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Peptide-based capture-and-release purification of extracellular vesicles and statistical algorithm enabled quality assessment

ABSTRACT: Extracellular vesicles (EVs) have gained significant attention in the field of extracellular communication, holding promise as intercellular messengers and diagnostic biomarkers. However, the challenges in isolating and purifying EVs from complex biological samples have hindered their widespread utility. This study presents a novel EV isolation strategy leveraging bioinformatics, utilizing the pH-low insertion peptide (pHLIP) to capture and release EVs under controlled conditions. The pHLIP-magnetic bead approach was developed to achieve efficient EV isolation, addressing the persistent issue of EV isolation method comparability. EVs from human plasma were isolated and characterized using various techniques, offering insights into the proposed isolation method's efficacy. A data science-driven statistical metric integrating multiple characterizations was applied to enable direct comparisons between different isolation methods. Next generation sequencing was applied to examine how the observed RNA-population differences across isolated EVs may lead researchers to different conclusions. This research contributes to the advancement of reliable and rigorous EV isolation methods and their potential clinical applications.

ORGANISM(S): Homo sapiens

PROVIDER: GSE246925 | GEO | 2024/01/31

REPOSITORIES: GEO

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Project description:Circulating extracellular vesicles (EVs) contain molecular footprints - lipids, proteins, metabolites, RNA, and DNA - from their cell of origin and may provide non-invasive access for detection, characterization, and monitoring of diseases. Consequently, EV-associated RNA and proteins have gained widespread interest in developing liquid-biopsy assays for cancer. Yet, an integrative proteo-transcriptomic landscape of EVs and a direct comparison with their cell of origin remains relatively unexplored. Here, we report that EVs enrich for distinct molecular cargo and their proteo-transcriptome does not linearly correlate with their cell of origin. Our sub-cellular compartment analyses revealed that EV enrich 2-6 times more cytoskeletal and extracellular proteins, while their donor cells cargo 3-10 times more nuclear and mitochondrial proteins. EVs predominantly enrich (40-60%) for small RNA between ~15-200 nucleotides, which include miRNAs, siRNAs, tRNA, 5S rRNAs, and snRNAs, associated with cell differentiation, development, and Wnt signaling signatures. Finally, our integrated proteo-transcriptomic analyses reveal that EVs are enriched with specific small RNAs (RNY3, vtRNA, and MIRLET-7) and their complementary proteins (YBX1, IGF2BP2, SRSF1/2). These analyses suggest that RNA-protein complexes may constitute a functional interaction network inside EVs to protect and regulate access to EV-RNA. To ensure that our analyses are unbiased and independent of the cell of origin, EV isolation methods, site of experimentation, site of data generation, and methodologies applied for RNAseq and mass spectrometry, we have generated and curated comprehensive datasets of proteomics and transcriptomics from a total of 12 cancer cell lines, their EVs, and prostate cancer patientsÕ serum EVs (A detailed description is provided in Fig. 1). These combined analyses demonstrated that irrespective of the cell of origin and other aforementioned conditions, EVs enrich for distinct RNA and protein signatures that do not linearly correlate with their cell of origin.

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Peptide-based capture-and-release purification of extracellular vesicles and statistical algorithm enabled quality assessment

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