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MVA-based SARS-CoV-2 vaccine candidates encoding different spike protein conformations induce distinct early transcriptional responses which may impact subsequent adaptive immunity

GSE276544 Homo sapiens (human) RNA-seq (gene expression) 305 samples Submitted 2025/01/07 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 305 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
305 samples: 86 conditions, mostly with about 4 replicates eachGroups 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
MVA-based SARS-CoV-2 vaccine candidates encoding different spike protein conformations induce distinct early transcriptional responses which may impact subsequent adaptive immunityFrontiers in immunology · 2024
Summary (written by the submitters)
Introduction: Vaccine platforms such as viral vectors and mRNA can accelerate vaccine development in response to newly emerging pathogens, as demonstrated during the COVID-19 pandemic. However, the differential effects of platform and antigen insert on vaccine immunogenicity remain incompletely understood. Innate immune responses induced by viral vector vaccines are suggested to have an adjuvant effect for subsequent adaptive immunity.
Read the full summary ↓
Integrating data on both innate and adaptive immunity, systems vaccinology approaches can improve the understanding of vaccine-induced immune mechanisms. Methods: Two vaccine candidates against SARS-CoV-2, both based on the viral vector Modified Vaccinia virus Ankara (MVA) and encoding the native (MVA SARS-2-S) or prefusion-stabilized spike protein (MVA-SARS-2-ST), were evaluated in phase 1 clinical trials (ClinicalTrials.gov: NCT04569383, NCT04895449). Longitudinal dynamics of innate and early adaptive immune responses induced by vaccination in SARS-CoV-2-naïve individuals were analyzed based on transcriptome and flow cytometry data, in comparison to the licensed ChAd and mRNA vaccines. Results: Compared to MVA-SARS-2-S, MVA-SARS-2-ST (encoding the prefusion-stabilized spike protein) induced a stronger transcriptional activation early after vaccination, as well as higher virus neutralizing antibodies. Positive correlations were observed between innate and adaptive immune responses induced by a second MVA-SARS-2-ST vaccination. MVA-, ChAd- and mRNA-based vaccines induced distinct immune signatures, with the overall strongest transcriptional activation as well as monocyte and T follicular helper cell responses induced by ChAd. Discussion: Our findings suggest a potential impact of the spike protein conformation not only on adaptive but also on innate immune responses. As indicated by positive correlations between several immune parameters induced by MVA-SARS-2-ST, the distinct transcriptional activation early after vaccination may be linked to the induction of classical monocytes and activation of cTFH1 cells, which may in turn result in the superior adaptive immunogenicity of MVA-SARS-2-ST, compared to MVA-SARS-2-S. Overall, our data demonstrate that both the vaccine platform and antigen insert can affect innate immune responses and subsequent vaccine immunogenicity in humans.
Published in
MVA-based SARS-CoV-2 vaccine candidates encoding different spike protein conformations induce distinct early transcriptional responses which may impact subsequent adaptive immunity
Grewe I, Friedrich M, Dieck ML et al. · Frontiers in immunology 2024 · PMID 39749328 · doi:10.3389/fimmu.2024.1500615
This dataset
Open GSE276544 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 GSE276544_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 PRJNA1157815. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39749328) ↗
Study design
86 conditions, mostly with about 4 replicates each
ChAd/mRNA_01_V1D ×4 ChAd/mRNA_02_V1D ×4 ChAd/mRNA_03_V1D ×4 ChAd/mRNA_04_V1D ×4 ChAd/mRNA_05_V1D ×4 ChAd/mRNA_06_V1D ×4 ChAd/mRNA_07_V1D ×4 ChAd/mRNA_08_V1D ×4 +78 more

Supports a between-group comparison across 305 samples.

How we read this: 86 replicated groups read from 305 sample titles; they account for 305 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

+ 265 more — browse all 305 samples with per-sample file links →

Datasets on a similar topic

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