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Nanoengineered STING Mucosal Adjuvant Activates Coordinated Mucosal-Systemic Immunity for Durable Cross-Protective Defense

GSE297387 Mus musculus (mouse) Single-cell RNA-seq 24 samples Submitted 2025/05/21 Platform GPL24247
At a glance

Single-cell RNA-seq · mouse · 24 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
Organism
Mus musculus (mouse)
Samples
24 samples: 3 × SSM2,24H,sample vs 3 × NanoCF501/SSM2,24H,sample vs 3 × SSM2,Day 35,sample vs 3 × NanoCF501/SSM2,Day 35,sampleGroups 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)
A longstanding barrier in vaccinology has been the inability to reconcile potent mucosal immune activation with systemic tolerability, hindering adjuvant development for over a century. Here, we present NanoCF501, a nanoparticulate STING agonist engineered with respiratory-tuned, clinically safe polymers, which overcomes this fundamental limitation.
Read the full summary ↓
When co-administered with a multivalent pan-β-coronavirus subunit vaccine, NanoCF501 at 1/20th the systemic adjuvant dose elicits coordinated mucosal-systemic immunity, inducing robust and durable cross-protective responses. These include mucosal secretory IgA and tissue-resident memory T cells alongside systemic neutralizing antibodies, memory B cells, and long-lived plasma cells persisting >12 months in murine models. Non-human primates validate the dual-axis mucosal-systemic coupling, while toxicology studies in rats demonstrate more than 18-fold safety margin and undetectable systemic exposure, underscoring translational viability. Mechanistic interrogation via single-cell transcriptomics reveals that NanoCF501 drives STING-dependent innate immune activation, orchestrating broad transcriptional reprogramming in lung antigen-presenting cells and efficient priming of adaptive T and B cell responses. Notably, NanoCF501 converts conventional quadrivalent influenza subunit vaccines into mucosal immunogenic formulations, demonstrating platform versatility. By integrating rational nanocarrier design with innate immune targeting, this work establishes a universal mucosal vaccination strategy with broad implications for pandemic preparedness and mucosal vaccinology.
This dataset
Open GSE297387 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 GSE297387_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 PRJNA1263728 and SRA study SRP586035. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
3 × SSM2,24H,sample vs 3 × NanoCF501/SSM2,24H,sample vs 3 × SSM2,Day 35,sample vs 3 × NanoCF501/SSM2,Day 35,sample

Supports a between-group comparison across 12 samples.

How we read this: 4 replicated groups read from 24 sample titles; they account for 12 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
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