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Inflammation durably imprints memory CD4+ T cells

GSE233046 Homo sapiens (human) RNA-seq (gene expression) 73 samples Submitted 2024/03/15 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 73 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
73 samples: 73 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
SARS-CoV-2 inflammation durably imprints memory CD4 T cellsScience immunology · 2024
Summary (written by the submitters)
Memory CD4 T cells are critical to human immunity, yet it is unclear if viral inflammation during memory formation has long-term consequences. Here, we compared transcriptional and epigenetic landscapes of Spike (S)-specific memory CD4 T cells in 24 individuals whose first exposure to S was via SARS-CoV-2 infection or mRNA vaccination.
Read the full summary ↓
Nearly two years after memory formation, S-specific CD4 T cells established by infection remained enriched for transcripts related to cytotoxicity and for interferon-stimulated genes, likely due to a chromatin accessibility landscape altered by inflammation. Moreover, S-specific CD4 T cells primed by infection had reduced proliferative capacity in vitro relative to vaccine-primed cells. Furthermore, the transcriptional state of S-specific memory CD4 T cells was minimally altered by booster immunization and/or breakthrough infection. Thus, these data demonstrate the durable imprint of inflammation on CD4 T cell memory which affected function and may have consequences for long-term immunity.
Published in
SARS-CoV-2 inflammation durably imprints memory CD4 T cells
Gray-Gaillard SL, Solis SM, Chen HM et al. · Science immunology 2024 · PMID 38905326 · doi:10.1126/sciimmunol.adj8526
This dataset
Open GSE233046 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 GSE233046_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 PRJNA974831 and SRA study SRP438830. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 38905326) ↗
Study design
73 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 73 sample titles: 73 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

+ 33 more — browse all 73 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.