GEO series

Lymphocyte-derived cholinergic circuits modulate germinal center output and B cell activation

GSE316392 Mus musculus (mouse) RNA-seq (gene expression) 16 samples Submitted 2026/03/06 Platform GPL19057

At a glance

RNA-seq (gene expression) · mouse · 16 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: 16 samples: 4 × GFP negative GC B cells vs 4 × GFP negative Tfh cells vs 4 × GFP positive Tfh cells vs 4 × GFP positive GC B cellsGroups 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: Lymphocyte-derived cholinergic circuits modulate germinal center output and B cell activationNature immunology · 2026

Summary (written by the submitters)

Germinal centers (GCs) are specialized lymphoid structures in which activated B cells undergo clonal selection and B cell receptor (BCR) somatic hypermutation to generate high-affinity antibodies. Previous work has shown that T cells expressing choline acetyltransferase (ChAT), the enzyme that synthesizes acetylcholine (ACh), are linked to the production of high-affinity antibodies in the GC response.

Read the full summary ↓

However, whether B cells in the GC also express ChAT, and the details of the interplay of cholinergic circuits within the GC, remain unclear. Here, we show that ChAT expressed by GC B cells contributes to the early accumulation of high-affinity GC B cells following antigen encounter. We identify key transcriptional regulators of ChAT expression in GC B cells, and demonstrate that ACh receptor (AChR) expression is dynamically coordinated during B cell activation. In vitro, we show that ACh binding to muscarinic AChRs limits plasma cell differentiation and dampens BCR signal transduction to fine-tune the threshold for affinity-based positive selection. Together, these findings reveal a previously unrecognized regulatory axis that operates early during GC selection and employs cholinergic signals to shape B cell fate decisions and humoral immunity.

Published in

Lymphocyte-derived cholinergic circuits modulate germinal center output and B cell activation

Nechanitzky D, Smith LK, Nechanitzky R et al. · Nature immunology 2026 · PMID 41735533 · doi:10.1038/s41590-026-02444-3

This dataset

Open GSE316392 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 GSE316392_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 PRJNA1402430 and SRA study SRP661924. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41735533) ↗

Study design

4 × GFP negative GC B cells vs 4 × GFP negative Tfh cells vs 4 × GFP positive Tfh cells vs 4 × GFP positive GC B cells

Supports a between-group comparison across 16 samples.

How we read this: 4 replicated groups read from 16 sample titles; they account for 16 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

GSM9451561 GFP negative GC B cells 1 GFP negative GC B cells
GSM9451562 GFP negative Tfh cells 1 GFP negative Tfh cells
GSM9451563 GFP positive Tfh cells 1 GFP positive Tfh cells
GSM9451564 GFP positive GC B cells 2 GFP positive GC B cells
GSM9451565 GFP negative GC B cells 2 GFP negative GC B cells
GSM9451566 GFP negative Tfh cells 2 GFP negative Tfh cells
GSM9451567 GFP positive Tfh cells 2 GFP positive Tfh cells
GSM9451568 GFP positive GC B cells 3 GFP positive GC B cells
GSM9451569 GFP negative GC B cells 3 GFP negative GC B cells
GSM9451570 GFP negative Tfh cells 3 GFP negative Tfh cells
GSM9451571 GFP positive Tfh cells 3 GFP positive Tfh cells
GSM9451572 GFP positive GC B cells 4 GFP positive GC B cells
GSM9451573 GFP negative GC B cells 4 GFP negative GC B cells
GSM9451574 GFP negative Tfh cells 4 GFP negative Tfh cells
GSM9451575 GFP positive Tfh cells 4 GFP positive Tfh cells
GSM9451576 GFP positive GC B cells 1 GFP positive GC B cells

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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.