GEO series

Comparison of extracellular vesicles isolation methods reveals method-dependent protein and miRNA profiles in saliva

GSE312585 Homo sapiens (human) RNA-seq (gene expression) 12 samples Submitted 2025/12/05 Platform GPL18573

At a glance

RNA-seq (gene expression) · human · 12 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: 12 samples
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)

Salivary extracellular vesicles (EVs) represent a powerful, non-invasive source of biomarkers for disease diagnosis and monitoring. Their molecular cargo reflects systemic and local physiological states, offering a window into neurological and inflammatory disorders. However, the diversity of EV isolation protocols and the possibility that each enriches distinct EV subpopulations remains a major barrier to reproducibility and data comparability.

Read the full summary ↓

We conducted a comprehensive comparison of three EV isolation methods: ultracentrifugation (UC), PEG-based precipitation (Q), and immunoaffinity capture (M) to evaluate their impact on EV yield, purity, and molecular composition. Salivary EVs from healthy volunteers were analysed using proteomic and small-RNA sequencing approaches. Principal component analysis revealed clear isolation method-dependent clustering, where M-derived EVs displayed the most distinct profile. UC and Q produced broader proteomic repertoires with higher total protein content, whereas M-isolated EVs exhibited greater purity and enrichment of trafficking- and lysosome-associated proteins. Over 731 miRNAs selected, 28 were consistently altered across methods and 65 uniquely enriched in M isolates. RT-qPCR confirmed key directional trends. These 93 method-dependent miRNAs have predicted targets associated with synaptic structure and neurodegenerative pathways. These findings show that isolation methodology deeply shapes salivary EV cargo and suggest that immunoaffinity capture can isolate specific EV populations meeting diagnostic requirements.

This dataset

Open GSE312585 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 GSE312585_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 PRJNA1374215 and SRA study SRP651479. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Samples in this study

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+ 12 more — browse all 12 samples with per-sample file links →

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