GEO series

Nociceptor-immune interactomes reveal insult-specific immune signatures of pain

GSE255686 Mus musculus (mouse) Single-cell RNA-seq 24 samples Submitted 2024/05/28 Platform GPL24247

At a glance

Single-cell RNA-seq · mouse · 24 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: 24 samples: 9 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.
Paper: Nociceptor-immune interactomes reveal insult-specific immune signatures of painNature immunology · 2024

Summary (written by the submitters)

Inflammatory pain associated with tissue injury and infection largely results from the heightened sensitivity of the peripheral terminals of nociceptor sensory neurons as a consequence of exposure to inflammatory mediators. Targeting immune-derived inflammatory ligands, such as prostaglandin E2, reduces inflammatory pain, but more effective and safer therapies are needed.

Read the full summary ↓

However, the diversity of immune cell and sensory neuron types, their ligands, and receptors make it challenging to map the immune mechanisms that contribute to inflammatory pain. We, therefore, used single-cell transcriptomics to explore which specific immune cell types affect the development of pain in diverse inflammatory pain models. We found that both the magnitude of macrophage and neutrophil recruitment and the injury-triggered transcriptional program in Cx3cr1 high and MHCII+ dermal macrophages closely mirror the kinetics of inflammatory pain hypersensitivity. We constructed a comprehensive list of potential cell-cell interactions covering receptors, ligands, and metabolites, and generated injury-specific neuroimmune interactomes based on immune cell and sensory neuron single-cell transcriptomic data. This analysis revealed both interactions common to multiple inflammatory pain models and those specific to a particular condition and uncovered immune mediators not previously identified as pain modulators.

Published in

Nociceptor-immune interactomes reveal insult-specific immune signatures of pain

Jain A, Gyori BM, Hakim S et al. · Nature immunology 2024 · PMID 38806708 · doi:10.1038/s41590-024-01857-2

This dataset

Open GSE255686 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 GSE255686_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 PRJNA1076164 and SRA study SRP489648. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 38806708) ↗

Study design

9 conditions, mostly in duplicate

uvb, contra, ×8 zymosan, contra, ×2 zymosan, 4h, ×2 zymosan, 24h, ×2 zymosan, 48h, ×2 incision, contra, ×2 incision, 4h, ×2 incision, 24h, ×2 +1 more

Supports a between-group comparison across 24 samples.

How we read this: 9 replicated groups read from 24 sample titles; they account for 24 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

GSM8077728 zymosan, contra, replicate 1 zymosan, contra,
GSM8077729 zymosan, 4h, replicate 1 zymosan, 4h,
GSM8077730 zymosan, 24h, replicate 1 zymosan, 24h,
GSM8077731 zymosan, 48h, replicate 1 zymosan, 48h,
GSM8077732 zymosan, contra, replicate 2 zymosan, contra,
GSM8077733 zymosan, 4h, replicate 2 zymosan, 4h,
GSM8077734 zymosan, 24h, replicate 2 zymosan, 24h,
GSM8077735 zymosan, 48h, replicate 2 zymosan, 48h,
GSM8077736 incision, contra, replicate 1 incision, contra,
GSM8077737 incision, 4h, replicate 1 incision, 4h,
GSM8077738 incision, 24h, replicate 1 incision, 24h,
GSM8077739 incision, 48h, replicate 1 incision, 48h,
GSM8077740 incision, contra, replicate 2 incision, contra,
GSM8077741 incision, 4h, replicate 2 incision, 4h,
GSM8077742 incision, 24h, replicate 2 incision, 24h,
GSM8077743 incision, 48h, replicate 2 incision, 48h,
GSM8077744 uvb, contra, replicate 17 uvb, contra,
GSM8077745 uvb, contra, replicate 18 uvb, contra,
GSM8077746 uvb, contra, replicate 19 uvb, contra,
GSM8077747 uvb, contra, replicate 20 uvb, contra,
GSM8077748 uvb, contra, replicate 21 uvb, contra,
GSM8077749 uvb, contra, replicate 22 uvb, contra,
GSM8077750 uvb, contra, replicate 23 uvb, contra,
GSM8077751 uvb, contra, replicate 24 uvb, contra,

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