GEO series

Macrophages direct location-dependent recall of B cell memory to vaccination [scRNA-seq and scVDJ-seq]

GSE291745 Homo sapiens (human) Single-cell RNA-seq 24 samples Submitted 2025/06/30 Platform GPL24676

At a glance

Single-cell RNA-seq · human · 24 samples

What it is: Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
Organism: Homo sapiens (human)
Samples: 24 samples: 24 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: Macrophages direct location-dependent recall of B cell memory to vaccinationCell · 2025

Summary (written by the submitters)

Vaccines generate long-lived plasma cells and memory B cells (Bmems) that may re-enter secondary germinal centers (GCs) to further mutate their B cell receptor upon boosting and re-exposure to antigen. We show that lymph nodes draining the primary vaccination site harbour a subset of Bmems that reside in the subcapsular niche, generate larger recall responses, and are more likely to re-enter GCs compared to circulating Bmems in non-draining lymph nodes.

Read the full summary ↓

Depletion of CD169+ subcapsular sinus macrophages impairs Bmem proliferative expansion, secondary GC formation and secretion of affinity-matured antibodies upon boosting of the draining lymph node. This site-specific, niche-dependent control is associated with more rapid secretion of broadly neutralizing antibodies, GC participation and clonal expansion of SARS-CoV-2-specific B cells in healthy volunteers boosted with the BNT162b2 vaccine in the same versus opposite arm. These data reveal an unappreciated role for primed draining lymph node SSMs in Bmem cell fate determination.

Published in

Macrophages direct location-dependent recall of B cell memory to vaccination

Dhenni R, Carey Hoppé A, Reynaldi A et al. · Cell 2025 · PMID 40300604 · doi:10.1016/j.cell.2025.04.005

This dataset

Open GSE291745 in finder → Find more human 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 GSE291745_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 PRJNA1235184 and SRA study SRP569872. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40300604) ↗

Study design

24 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 24 sample titles: 24 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

GSM8841578 COVAX_007L_GEX
GSM8841579 COVAX_007L_VDJ-B
GSM8841580 COVAX_007R_GEX
GSM8841581 COVAX_007R_VDJ-B
GSM8841582 COVAX_008L_GEX
GSM8841583 COVAX_008L_VDJ-B
GSM8841584 COVAX_008R_GEX
GSM8841585 COVAX_008R_VDJ-B
GSM8841586 COVAX_010L_GEX
GSM8841587 COVAX_010L_VDJ-B
GSM8841588 COVAX_010R_GEX
GSM8841589 COVAX_010R_VDJ-B
GSM8841590 COVAX_011L_GEX
GSM8841591 COVAX_011L_VDJ-B
GSM8841592 COVAX_011R_GEX
GSM8841593 COVAX_011R_VDJ-B
GSM8841594 COVAX_012L_GEX
GSM8841595 COVAX_012L_VDJ-B
GSM8841596 COVAX_012R_GEX
GSM8841597 COVAX_012R_VDJ-B
GSM8841598 COVAX_015L_GEX
GSM8841599 COVAX_015L_VDJ-B
GSM8841600 COVAX_015R_GEX
GSM8841601 COVAX_015R_VDJ-B

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