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Neutral sphingomyelinase 2 inhibition alters inflammatory gene expression signatures in the brain of mice infected with West Nile virus

GSE256333 Mus musculus (mouse) RNA-seq (gene expression) 27 samples Submitted 2025/07/16 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 27 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
27 samples: 12 × Vehicle, brain, 7 dpi, vs 11 × DPTIP, brain, 7 dpi, vs 4 × Mock, brain, 7 dpi,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
Neutral sphingomyelinase 2 inhibition alters inflammatory gene expression signatures in the brain of mice infected with West Nile virusInternational immunopharmacology · 2025
Summary (written by the submitters)
To investigate the in vivo effects of DPTIP during WNV infection in a mouse model, we compared infected mice with WNV NY99 treated with DPTIP or vehicle and uninfected (mock) mice. DPTIP is a pro-dug that targets mouse nSMASE. We then performed gene expression profiling analysis using data obtained from RNA-seq from infected-vehicle mice, uninfected mice and infected DPTIP-treated mice
Published in
Neutral sphingomyelinase 2 inhibition alters inflammatory gene expression signatures in the brain of mice infected with West Nile virus
Mingo-Casas P, Álvarez-Fernández H, Blázquez AB et al. · International immunopharmacology 2025 · PMID 40652589 · doi:10.1016/j.intimp.2025.115203
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 GSE256333_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 PRJNA1079206 and SRA study SRP490966. Searching any of these in the dataset finder brings you back here.

Study design
12 × Vehicle, brain, 7 dpi, vs 11 × DPTIP, brain, 7 dpi, vs 4 × Mock, brain, 7 dpi,

Supports a between-group comparison across 27 samples.

How we read this: 3 replicated groups read from 27 sample titles; they account for 27 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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