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mRNA-based influenza vaccine expands the breadth of the B cell response in humans

GSE328165 Homo sapiens (human) RNA-seq (gene expression) 109 samples Submitted 2026/04/18 Platform GPL34281
At a glance

RNA-seq (gene expression) · human · 109 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
Homo sapiens (human)
Samples
109 samples: 54 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.
Summary (written by the submitters)
Eliciting durable antibody responses against rapidly evolving pathogens such as the influenza virus remains a formidable challenge. Conventional influenza virus vaccines are poorly immunogenic and induce antibody responses of limited breadth. Germinal center (GC) reactions in draining lymph nodes are key sites for antibody diversification and affinity maturation following vaccination.
Read the full summary ↓
Whether an mRNA-based influenza virus vaccine can induce a superior GC response in humans compared to conventional vaccines remains unclear. We assessed B cell responses in an observational study of cohorts of healthy young adults receiving a licensed, split-virion or an investigative mRNA-based quadrivalent seasonal influenza virus vaccine over two consecutive seasons. mRNA-based vaccines consistently elicited higher antibody titers and frequencies of memory B cells. In the draining lymph nodes, mRNA vaccination stimulated sustained GC reactions that persisted for at least 26 weeks post vaccination in five of thirteen participants across the two seasons. To understand how sustained GC activity shapes the secreted serum IgG repertoire, we performed proteomic analysis of serum IgG repertoire. mRNA vaccination increased the number of vaccine-elicited serum IgG clonotypes and promoted intraclonal expansion within pre-existing clonotypes. B cell lineage analyses further indicated that expanded serum clonotypes map to GC B cell-associated subbranches, consistent with ongoing GC-driven evolution underlying intraclonal expansion. This repertoire remodeling was accompanied by increased binding breadth against antigenically divergent influenza viruses. These findings reveal a key role for persistent GC responses in broadening the repertoire of vaccine-induced antibodies.
This dataset
Open GSE328165 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 GSE328165_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 PRJNA1049392 and SRA study SRP476540. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
54 conditions, mostly in duplicate
397-17 d0 MBC ×2 397-17 d8 PB ×2 397-17 d121 MBC ×2 397-17 d0 FNA ×2 397-17 d15 FNA ×2 397-17 d57 FNA ×2 397-17 d121 FNA ×2 397-17 d181 FNA ×2 +47 more

Supports a between-group comparison across 108 samples.

How we read this: 54 replicated groups read from 109 sample titles; they account for 108 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

+ 69 more — browse all 109 samples with per-sample file links →

Datasets on a similar topic

Search all human RNA-seq datasets in GEO →

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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.