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Polymicrobial extracellular vesicles reduce the innate immune response of human cystic fibrosis bronchial epithelial cells

GSE325885 Homo sapiens (human) RNA-seq (gene expression) 28 samples Submitted 2026/04/11 Platform GPL30173
At a glance

RNA-seq (gene expression) · human · 28 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
28 samples: 28 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
Polymicrobial extracellular vesicles reduce the innate immune response of human cystic fibrosis bronchial epithelial cellsbioRxiv : the preprint server for biology · 2026
Summary (written by the submitters)
Adults with cystic fibrosis (CF) have chronic antibiotic-resistant polymicrobial lung infections, the leading cause of death in CF. We developed a polymicrobial culture model containing four genera that represents a ‘pulmotype’ detected in ~34% of lung infections in people with CF (pwCF), and accounts for 27% of the variability in lung function.
Read the full summary ↓
This community, comprised of Pseudomonas aeruginosa, Staphylococcus aureus, Streptococcus sanguinis, and Prevotella melaninogenica, is grown in synthetic CF media (SCFM2) under anoxic conditions that mimic the environment in mucus plugs in CF. We have shown that Pseudomonas in monoculture communicates with primary human bronchial epithelial cells (pHBEC) by secreting bacterial extracellular vesicles (bEVs) that diffuse through mucus and deliver virulence factors, DNA, and RNA to pHBEC. We report herein that each bacterial genus in the polymicrobial community secretes bEVs containing proteins and RNAs predicted to promote the establishment of chronic infection by enhancing virulence and biofilm formation, and upregulating the stress response and pro-inflammatory pathways in pHBEC. This response is most pronounced in CF pHBEC. Trikafta, a highly effective drug, does not ameliorate the response or return it to WT levels. Bacterial EVs also inhibited Trikafta-stimulated CFTR Cl- currents by CF pHBEC. These studies provide insight into why Trikafta does not eliminate polymicrobial lung infections and a hyperinflammatory lung environment in pwCF.
Published in
Polymicrobial extracellular vesicles reduce the innate immune response of human cystic fibrosis bronchial epithelial cells
Charpentier LA, Barnaby RL, Roche CT et al. · bioRxiv : the preprint server for biology 2026 · PMID 41993502 · doi:10.64898/2026.04.09.717493
This dataset
Open GSE325885 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 GSE325885_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 PRJNA1442136 and SRA study SRP686305. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41993502) ↗
Study design
28 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 28 sample titles: 28 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
Datasets on a similar topic

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