GEO series

B cells mediate lung ischemia-reperfusion injury by recruitment of CCR2+-classical monocytes via synergistic BCR-TLR4 signaling

GSE249242 Mus musculus (mouse) RNA-seq (gene expression) 3 samples Submitted 2024/03/20 Platform GPL24247

At a glance

RNA-seq (gene expression) · mouse · 3 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: 3 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.
Paper: B cells mediate lung ischemia/reperfusion injury by recruiting classical monocytes via synergistic B cell receptor/TLR4 signalingThe Journal of clinical investigation · 2024

Summary (written by the submitters)

Ischemia reperfusion injury (IRI)-mediated primary graft dysfunction (PGD) adversely impacts both short- and long-term outcomes after lung transplantation, a procedure which remains the only treatment option for patients suffering from end-stage respiratory failure. While B cells can regulate adaptive immune responses through antibody production, antigen presentation and secretion of cytokines, their role in lung IRI is not well understood.

Read the full summary ↓

Here, we demonstrate by intravital imaging that B cells are rapidly recruited to injured lungs, where they extravasate into the parenchyma. Using hilar clamping and transplant models, we observe that lung-infiltrating B cells produce the monocyte chemokine CCL7 in Toll-like receptor 4 (TLR4)-TRIF-dependent fashion, a critical step contributing to classical monocyte (CM) recruitment and subsequent neutrophil extravasation, resulting in worse lung function. We find that synergistic BCR-TLR4 activation on B cells is required for the recruitment of CMs to the injured lung. Finally, we corroborate our findings in reperfused human lungs, where we observe a correlation between B cell infiltration and CM recruitment after transplantation. This study uncovers a role for B cells as critical orchestrators of lung IRI. As B cells can be depleted with currently available agents, our study provides a rationale for clinical trials investigating B cell-targeting therapies.

Published in

B cells mediate lung ischemia/reperfusion injury by recruiting classical monocytes via synergistic B cell receptor/TLR4 signaling

Farahnak K, Bai YZ, Yokoyama Y et al. · The Journal of clinical investigation 2024 · PMID 38488011 · doi:10.1172/JCI170118

This dataset

Open GSE249242 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 GSE249242_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 PRJNA1048299 and SRA study SRP475590. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 38488011) ↗

Samples in this study

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+ 3 more — browse all 3 samples with per-sample file links →

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