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Post-resolution macrophage-derived lipids shapes long-term tissue immunity and integrity

GSE264058 Mus musculus (mouse) RNA-seq (gene expression) 40 samples Submitted 2024/04/17 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 40 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
40 samples: 8 conditions, mostly with about 5 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)
Resolving inflammation is thought to return the affected tissue back to homeostasis. However, we show that within days following resolution of Streptococcus pneumonia-triggered lung inflammation there is an influx of antigen specific lymphocytes with a memory and tissue-resident phenotype as well as macrophages bearing an alveolar or interstitial phenotype.
Read the full summary ↓
Transcriptomic analysis revealed that macrophages are enriched with genes that drive T cell chemotaxis and differentiation as well as prostaglandin biosynthesis. Therapeutic depletion of post-resolution macrophages, inhibition of PGE2 synthesis or antagonism of EP4 reduced numbers of lung CD4+/CD44+/CD62L+ and CD4+/CD44+/CD62L-/CD27+ T cells as well as their expression of the a-integrin, CD103. This intervention resulted in a failure of these cells to reappear and reactivate upon secondary challenge up to six weeks following primary infection. Concomitantly, EP4 antagonism caused accumulation of lung macrophages and marked tissue fibrosis. Hence, resolving inflammation triggers a second wave of immune activity controlled, in part, by PGE2, which through EP4, drives local tissue-resident T cell development on the one hand, whilst limiting tissue injury on the other
This dataset
Open GSE264058 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 GSE264058_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 PRJNA1100707 and SRA study SRP501934. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
8 conditions, mostly with about 5 replicates each
NAM ×5 NIMMHCII ×5 14IMDN ×5 14IMMHCII ×5 14AM ×5 14IMLYVE ×5 NIMLYVE ×5 NIMDN ×5

Supports a between-group comparison across 40 samples.

How we read this: 8 replicated groups read from 40 sample titles; they account for 40 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

Search all mouse RNA-seq datasets in GEO →

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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.