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TL1A and IL-18 synergy promotes GM-CSF dependent thymic emergency granulopoiesis

GSE244172 Mus musculus (mouse) Single-cell RNA-seq 12 samples Submitted 2024/09/05 Platform GPL21103Platform GPL24247
At a glance

Single-cell RNA-seq · mouse · 12 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
12 samples: 12 samples, each with a distinct title — no replicated groupsGroups 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
TL1A and IL-18 synergy promotes GM-CSF-dependent thymic granulopoiesis in miceCellular & molecular immunology · 2024
Summary (written by the submitters)
The current model of hematopoiesis only resolves the thymus around the production and establishment of the peripheral T cell pool. However, the role and in situ development of other immune subsets has been overlooked. We aim to demonstrate that during TL1A and IL-18 induced inflammation, the thymus is capable of producing other cell types such as neutrophils, monocytes, and macrophages and that these potentially have other functions aside from supporting T cell development as scavengers.
Read the full summary ↓
Here we have proven that ex vivo and in vivo treatment with TL1A and IL-18 results in acute thymic atrophy by a massive loss of DP T cells and shrinking of the thymic lobe. By electron microscopy, flow cytometry and single cell we demonstrate that neutrophils are able to maturate inside the thymus lobe in a NOTCH-independent manner. We used fate-mapping tools to elucidate the origin of thymic neutrophils since we observed a great expansion in our culture that is isolated from the influx of BM progenitors. The Rag1-Cre Rosa26-YFP fate mapping model revealed that neutrophils share a common progenitor with T cells, while monocytes/macrophages do not. Furthermore, we found that most of the thymic GMPs (defined as Lin-Sca-1-c-Kit+CD16/32+CD34+) show history of Rag1 expression in comparison with bone marrow GMPs. Additionally, by using Ms4a3-Cre Rosa26Tdtomato fate mapping model we observed that there was not difference in Tdt labeling between the thymus and bone marrow, suggesting that thymic neutrophils still undergo conventional neutrophils pathway arising from GMPs. Moreover, we show that thymic-derived neutrophils are functional and are capable of forming extracellular neutrophils traps (NETs) similarly to benchmark peritoneal neutrophils. We found that the expansion of thymic neutrophils is GM-CSF dependent by using Csf2rb KO mice. Additionally, we identified DR3+ and IL-18Rα+ expressing subsets of ILCs and gdT cells as the cellular source GM-CSF. Lastly, in vivo treatment with TL1A+IL-18 lead to emergency granulopoiesis and an increase of neutrophils in all the organs investigated, including the thymus.
Published in
TL1A and IL-18 synergy promotes GM-CSF-dependent thymic granulopoiesis in mice
Ruiz Pérez M, Maueröder C, Steels W et al. · Cellular & molecular immunology 2024 · PMID 38839915 · doi:10.1038/s41423-024-01180-8
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 GSE244172_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: 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 PRJNA1021587 and SRA study SRP463509. Searching any of these in the dataset finder brings you back here.

Study design
12 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 12 sample titles: 12 distinct titles with little repetition. 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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