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The metabolic signature of inflammatory skin-imprinted eosinophils accounts for the chronicity of Leishmania mexicana infections [Day50]

GSE281802 Mus musculus (mouse) RNA-seq (gene expression) 1 samples Submitted 2026/02/23 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 1 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
1 samples
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)
Eosinophils exert antimicrobial, cytotoxic and immunoregulatory effects, but their function in cutaneous tissue still remains poorly understood. Here, we used a mouse model of chronic cutaneous leishmaniasis caused by the protozoan parasite Leishmania (L.) mexicana to investigate the functional role and transcriptomic signature of eosinophils in the skin.
Read the full summary ↓
In C57BL/6 wild-type mice, L. mexicana induced local and systemic eosinophilia that was dependent on type 2 innate lymphoid cells and interleukin-5. Genetic and pharmacological depletion of eosinophils led to clinical resolution of disease, which was accompanied by a more pronounced Th1 and M1-like macrophage response. Bioinformatic analyses revealed a novel inflammatory and tissue-specific transcriptional trajectory in skin-infiltrating eosinophils. Skin-imprinted eosinophils strongly expressed the high-affinity glucose transporter 3 (Slc2a3), deprived the environment of glucose and directly impeded the function of Th1 cells. Together, our results demonstrate that the chronicity of L. mexicana infection is linked to inflammatory eosinophils and their metabolic signature
This dataset
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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 GSE281802_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 PRJNA1185734 and SRA study SRP545007. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Samples in this study

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