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Characterizing the metabolomes of microglia, astrocytes, and neurons in the brain across states of health, aging, and disease

GSE316928 Mus musculus (mouse) RNA-seq (gene expression) 35 samples Submitted 2026/02/04 Platform GPL24247Platform GPL30215
At a glance

RNA-seq (gene expression) · mouse · 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
Mus musculus (mouse)
Samples
35 samples: 7 conditions, mostly with about 4 replicates eachGroups 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.
Summary (written by the submitters)
Neurons and glia are distinct in their morphology, development, and function. They have unique transcriptomes and proteomes, but little is known about their metabolomes. The challenge of brain cell metabolic profiling is to obtain a large number of pure cells for reliable analysis. Here, we purify microglia, astrocytes, and neurons from the genetically labeled-brain.
Read the full summary ↓
We identified >70 metabolites in them with targeted metabolomics and 9,854 metabolite features with untargeted metabolomics. We systematically characterized cell type–enriched metabolites and metabolic pathways. The enrichment of glutathione (GSH) metabolism in microglia was further validated in vivo. A significant decrease in GSH levels and GSH metabolism observed in microglia in aging and Alzheimer's disease (AD) models. Disrupting GSH metabolism in microglia results in aberrant morphogenesis, upregulation of mitophagy-related genes, and the deposition of β-Amyloid. Our results provide a valuable resource for metabolic studies related to aging, AD and other neurological diseases.
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 GSE316928_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 PRJNA1405558 and SRA study SRP664706. Searching any of these in the dataset finder brings you back here.

Study design
7 conditions, mostly with about 4 replicates each
mouse brain cortex, Neuron_40 ×11 mouse brain cortex, Astrocyte_40 ×5 mouse brain cortex, Microglia_40 ×4 mouse brain cortex, Microglia_1y ×4 mouse brain cortex, mg_gpx1 ×4 mouse brain cortex,mg_fad ×3 mouse brain cortex,Ast_12month_AD60 ×2 mouse brain cortex, Ast_12month_AD ×1 +1 more

Supports a between-group comparison across 33 samples.

How we read this: 7 replicated groups read from 35 sample titles; they account for 33 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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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.