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Induction of a distinct macrophage population and protection from lung injury and fibrosis by Notch2 blockade

GSE243289 Mus musculus (mouse) Single-cell RNA-seq 30 samples Submitted 2024/09/14 Platform GPL17021Platform GPL30172Platform GPL24247
At a glance

Single-cell RNA-seq · mouse · 30 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
30 samples: 11 conditions, mostly in duplicateGroups 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)
Macrophages are pleiotropic and diverse cells that populate all tissues of the body. Besides tissue-specific resident macrophages such as alveolar macrophages, Kupffer cells and microglia, multiple organs harbor at least two subtypes of other resident macrophages at steady state. During certain circumstances, like tissue insult, additional subtypes of macrophages are recruited to the tissue from the monocyte pool.
Read the full summary ↓
Recently, a recruited macrophage population marked by expression of Spp1, Cd9, Gpnmb, Fabp5, and Trem2 has been described in several models of organ injury and cancer, and linked to fibrosis in mice and humans. Here, we show that Notch2 blockade given systemically or locally led to an increase in this putative pro-fibrotic macrophage in the lung. Single cell RNA sequencing suggested that the newly arising population derived from monocytes when Notch2 blockade was systemic or derived from alveolar macrophages when Notch2 blockade was local. Unexpectedly, using a bleomycin and COVID19 model of lung injury and fibrosis, we found that the expansion of these macrophages before lung injury ameliorated rather than promoted fibrosis. This suggests that these damage-associated macrophages are not drivers of fibrosis in the lung.
This dataset
Open GSE243289 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 GSE243289_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: 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 PRJNA1017540 and SRA study SRP460645. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
11 conditions, mostly in duplicate
IP_InterstitialMacrophages_gex ×2 IP_AlveolarMacrophages_gex ×2 IP_Monocytes_gex ×2 IP_InterstitialMacrophages_adt ×2 IP_AlveolarMacrophages_adt ×2 IP_Monocytes_adt ×2 IP_Bleo_Monocytes_hto ×2 IP_Bleo_AlveolarMacrophages_hto ×2 +11 more

Supports a between-group comparison across 22 samples.

How we read this: 11 replicated groups read from 30 sample titles; they account for 22 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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