary (written by the submitters)
Single cell analyses of hepatocytes across the liver lobule demonstrated that gluconeogenic gene expression (Pck1 and G6pc) is relatively low in the fed state and gradually increase first in the periportal hepatocytes during the initial fasting period. As the time of fasting progresses, pericentral hepatocyte gluconeogenic gene expression increases and following entry into the starvation state the pericentral hepatocytes are not significantly different than the periportal hepatocytes.
Read the full summary ↓
Similarly, pyruvate-dependent gluconeogenic activity is approximately 10-fold higher in the periportal hepatocytes during the initial fasting states but with only 1.5-fold different between the pericentral and periportal hepatocytes in the starvation state. In parallel, starvation induced a reduction of canonical beta-catenin signaling and redistribution of pericentral and periportal glutamine synthetase and glutaminase resulting in an enhanced pericentral glutamine-dependent gluconeogenesis. These data demonstrate that hepatocyte gluconeogenic gene expression and gluconeogenic activity are highly spatially and temporally plastic across the liver lobule and underscore the critical importance of using well-defined feeding and fasting times to define the basis of hepatic insulin resistance and glucose production.
Published in
Spatial hepatocyte plasticity of gluconeogenesis during the metabolic transitions between fed, fasted and starvation states
Okada J, Landgraf A, Xiaoli AM et al. · Nature metabolism 2025 · PMID 40281362 · doi:10.1038/s42255-025-01269-y
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 GSE263415_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA1097505 and SRA study SRP500270. Searching any of these in the dataset finder brings you back here.

Study design
6 conditions, mostly in triplicate
total RNA, Male Fed4h WT Digitonin PC, ×3 total RNA, Male Fed4h WT Digitonin PP, ×3 total RNA, Male Fast8h WT Digitonin PC, ×3 total RNA, Male Fast8h WT Digitonin PP, ×3 total RNA, Male Fast24h WT Digitonin PC, ×3 total RNA, Male Fast24h WT Digitonin PP, ×3

Supports a between-group comparison across 18 samples.

How we read this: 6 replicated groups read from 18 sample titles; they account for 18 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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